2026-05-18T20:43:34 - INFO: Slick 0.0.8a13

🟢 Starting Calibration Pipeline

=== Processing MDCP3D-SL-007_W038_2026_05_05 ===
2026-05-18T20:43:34 - INFO: Camera ID: 06PFP
2026-05-18T20:43:34 - INFO: Wand ID: 00001f0c2bba
2026-05-18T20:43:34 - INFO: Recorded At: 2026-05-05T14:52:44Z

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                        Step 1: Digitization                       
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[🔄] Full PTD mode: Processing ALL images then creating calibration subset
[📸] Digitizing ALL images...
[📸] Full dataset mode: Processing ALL images (no debug visualizations)
[INFO] Found 4 las0.zip files to process

Processing Rigs:   0%|          | 0/4 [00:00<?, ?it/s][INFO] Filtered 447 stationary frames, 577 remain


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→ 2000L (577 images) Phase 1:  22%|██▏       | 129/577 [00:02<00:04, 90.94it/s]

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→ 2000L (577 images) Phase 1:  55%|█████▌    | 320/577 [00:04<00:03, 84.88it/s]

→ 2000L (577 images) Phase 1:  57%|█████▋    | 331/577 [00:05<00:03, 62.47it/s]

→ 2000L (577 images) Phase 1:  60%|██████    | 348/577 [00:05<00:02, 80.93it/s]

→ 2000L (577 images) Phase 1:  62%|██████▏   | 359/577 [00:05<00:03, 62.58it/s]

→ 2000L (577 images) Phase 1:  64%|██████▍   | 371/577 [00:05<00:02, 72.19it/s]

→ 2000L (577 images) Phase 1:  67%|██████▋   | 384/577 [00:05<00:02, 77.02it/s]

→ 2000L (577 images) Phase 1:  68%|██████▊   | 394/577 [00:06<00:02, 62.80it/s]

→ 2000L (577 images) Phase 1:  71%|███████   | 408/577 [00:06<00:02, 76.15it/s]

→ 2000L (577 images) Phase 1:  72%|███████▏  | 418/577 [00:06<00:02, 61.93it/s]

→ 2000L (577 images) Phase 1:  74%|███████▍  | 426/577 [00:06<00:02, 65.11it/s]

→ 2000L (577 images) Phase 1:  77%|███████▋  | 442/577 [00:06<00:01, 84.54it/s]

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→ 2000L (577 images) Phase 1:  80%|████████  | 463/577 [00:07<00:01, 69.49it/s]

→ 2000L (577 images) Phase 1:  83%|████████▎ | 479/577 [00:07<00:01, 86.80it/s]

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→ 2000L (577 images) Phase 1:  94%|█████████▍| 543/577 [00:08<00:00, 85.84it/s]

→ 2000L (577 images) Phase 1:  96%|█████████▌| 554/577 [00:08<00:00, 63.85it/s]

→ 2000L (577 images) Phase 1: 100%|█████████▉| 575/577 [00:08<00:00, 87.64it/s]

                                                                               

→ 2000L Phase 2: corners:   0%|          | 0/576 [00:00<?, ?it/s]

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→ 2000L Phase 2: corners:  59%|█████▉    | 341/576 [00:02<00:01, 147.14it/s]

→ 2000L Phase 2: corners:  62%|██████▏   | 356/576 [00:02<00:01, 137.03it/s]

→ 2000L Phase 2: corners:  65%|██████▍   | 373/576 [00:02<00:01, 142.77it/s]

→ 2000L Phase 2: corners:  68%|██████▊   | 391/576 [00:02<00:01, 152.48it/s]

→ 2000L Phase 2: corners:  71%|███████   | 409/576 [00:03<00:01, 158.21it/s]

→ 2000L Phase 2: corners:  74%|███████▍  | 425/576 [00:03<00:00, 151.42it/s]

→ 2000L Phase 2: corners:  77%|███████▋  | 443/576 [00:03<00:00, 156.67it/s]

→ 2000L Phase 2: corners:  80%|███████▉  | 459/576 [00:03<00:00, 154.37it/s]

→ 2000L Phase 2: corners:  82%|████████▏ | 475/576 [00:03<00:00, 145.76it/s]

→ 2000L Phase 2: corners:  85%|████████▌ | 492/576 [00:03<00:00, 151.46it/s]

→ 2000L Phase 2: corners:  88%|████████▊ | 508/576 [00:03<00:00, 149.02it/s]

→ 2000L Phase 2: corners:  91%|█████████ | 525/576 [00:03<00:00, 152.81it/s]

→ 2000L Phase 2: corners:  94%|█████████▍| 542/576 [00:03<00:00, 155.96it/s]

                                                                            [PASS2] Frame 0000328: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000329: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000330: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000331: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000332: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000333: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000839: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0000840: fixed corners {0, 1, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000993: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000994: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000998: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000999: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001000: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001004: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001005: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001156: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001157: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001158: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001159: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001241: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001242: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001243: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001244: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000330: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000332: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000839: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0000840: fixed corners {0, 1, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000998: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001004: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001158: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000839: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0000840: fixed corners {0, 1, 3} (was_fixed=False, trusted=False)
[PASS2] Summary: 11 frames fixed, 15 untrusted, 576 total


→ 2000L Phase 3: finalize:   0%|          | 0/576 [00:00<?, ?it/s]

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→ 2000L Phase 3: finalize:  57%|█████▋    | 329/576 [00:06<00:04, 52.29it/s]

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→ 2000L Phase 3: finalize:  63%|██████▎   | 365/576 [00:07<00:04, 52.30it/s]

→ 2000L Phase 3: finalize:  64%|██████▍   | 371/576 [00:07<00:03, 52.42it/s]

→ 2000L Phase 3: finalize:  65%|██████▌   | 377/576 [00:07<00:03, 52.57it/s]

→ 2000L Phase 3: finalize:  66%|██████▋   | 383/576 [00:07<00:03, 52.74it/s]

→ 2000L Phase 3: finalize:  68%|██████▊   | 389/576 [00:07<00:03, 52.79it/s]

→ 2000L Phase 3: finalize:  69%|██████▊   | 395/576 [00:07<00:03, 52.95it/s]

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→ 2000L Phase 3: finalize:  74%|███████▍  | 425/576 [00:08<00:02, 53.77it/s]

→ 2000L Phase 3: finalize:  75%|███████▍  | 431/576 [00:08<00:02, 53.84it/s]

→ 2000L Phase 3: finalize:  76%|███████▌  | 437/576 [00:08<00:02, 53.87it/s]

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→ 2000L Phase 3: finalize:  78%|███████▊  | 449/576 [00:08<00:02, 53.86it/s]

→ 2000L Phase 3: finalize:  79%|███████▉  | 455/576 [00:08<00:02, 53.97it/s]

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→ 2000L Phase 3: finalize:  83%|████████▎ | 479/576 [00:09<00:01, 54.19it/s]

→ 2000L Phase 3: finalize:  84%|████████▍ | 485/576 [00:09<00:01, 53.99it/s]

→ 2000L Phase 3: finalize:  85%|████████▌ | 491/576 [00:09<00:01, 53.08it/s]

→ 2000L Phase 3: finalize:  86%|████████▋ | 497/576 [00:09<00:01, 52.88it/s]

→ 2000L Phase 3: finalize:  87%|████████▋ | 503/576 [00:09<00:01, 52.70it/s]

→ 2000L Phase 3: finalize:  88%|████████▊ | 509/576 [00:09<00:01, 52.54it/s]

→ 2000L Phase 3: finalize:  89%|████████▉ | 515/576 [00:09<00:01, 52.26it/s]

→ 2000L Phase 3: finalize:  90%|█████████ | 521/576 [00:10<00:01, 52.18it/s]

→ 2000L Phase 3: finalize:  91%|█████████▏| 527/576 [00:10<00:00, 52.47it/s]

→ 2000L Phase 3: finalize:  93%|█████████▎| 533/576 [00:10<00:00, 52.62it/s]

→ 2000L Phase 3: finalize:  94%|█████████▎| 539/576 [00:10<00:00, 52.69it/s]

→ 2000L Phase 3: finalize:  95%|█████████▍| 545/576 [00:10<00:00, 52.70it/s]

→ 2000L Phase 3: finalize:  96%|█████████▌| 551/576 [00:10<00:00, 52.68it/s]

→ 2000L Phase 3: finalize:  97%|█████████▋| 557/576 [00:10<00:00, 52.66it/s]

→ 2000L Phase 3: finalize:  98%|█████████▊| 563/576 [00:10<00:00, 52.61it/s]

→ 2000L Phase 3: finalize:  99%|█████████▉| 569/576 [00:10<00:00, 52.48it/s]

→ 2000L Phase 3: finalize: 100%|█████████▉| 575/576 [00:11<00:00, 52.41it/s]

                                                                            
[TIMING] 2000L — 577 frames
  Phase 1  radial detect   (parallel)  :   8.64s  (15.0 ms/frame)
  Phase 2a corner detect   (parallel)  :   4.02s  (7.0 ms/frame)
  Phase 2b corner fix      (sequential):   0.80s
  Phase 3  finalize        (sequential):  11.09s  (19.2 ms/frame)
    decode + undistort                 :   5.89s  (10.2 ms/frame)
    corner apply + refinement          :   2.41s  (4.2 ms/frame)
    segment                            :   2.27s  (3.9 ms/frame)
    smooth                             :   0.32s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  24.55s


Processing Rigs:  25%|██▌       | 1/4 [00:28<01:25, 28.64s/it][INFO] Filtered 520 stationary frames, 736 remain


→ 2000R (736 images) Phase 1:   0%|          | 0/736 [00:00<?, ?it/s]

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→ 2000R (736 images) Phase 1:   7%|▋         | 54/736 [00:01<00:10, 65.92it/s]

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→ 2000R (736 images) Phase 1:  13%|█▎        | 97/736 [00:01<00:09, 68.08it/s]

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→ 2000R (736 images) Phase 1:  16%|█▌        | 119/736 [00:02<00:07, 77.21it/s]

→ 2000R (736 images) Phase 1:  17%|█▋        | 128/736 [00:02<00:08, 68.14it/s]

→ 2000R (736 images) Phase 1:  18%|█▊        | 136/736 [00:02<00:09, 61.99it/s]

→ 2000R (736 images) Phase 1:  21%|██        | 151/736 [00:02<00:07, 79.01it/s]

→ 2000R (736 images) Phase 1:  22%|██▏       | 160/736 [00:02<00:08, 69.96it/s]

→ 2000R (736 images) Phase 1:  23%|██▎       | 168/736 [00:03<00:09, 62.17it/s]

→ 2000R (736 images) Phase 1:  25%|██▍       | 183/736 [00:03<00:07, 78.52it/s]

→ 2000R (736 images) Phase 1:  26%|██▌       | 192/736 [00:03<00:07, 69.92it/s]

→ 2000R (736 images) Phase 1:  27%|██▋       | 200/736 [00:03<00:08, 63.39it/s]

→ 2000R (736 images) Phase 1:  29%|██▉       | 215/736 [00:03<00:06, 80.67it/s]

→ 2000R (736 images) Phase 1:  30%|███       | 224/736 [00:03<00:07, 70.31it/s]

→ 2000R (736 images) Phase 1:  32%|███▏      | 232/736 [00:03<00:07, 63.60it/s]

→ 2000R (736 images) Phase 1:  33%|███▎      | 246/736 [00:04<00:06, 78.04it/s]

→ 2000R (736 images) Phase 1:  35%|███▍      | 255/736 [00:04<00:06, 71.01it/s]

→ 2000R (736 images) Phase 1:  36%|███▌      | 263/736 [00:04<00:07, 62.11it/s]

→ 2000R (736 images) Phase 1:  38%|███▊      | 278/736 [00:04<00:05, 77.90it/s]

→ 2000R (736 images) Phase 1:  39%|███▉      | 287/736 [00:04<00:06, 72.29it/s]

→ 2000R (736 images) Phase 1:  40%|████      | 295/736 [00:04<00:07, 61.87it/s]

→ 2000R (736 images) Phase 1:  42%|████▏     | 310/736 [00:04<00:05, 79.08it/s]

→ 2000R (736 images) Phase 1:  43%|████▎     | 319/736 [00:05<00:05, 71.88it/s]

→ 2000R (736 images) Phase 1:  44%|████▍     | 327/736 [00:05<00:07, 51.95it/s]

→ 2000R (736 images) Phase 1:  47%|████▋     | 343/736 [00:05<00:05, 71.83it/s]

→ 2000R (736 images) Phase 1:  48%|████▊     | 353/736 [00:05<00:05, 65.57it/s]

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→ 2000R (736 images) Phase 1:  51%|█████▏    | 379/736 [00:06<00:04, 80.30it/s]

→ 2000R (736 images) Phase 1:  53%|█████▎    | 389/736 [00:06<00:05, 58.19it/s]

→ 2000R (736 images) Phase 1:  55%|█████▌    | 407/736 [00:06<00:04, 77.86it/s]

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→ 2000R (736 images) Phase 1:  59%|█████▉    | 434/736 [00:06<00:04, 74.82it/s]

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→ 2000R (736 images) Phase 1:  62%|██████▏   | 454/736 [00:07<00:04, 60.84it/s]

→ 2000R (736 images) Phase 1:  64%|██████▍   | 472/736 [00:07<00:03, 81.91it/s]

→ 2000R (736 images) Phase 1:  66%|██████▌   | 483/736 [00:07<00:04, 59.67it/s]

→ 2000R (736 images) Phase 1:  68%|██████▊   | 501/736 [00:07<00:02, 78.99it/s]

→ 2000R (736 images) Phase 1:  70%|██████▉   | 512/736 [00:07<00:03, 70.30it/s]

→ 2000R (736 images) Phase 1:  71%|███████   | 522/736 [00:08<00:03, 66.39it/s]

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→ 2000R (736 images) Phase 1:  75%|███████▍  | 550/736 [00:08<00:03, 60.20it/s]

→ 2000R (736 images) Phase 1:  77%|███████▋  | 569/736 [00:08<00:02, 81.02it/s]

→ 2000R (736 images) Phase 1:  79%|███████▉  | 581/736 [00:09<00:02, 60.68it/s]

→ 2000R (736 images) Phase 1:  82%|████████▏ | 600/736 [00:09<00:01, 80.66it/s]

→ 2000R (736 images) Phase 1:  83%|████████▎ | 612/736 [00:09<00:02, 61.52it/s]

→ 2000R (736 images) Phase 1:  86%|████████▌ | 632/736 [00:09<00:01, 81.89it/s]

→ 2000R (736 images) Phase 1:  88%|████████▊ | 645/736 [00:09<00:01, 62.01it/s]

→ 2000R (736 images) Phase 1:  90%|████████▉ | 662/736 [00:10<00:00, 77.96it/s]

→ 2000R (736 images) Phase 1:  92%|█████████▏| 674/736 [00:10<00:00, 62.90it/s]

→ 2000R (736 images) Phase 1:  93%|█████████▎| 687/736 [00:10<00:00, 73.33it/s]

→ 2000R (736 images) Phase 1:  95%|█████████▌| 701/736 [00:10<00:00, 75.63it/s]

→ 2000R (736 images) Phase 1:  97%|█████████▋| 711/736 [00:10<00:00, 64.09it/s]

→ 2000R (736 images) Phase 1: 100%|█████████▉| 733/736 [00:10<00:00, 89.87it/s]

                                                                               

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→ 2000R Phase 2: corners:  15%|█▌        | 112/735 [00:01<00:05, 123.54it/s]

→ 2000R Phase 2: corners:  17%|█▋        | 126/735 [00:01<00:04, 127.52it/s]

→ 2000R Phase 2: corners:  19%|█▉        | 141/735 [00:01<00:04, 132.21it/s]

→ 2000R Phase 2: corners:  21%|██        | 155/735 [00:01<00:05, 108.46it/s]

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→ 2000R Phase 2: corners:  25%|██▌       | 186/735 [00:01<00:04, 127.26it/s]

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→ 2000R Phase 2: corners:  48%|████▊     | 354/735 [00:02<00:02, 150.12it/s]

→ 2000R Phase 2: corners:  50%|█████     | 370/735 [00:03<00:02, 149.13it/s]

→ 2000R Phase 2: corners:  53%|█████▎    | 390/735 [00:03<00:02, 163.09it/s]

→ 2000R Phase 2: corners:  56%|█████▌    | 408/735 [00:03<00:01, 165.22it/s]

→ 2000R Phase 2: corners:  58%|█████▊    | 427/735 [00:03<00:01, 171.23it/s]

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→ 2000R Phase 2: corners:  65%|██████▌   | 478/735 [00:03<00:01, 148.38it/s]

→ 2000R Phase 2: corners:  67%|██████▋   | 493/735 [00:03<00:01, 143.38it/s]

→ 2000R Phase 2: corners:  69%|██████▉   | 510/735 [00:03<00:01, 148.42it/s]

→ 2000R Phase 2: corners:  72%|███████▏  | 526/735 [00:04<00:01, 148.88it/s]

→ 2000R Phase 2: corners:  74%|███████▍  | 544/735 [00:04<00:01, 157.00it/s]

→ 2000R Phase 2: corners:  76%|███████▌  | 560/735 [00:04<00:01, 152.01it/s]

→ 2000R Phase 2: corners:  79%|███████▊  | 577/735 [00:04<00:01, 153.97it/s]

→ 2000R Phase 2: corners:  81%|████████  | 597/735 [00:04<00:00, 165.88it/s]

→ 2000R Phase 2: corners:  84%|████████▎ | 614/735 [00:04<00:00, 163.47it/s]

→ 2000R Phase 2: corners:  86%|████████▌ | 631/735 [00:04<00:00, 160.24it/s]

→ 2000R Phase 2: corners:  89%|████████▊ | 651/735 [00:04<00:00, 165.58it/s]

→ 2000R Phase 2: corners:  91%|█████████▏| 672/735 [00:04<00:00, 175.23it/s]

→ 2000R Phase 2: corners:  94%|█████████▍| 690/735 [00:05<00:00, 157.95it/s]

→ 2000R Phase 2: corners:  96%|█████████▌| 707/735 [00:05<00:00, 143.68it/s]

                                                                            [PASS2] Frame 0000562: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000583: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000689: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000692: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000696: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000708: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000725: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001308: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001309: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001310: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001311: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001323: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001324: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001325: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001326: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000696: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001310: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001325: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000696: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Summary: 11 frames fixed, 7 untrusted, 735 total


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→ 2000R Phase 3: finalize:  56%|█████▌    | 408/735 [00:07<00:06, 51.18it/s]

→ 2000R Phase 3: finalize:  56%|█████▋    | 414/735 [00:07<00:06, 51.36it/s]

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→ 2000R Phase 3: finalize:  64%|██████▎   | 468/735 [00:08<00:05, 50.09it/s]

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→ 2000R Phase 3: finalize:  66%|██████▌   | 486/735 [00:09<00:04, 51.13it/s]

→ 2000R Phase 3: finalize:  67%|██████▋   | 492/735 [00:09<00:04, 51.52it/s]

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→ 2000R Phase 3: finalize:  69%|██████▊   | 504/735 [00:09<00:04, 51.82it/s]

→ 2000R Phase 3: finalize:  69%|██████▉   | 510/735 [00:09<00:04, 51.85it/s]

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→ 2000R Phase 3: finalize:  71%|███████   | 522/735 [00:09<00:04, 51.94it/s]

→ 2000R Phase 3: finalize:  72%|███████▏  | 528/735 [00:09<00:03, 51.84it/s]

→ 2000R Phase 3: finalize:  73%|███████▎  | 534/735 [00:10<00:03, 51.92it/s]

→ 2000R Phase 3: finalize:  73%|███████▎  | 540/735 [00:10<00:03, 51.90it/s]

→ 2000R Phase 3: finalize:  74%|███████▍  | 546/735 [00:10<00:03, 51.80it/s]

→ 2000R Phase 3: finalize:  75%|███████▌  | 552/735 [00:10<00:03, 51.89it/s]

→ 2000R Phase 3: finalize:  76%|███████▌  | 558/735 [00:10<00:03, 51.86it/s]

→ 2000R Phase 3: finalize:  77%|███████▋  | 564/735 [00:10<00:03, 51.64it/s]

→ 2000R Phase 3: finalize:  78%|███████▊  | 570/735 [00:10<00:03, 51.69it/s]

→ 2000R Phase 3: finalize:  78%|███████▊  | 576/735 [00:10<00:03, 51.50it/s]

→ 2000R Phase 3: finalize:  79%|███████▉  | 582/735 [00:11<00:02, 51.50it/s]

→ 2000R Phase 3: finalize:  80%|████████  | 588/735 [00:11<00:02, 51.47it/s]

→ 2000R Phase 3: finalize:  81%|████████  | 594/735 [00:11<00:02, 51.58it/s]

→ 2000R Phase 3: finalize:  82%|████████▏ | 600/735 [00:11<00:02, 51.55it/s]

→ 2000R Phase 3: finalize:  82%|████████▏ | 606/735 [00:11<00:02, 51.58it/s]

→ 2000R Phase 3: finalize:  83%|████████▎ | 612/735 [00:11<00:02, 51.45it/s]

→ 2000R Phase 3: finalize:  84%|████████▍ | 618/735 [00:11<00:02, 51.48it/s]

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→ 2000R Phase 3: finalize:  86%|████████▌ | 630/735 [00:11<00:02, 51.48it/s]

→ 2000R Phase 3: finalize:  87%|████████▋ | 636/735 [00:12<00:01, 51.56it/s]

→ 2000R Phase 3: finalize:  87%|████████▋ | 642/735 [00:12<00:01, 51.55it/s]

→ 2000R Phase 3: finalize:  88%|████████▊ | 648/735 [00:12<00:01, 51.62it/s]

→ 2000R Phase 3: finalize:  89%|████████▉ | 654/735 [00:12<00:01, 51.39it/s]

→ 2000R Phase 3: finalize:  90%|████████▉ | 660/735 [00:12<00:01, 51.36it/s]

→ 2000R Phase 3: finalize:  91%|█████████ | 666/735 [00:12<00:01, 51.32it/s]

→ 2000R Phase 3: finalize:  91%|█████████▏| 672/735 [00:12<00:01, 51.51it/s]

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→ 2000R Phase 3: finalize:  93%|█████████▎| 684/735 [00:12<00:00, 51.39it/s]

→ 2000R Phase 3: finalize:  94%|█████████▍| 690/735 [00:13<00:00, 51.72it/s]

→ 2000R Phase 3: finalize:  95%|█████████▍| 696/735 [00:13<00:00, 51.89it/s]

→ 2000R Phase 3: finalize:  96%|█████████▌| 702/735 [00:13<00:00, 52.01it/s]

→ 2000R Phase 3: finalize:  96%|█████████▋| 708/735 [00:13<00:00, 52.21it/s]

→ 2000R Phase 3: finalize:  97%|█████████▋| 714/735 [00:13<00:00, 52.16it/s]

→ 2000R Phase 3: finalize:  98%|█████████▊| 720/735 [00:13<00:00, 52.04it/s]

→ 2000R Phase 3: finalize:  99%|█████████▉| 726/735 [00:13<00:00, 52.09it/s]

→ 2000R Phase 3: finalize: 100%|█████████▉| 732/735 [00:13<00:00, 51.99it/s]

                                                                            
[TIMING] 2000R — 736 frames
  Phase 1  radial detect   (parallel)  :  11.18s  (15.2 ms/frame)
  Phase 2a corner detect   (parallel)  :   5.33s  (7.3 ms/frame)
  Phase 2b corner fix      (sequential):   0.68s
  Phase 3  finalize        (sequential):  13.97s  (19.0 ms/frame)
    decode + undistort                 :   7.43s  (10.1 ms/frame)
    corner apply + refinement          :   2.96s  (4.0 ms/frame)
    segment                            :   2.92s  (4.0 ms/frame)
    smooth                             :   0.41s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  31.16s


Processing Rigs:  50%|█████     | 2/4 [01:04<01:05, 32.97s/it][INFO] Filtered 491 stationary frames, 818 remain


→ 1500 (818 images) Phase 1:   0%|          | 0/818 [00:00<?, ?it/s]

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→ 1500 (818 images) Phase 1:  98%|█████████▊| 802/818 [00:12<00:00, 79.96it/s]

→ 1500 (818 images) Phase 1:  99%|█████████▉| 811/818 [00:12<00:00, 81.64it/s]

                                                                              

→ 1500 Phase 2: corners:   0%|          | 0/817 [00:00<?, ?it/s]

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→ 1500 Phase 2: corners:  52%|█████▏    | 421/817 [00:03<00:02, 168.61it/s]

→ 1500 Phase 2: corners:  54%|█████▍    | 440/817 [00:03<00:02, 174.47it/s]

→ 1500 Phase 2: corners:  56%|█████▌    | 458/817 [00:03<00:02, 169.90it/s]

→ 1500 Phase 2: corners:  58%|█████▊    | 476/817 [00:04<00:02, 125.13it/s]

→ 1500 Phase 2: corners:  60%|██████    | 491/817 [00:04<00:02, 130.64it/s]

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→ 1500 Phase 2: corners:  64%|██████▍   | 525/817 [00:04<00:02, 142.87it/s]

→ 1500 Phase 2: corners:  66%|██████▋   | 543/817 [00:04<00:01, 152.56it/s]

→ 1500 Phase 2: corners:  68%|██████▊   | 559/817 [00:04<00:01, 154.52it/s]

→ 1500 Phase 2: corners:  71%|███████   | 578/817 [00:04<00:01, 160.01it/s]

→ 1500 Phase 2: corners:  73%|███████▎  | 595/817 [00:04<00:01, 155.54it/s]

→ 1500 Phase 2: corners:  75%|███████▍  | 611/817 [00:04<00:01, 156.42it/s]

→ 1500 Phase 2: corners:  77%|███████▋  | 628/817 [00:05<00:01, 156.32it/s]

→ 1500 Phase 2: corners:  79%|███████▉  | 647/817 [00:05<00:01, 163.93it/s]

→ 1500 Phase 2: corners:  81%|████████▏ | 664/817 [00:05<00:00, 160.39it/s]

→ 1500 Phase 2: corners:  83%|████████▎ | 681/817 [00:05<00:00, 158.05it/s]

→ 1500 Phase 2: corners:  85%|████████▌ | 698/817 [00:05<00:00, 153.79it/s]

→ 1500 Phase 2: corners:  88%|████████▊ | 715/817 [00:05<00:00, 153.80it/s]

→ 1500 Phase 2: corners:  89%|████████▉ | 731/817 [00:05<00:00, 150.47it/s]

→ 1500 Phase 2: corners:  92%|█████████▏| 748/817 [00:05<00:00, 153.75it/s]

→ 1500 Phase 2: corners:  94%|█████████▎| 764/817 [00:05<00:00, 152.66it/s]

→ 1500 Phase 2: corners:  95%|█████████▌| 780/817 [00:06<00:00, 151.21it/s]

                                                                           [PASS2] Frame 0000437: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000438: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000439: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000440: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000441: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000442: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000443: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000444: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000724: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000725: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000726: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000727: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000986: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001170: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0001284: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001286: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001287: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001291: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001293: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001297: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001298: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001299: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001305: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001309: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001312: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001315: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001318: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001319: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001452: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001453: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001454: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001455: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001456: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001457: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001458: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001459: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001466: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001467: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001468: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001469: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001470: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001471: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001472: fixed corners {2, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001474: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000439: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001170: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0001314: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001318: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001454: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001458: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001468: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001472: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001473: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001170: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0001314: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Summary: 24 frames fixed, 28 untrusted, 817 total


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→ 1500 Phase 3: finalize:  98%|█████████▊| 803/817 [00:14<00:00, 53.48it/s]

→ 1500 Phase 3: finalize:  99%|█████████▉| 809/817 [00:14<00:00, 53.53it/s]

→ 1500 Phase 3: finalize: 100%|█████████▉| 815/817 [00:15<00:00, 53.47it/s]

                                                                           
[TIMING] 1500 — 818 frames
  Phase 1  radial detect   (parallel)  :  12.85s  (15.7 ms/frame)
  Phase 2a corner detect   (parallel)  :   6.26s  (7.7 ms/frame)
  Phase 2b corner fix      (sequential):   1.24s
  Phase 3  finalize        (sequential):  15.12s  (18.5 ms/frame)
    decode + undistort                 :   8.06s  (9.9 ms/frame)
    corner apply + refinement          :   3.12s  (3.8 ms/frame)
    segment                            :   3.21s  (3.9 ms/frame)
    smooth                             :   0.45s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  35.47s


Processing Rigs:  75%|███████▌  | 3/4 [01:45<00:36, 36.48s/it][INFO] Filtered 509 stationary frames, 725 remain


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→ 1000 (725 images) Phase 1:  99%|█████████▉| 717/725 [00:11<00:00, 81.46it/s]

                                                                              

→ 1000 Phase 2: corners:   0%|          | 0/724 [00:00<?, ?it/s]

→ 1000 Phase 2: corners:   0%|          | 1/724 [00:00<10:39,  1.13it/s]

→ 1000 Phase 2: corners:   2%|▏         | 15/724 [00:00<00:35, 20.17it/s]

→ 1000 Phase 2: corners:   3%|▎         | 25/724 [00:01<00:21, 32.68it/s]

→ 1000 Phase 2: corners:   6%|▌         | 40/724 [00:01<00:12, 54.23it/s]

→ 1000 Phase 2: corners:   7%|▋         | 52/724 [00:01<00:09, 67.60it/s]

→ 1000 Phase 2: corners:   9%|▉         | 67/724 [00:01<00:07, 84.64it/s]

→ 1000 Phase 2: corners:  12%|█▏        | 87/724 [00:01<00:05, 112.36it/s]

→ 1000 Phase 2: corners:  15%|█▍        | 106/724 [00:01<00:04, 132.00it/s]

→ 1000 Phase 2: corners:  17%|█▋        | 122/724 [00:01<00:04, 137.15it/s]

→ 1000 Phase 2: corners:  19%|█▉        | 140/724 [00:01<00:03, 148.74it/s]

→ 1000 Phase 2: corners:  22%|██▏       | 157/724 [00:01<00:03, 150.78it/s]

→ 1000 Phase 2: corners:  24%|██▍       | 174/724 [00:02<00:03, 148.64it/s]

→ 1000 Phase 2: corners:  26%|██▌       | 190/724 [00:02<00:03, 144.65it/s]

→ 1000 Phase 2: corners:  28%|██▊       | 206/724 [00:02<00:03, 144.91it/s]

→ 1000 Phase 2: corners:  31%|███       | 221/724 [00:02<00:03, 144.14it/s]

→ 1000 Phase 2: corners:  33%|███▎      | 239/724 [00:02<00:03, 150.61it/s]

→ 1000 Phase 2: corners:  35%|███▌      | 255/724 [00:02<00:03, 148.78it/s]

→ 1000 Phase 2: corners:  37%|███▋      | 271/724 [00:02<00:02, 151.69it/s]

→ 1000 Phase 2: corners:  40%|███▉      | 288/724 [00:02<00:02, 155.40it/s]

→ 1000 Phase 2: corners:  42%|████▏     | 306/724 [00:02<00:02, 161.90it/s]

→ 1000 Phase 2: corners:  45%|████▍     | 323/724 [00:03<00:02, 163.66it/s]

→ 1000 Phase 2: corners:  47%|████▋     | 340/724 [00:03<00:02, 153.30it/s]

→ 1000 Phase 2: corners:  49%|████▉     | 356/724 [00:03<00:02, 152.97it/s]

→ 1000 Phase 2: corners:  52%|█████▏    | 375/724 [00:03<00:02, 158.56it/s]

→ 1000 Phase 2: corners:  54%|█████▍    | 391/724 [00:03<00:02, 158.37it/s]

→ 1000 Phase 2: corners:  56%|█████▋    | 409/724 [00:03<00:01, 161.79it/s]

→ 1000 Phase 2: corners:  59%|█████▉    | 429/724 [00:03<00:01, 168.69it/s]

→ 1000 Phase 2: corners:  62%|██████▏   | 446/724 [00:03<00:01, 159.14it/s]

→ 1000 Phase 2: corners:  64%|██████▍   | 463/724 [00:03<00:01, 157.71it/s]

→ 1000 Phase 2: corners:  66%|██████▌   | 479/724 [00:04<00:01, 153.15it/s]

→ 1000 Phase 2: corners:  69%|██████▊   | 497/724 [00:04<00:01, 158.73it/s]

→ 1000 Phase 2: corners:  71%|███████   | 513/724 [00:04<00:01, 147.78it/s]

→ 1000 Phase 2: corners:  73%|███████▎  | 530/724 [00:04<00:01, 153.40it/s]

→ 1000 Phase 2: corners:  75%|███████▌  | 546/724 [00:04<00:01, 153.77it/s]

→ 1000 Phase 2: corners:  78%|███████▊  | 562/724 [00:04<00:01, 145.51it/s]

→ 1000 Phase 2: corners:  80%|████████  | 581/724 [00:04<00:00, 157.63it/s]

→ 1000 Phase 2: corners:  83%|████████▎ | 599/724 [00:04<00:00, 161.65it/s]

→ 1000 Phase 2: corners:  85%|████████▌ | 616/724 [00:04<00:00, 160.01it/s]

→ 1000 Phase 2: corners:  88%|████████▊ | 639/724 [00:05<00:00, 174.70it/s]

→ 1000 Phase 2: corners:  91%|█████████ | 658/724 [00:05<00:00, 178.73it/s]

→ 1000 Phase 2: corners:  93%|█████████▎| 676/724 [00:05<00:00, 174.55it/s]

→ 1000 Phase 2: corners:  96%|█████████▌| 694/724 [00:05<00:00, 166.61it/s]

→ 1000 Phase 2: corners: 100%|█████████▉| 723/724 [00:05<00:00, 199.00it/s]

                                                                           [PASS2] Frame 0000266: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000267: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000268: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000269: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000275: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000276: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000277: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000278: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000284: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000285: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000286: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000287: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000288: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000289: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000290: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000291: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000292: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000655: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000656: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000657: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000658: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000714: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000715: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000716: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000717: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000718: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000719: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000723: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000724: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000725: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000726: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000727: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000728: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000739: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000755: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000756: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000757: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000758: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000842: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000852: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000902: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000906: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000907: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000908: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000909: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000910: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000911: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000912: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001235: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001236: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001237: fixed corners {2, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001239: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001241: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001242: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001243: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001250: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001251: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001252: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001253: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001254: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001255: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001256: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001262: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001263: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001264: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001265: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001266: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001267: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001268: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001269: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001270: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001271: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001272: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000268: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000277: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000286: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000288: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000289: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000291: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000655: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000656: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000657: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000715: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000716: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000717: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000718: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000722: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000723: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000724: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000726: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000727: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000728: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000757: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000906: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000907: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000908: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000909: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000911: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001238: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001241: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001242: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001243: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001252: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001255: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001264: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001265: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001269: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001271: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000655: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000656: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000657: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000715: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000716: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000722: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000723: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000724: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000726: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000727: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000728: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001238: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001241: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001242: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001243: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Summary: 45 frames fixed, 42 untrusted, 724 total


→ 1000 Phase 3: finalize:   0%|          | 0/724 [00:00<?, ?it/s]

→ 1000 Phase 3: finalize:   1%|          | 6/724 [00:00<00:13, 53.82it/s]

→ 1000 Phase 3: finalize:   2%|▏         | 12/724 [00:00<00:12, 56.06it/s]

→ 1000 Phase 3: finalize:   2%|▏         | 18/724 [00:00<00:12, 56.77it/s]

→ 1000 Phase 3: finalize:   3%|▎         | 24/724 [00:00<00:12, 57.13it/s]

→ 1000 Phase 3: finalize:   4%|▍         | 30/724 [00:00<00:12, 57.63it/s]

→ 1000 Phase 3: finalize:   5%|▍         | 36/724 [00:00<00:11, 57.84it/s]

→ 1000 Phase 3: finalize:   6%|▌         | 42/724 [00:00<00:11, 58.06it/s]

→ 1000 Phase 3: finalize:   7%|▋         | 48/724 [00:00<00:11, 58.57it/s]

→ 1000 Phase 3: finalize:   7%|▋         | 54/724 [00:00<00:11, 58.68it/s]

→ 1000 Phase 3: finalize:   8%|▊         | 60/724 [00:01<00:11, 59.01it/s]

→ 1000 Phase 3: finalize:   9%|▉         | 67/724 [00:01<00:11, 59.45it/s]

→ 1000 Phase 3: finalize:  10%|█         | 74/724 [00:01<00:10, 59.63it/s]

→ 1000 Phase 3: finalize:  11%|█         | 81/724 [00:01<00:10, 59.99it/s]

→ 1000 Phase 3: finalize:  12%|█▏        | 88/724 [00:01<00:10, 60.15it/s]

→ 1000 Phase 3: finalize:  13%|█▎        | 95/724 [00:01<00:10, 60.27it/s]

→ 1000 Phase 3: finalize:  14%|█▍        | 102/724 [00:01<00:10, 59.62it/s]

→ 1000 Phase 3: finalize:  15%|█▍        | 108/724 [00:01<00:10, 59.44it/s]

→ 1000 Phase 3: finalize:  16%|█▌        | 114/724 [00:01<00:10, 59.26it/s]

→ 1000 Phase 3: finalize:  17%|█▋        | 120/724 [00:02<00:10, 58.32it/s]

→ 1000 Phase 3: finalize:  17%|█▋        | 126/724 [00:02<00:10, 57.87it/s]

→ 1000 Phase 3: finalize:  18%|█▊        | 132/724 [00:02<00:10, 57.94it/s]

→ 1000 Phase 3: finalize:  19%|█▉        | 138/724 [00:02<00:10, 57.73it/s]

→ 1000 Phase 3: finalize:  20%|█▉        | 144/724 [00:02<00:10, 57.96it/s]

→ 1000 Phase 3: finalize:  21%|██        | 150/724 [00:02<00:09, 58.16it/s]

→ 1000 Phase 3: finalize:  22%|██▏       | 156/724 [00:02<00:09, 58.28it/s]

→ 1000 Phase 3: finalize:  22%|██▏       | 162/724 [00:02<00:09, 58.28it/s]

→ 1000 Phase 3: finalize:  23%|██▎       | 168/724 [00:02<00:09, 57.93it/s]

→ 1000 Phase 3: finalize:  24%|██▍       | 174/724 [00:02<00:09, 58.06it/s]

→ 1000 Phase 3: finalize:  25%|██▍       | 180/724 [00:03<00:09, 57.90it/s]

→ 1000 Phase 3: finalize:  26%|██▌       | 186/724 [00:03<00:09, 58.07it/s]

→ 1000 Phase 3: finalize:  27%|██▋       | 192/724 [00:03<00:09, 58.11it/s]

→ 1000 Phase 3: finalize:  27%|██▋       | 198/724 [00:03<00:09, 58.21it/s]

→ 1000 Phase 3: finalize:  28%|██▊       | 204/724 [00:03<00:08, 58.34it/s]

→ 1000 Phase 3: finalize:  29%|██▉       | 210/724 [00:03<00:08, 58.43it/s]

→ 1000 Phase 3: finalize:  30%|██▉       | 216/724 [00:03<00:08, 58.23it/s]

→ 1000 Phase 3: finalize:  31%|███       | 222/724 [00:03<00:08, 58.26it/s]

→ 1000 Phase 3: finalize:  31%|███▏      | 228/724 [00:03<00:08, 57.99it/s]

→ 1000 Phase 3: finalize:  32%|███▏      | 234/724 [00:04<00:08, 56.89it/s]

→ 1000 Phase 3: finalize:  33%|███▎      | 240/724 [00:04<00:08, 55.90it/s]

→ 1000 Phase 3: finalize:  34%|███▍      | 246/724 [00:04<00:08, 55.56it/s]

→ 1000 Phase 3: finalize:  35%|███▍      | 252/724 [00:04<00:08, 55.35it/s]

→ 1000 Phase 3: finalize:  36%|███▌      | 258/724 [00:04<00:08, 55.20it/s]

→ 1000 Phase 3: finalize:  36%|███▋      | 264/724 [00:04<00:08, 55.10it/s]

→ 1000 Phase 3: finalize:  37%|███▋      | 270/724 [00:04<00:08, 54.91it/s]

→ 1000 Phase 3: finalize:  38%|███▊      | 276/724 [00:04<00:08, 54.64it/s]

→ 1000 Phase 3: finalize:  39%|███▉      | 282/724 [00:04<00:08, 54.29it/s]

→ 1000 Phase 3: finalize:  40%|███▉      | 288/724 [00:05<00:08, 54.10it/s]

→ 1000 Phase 3: finalize:  41%|████      | 294/724 [00:05<00:08, 53.55it/s]

→ 1000 Phase 3: finalize:  41%|████▏     | 300/724 [00:05<00:07, 53.65it/s]

→ 1000 Phase 3: finalize:  42%|████▏     | 306/724 [00:05<00:07, 53.78it/s]

→ 1000 Phase 3: finalize:  43%|████▎     | 312/724 [00:05<00:07, 53.94it/s]

→ 1000 Phase 3: finalize:  44%|████▍     | 318/724 [00:05<00:07, 54.15it/s]

→ 1000 Phase 3: finalize:  45%|████▍     | 324/724 [00:05<00:07, 54.26it/s]

→ 1000 Phase 3: finalize:  46%|████▌     | 330/724 [00:05<00:07, 54.28it/s]

→ 1000 Phase 3: finalize:  46%|████▋     | 336/724 [00:05<00:07, 54.37it/s]

→ 1000 Phase 3: finalize:  47%|████▋     | 342/724 [00:06<00:07, 54.28it/s]

→ 1000 Phase 3: finalize:  48%|████▊     | 348/724 [00:06<00:06, 54.07it/s]

→ 1000 Phase 3: finalize:  49%|████▉     | 354/724 [00:06<00:06, 54.27it/s]

→ 1000 Phase 3: finalize:  50%|████▉     | 360/724 [00:06<00:06, 54.43it/s]

→ 1000 Phase 3: finalize:  51%|█████     | 366/724 [00:06<00:06, 54.51it/s]

→ 1000 Phase 3: finalize:  51%|█████▏    | 372/724 [00:06<00:06, 54.58it/s]

→ 1000 Phase 3: finalize:  52%|█████▏    | 378/724 [00:06<00:06, 54.59it/s]

→ 1000 Phase 3: finalize:  53%|█████▎    | 384/724 [00:06<00:06, 54.64it/s]

→ 1000 Phase 3: finalize:  54%|█████▍    | 390/724 [00:06<00:06, 53.98it/s]

→ 1000 Phase 3: finalize:  55%|█████▍    | 396/724 [00:07<00:06, 53.90it/s]

→ 1000 Phase 3: finalize:  56%|█████▌    | 402/724 [00:07<00:05, 53.91it/s]

→ 1000 Phase 3: finalize:  56%|█████▋    | 408/724 [00:07<00:05, 53.97it/s]

→ 1000 Phase 3: finalize:  57%|█████▋    | 414/724 [00:07<00:05, 53.88it/s]

→ 1000 Phase 3: finalize:  58%|█████▊    | 420/724 [00:07<00:05, 53.88it/s]

→ 1000 Phase 3: finalize:  59%|█████▉    | 426/724 [00:07<00:05, 53.82it/s]

→ 1000 Phase 3: finalize:  60%|█████▉    | 432/724 [00:07<00:05, 53.90it/s]

→ 1000 Phase 3: finalize:  60%|██████    | 438/724 [00:07<00:05, 53.91it/s]

→ 1000 Phase 3: finalize:  61%|██████▏   | 444/724 [00:07<00:05, 53.74it/s]

→ 1000 Phase 3: finalize:  62%|██████▏   | 450/724 [00:08<00:05, 53.82it/s]

→ 1000 Phase 3: finalize:  63%|██████▎   | 456/724 [00:08<00:04, 53.67it/s]

→ 1000 Phase 3: finalize:  64%|██████▍   | 462/724 [00:08<00:04, 53.81it/s]

→ 1000 Phase 3: finalize:  65%|██████▍   | 468/724 [00:08<00:04, 53.80it/s]

→ 1000 Phase 3: finalize:  65%|██████▌   | 474/724 [00:08<00:04, 53.89it/s]

→ 1000 Phase 3: finalize:  66%|██████▋   | 480/724 [00:08<00:04, 54.09it/s]

→ 1000 Phase 3: finalize:  67%|██████▋   | 486/724 [00:08<00:04, 54.29it/s]

→ 1000 Phase 3: finalize:  68%|██████▊   | 492/724 [00:08<00:04, 54.33it/s]

→ 1000 Phase 3: finalize:  69%|██████▉   | 498/724 [00:08<00:04, 54.42it/s]

→ 1000 Phase 3: finalize:  70%|██████▉   | 504/724 [00:09<00:04, 54.36it/s]

→ 1000 Phase 3: finalize:  70%|███████   | 510/724 [00:09<00:03, 54.38it/s]

→ 1000 Phase 3: finalize:  71%|███████▏  | 516/724 [00:09<00:03, 54.47it/s]

→ 1000 Phase 3: finalize:  72%|███████▏  | 522/724 [00:09<00:03, 54.63it/s]

→ 1000 Phase 3: finalize:  73%|███████▎  | 528/724 [00:09<00:03, 54.65it/s]

→ 1000 Phase 3: finalize:  74%|███████▍  | 534/724 [00:09<00:03, 54.79it/s]

→ 1000 Phase 3: finalize:  75%|███████▍  | 540/724 [00:09<00:03, 54.83it/s]

→ 1000 Phase 3: finalize:  75%|███████▌  | 546/724 [00:09<00:03, 54.87it/s]

→ 1000 Phase 3: finalize:  76%|███████▌  | 552/724 [00:09<00:03, 54.83it/s]

→ 1000 Phase 3: finalize:  77%|███████▋  | 558/724 [00:09<00:03, 54.79it/s]

→ 1000 Phase 3: finalize:  78%|███████▊  | 564/724 [00:10<00:02, 54.88it/s]

→ 1000 Phase 3: finalize:  79%|███████▊  | 570/724 [00:10<00:02, 54.91it/s]

→ 1000 Phase 3: finalize:  80%|███████▉  | 576/724 [00:10<00:02, 55.03it/s]

→ 1000 Phase 3: finalize:  80%|████████  | 582/724 [00:10<00:02, 55.07it/s]

→ 1000 Phase 3: finalize:  81%|████████  | 588/724 [00:10<00:02, 55.10it/s]

→ 1000 Phase 3: finalize:  82%|████████▏ | 594/724 [00:10<00:02, 55.23it/s]

→ 1000 Phase 3: finalize:  83%|████████▎ | 600/724 [00:10<00:02, 55.37it/s]

→ 1000 Phase 3: finalize:  84%|████████▎ | 606/724 [00:10<00:02, 55.35it/s]

→ 1000 Phase 3: finalize:  85%|████████▍ | 612/724 [00:10<00:02, 55.43it/s]

→ 1000 Phase 3: finalize:  85%|████████▌ | 618/724 [00:11<00:01, 55.52it/s]

→ 1000 Phase 3: finalize:  86%|████████▌ | 624/724 [00:11<00:01, 55.64it/s]

→ 1000 Phase 3: finalize:  87%|████████▋ | 630/724 [00:11<00:01, 55.63it/s]

→ 1000 Phase 3: finalize:  88%|████████▊ | 636/724 [00:11<00:01, 55.65it/s]

→ 1000 Phase 3: finalize:  89%|████████▊ | 642/724 [00:11<00:01, 55.67it/s]

→ 1000 Phase 3: finalize:  90%|████████▉ | 648/724 [00:11<00:01, 41.20it/s]

→ 1000 Phase 3: finalize:  90%|█████████ | 654/724 [00:11<00:01, 44.65it/s]

→ 1000 Phase 3: finalize:  91%|█████████ | 660/724 [00:11<00:01, 47.39it/s]

→ 1000 Phase 3: finalize:  92%|█████████▏| 666/724 [00:12<00:01, 49.48it/s]

→ 1000 Phase 3: finalize:  93%|█████████▎| 672/724 [00:12<00:01, 50.97it/s]

→ 1000 Phase 3: finalize:  94%|█████████▎| 678/724 [00:12<00:00, 52.00it/s]

→ 1000 Phase 3: finalize:  94%|█████████▍| 684/724 [00:12<00:00, 52.82it/s]

→ 1000 Phase 3: finalize:  95%|█████████▌| 690/724 [00:12<00:00, 52.89it/s]

→ 1000 Phase 3: finalize:  96%|█████████▌| 696/724 [00:12<00:00, 53.13it/s]

→ 1000 Phase 3: finalize:  97%|█████████▋| 702/724 [00:12<00:00, 53.11it/s]

→ 1000 Phase 3: finalize:  98%|█████████▊| 708/724 [00:12<00:00, 53.06it/s]

→ 1000 Phase 3: finalize:  99%|█████████▊| 714/724 [00:12<00:00, 53.20it/s]

→ 1000 Phase 3: finalize:  99%|█████████▉| 720/724 [00:13<00:00, 53.37it/s]

                                                                           
[TIMING] 1000 — 725 frames
  Phase 1  radial detect   (parallel)  :  11.58s  (16.0 ms/frame)
  Phase 2a corner detect   (parallel)  :   5.59s  (7.7 ms/frame)
  Phase 2b corner fix      (sequential):   1.95s
  Phase 3  finalize        (sequential):  13.14s  (18.1 ms/frame)
    decode + undistort                 :   7.15s  (9.9 ms/frame)
    corner apply + refinement          :   2.58s  (3.6 ms/frame)
    segment                            :   2.78s  (3.8 ms/frame)
    smooth                             :   0.41s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  32.25s


Processing Rigs: 100%|██████████| 4/4 [02:22<00:00, 36.69s/it]
Processing Rigs: 100%|██████████| 4/4 [02:22<00:00, 35.58s/it]
[💾] Saved RigFrameDataset to /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 2852 frames from 4 rigs to /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 2000L: 100 frames selected from 576
[📋] 2000R: 100 frames selected from 735
[📋] 1500: 100 frames selected from 817
[📋] 1000: 100 frames selected from 724
[💾] Saved RigFrameDataset to /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/1_digitized/rig_frames.json

-------------------------------------------------------------------
                      Step 2: Casing Detection                     
-------------------------------------------------------------------

-> Calculating the casing center ...
[INFO] Using 80 total sampled bright frames

Computing max image from bright frames:   0%|          | 0/80 [00:00<?, ?it/s]
Computing max image from bright frames:   1%|▏         | 1/80 [00:01<01:45,  1.33s/it]
Computing max image from bright frames:   2%|▎         | 2/80 [00:03<02:14,  1.72s/it]
Computing max image from bright frames:   4%|▍         | 3/80 [00:04<01:36,  1.25s/it]
Computing max image from bright frames:   5%|▌         | 4/80 [00:04<01:00,  1.26it/s]
Computing max image from bright frames:   6%|▋         | 5/80 [00:04<00:41,  1.82it/s]
Computing max image from bright frames:   9%|▉         | 7/80 [00:04<00:22,  3.20it/s]
Computing max image from bright frames:  10%|█         | 8/80 [00:04<00:18,  3.83it/s]
Computing max image from bright frames:  12%|█▎        | 10/80 [00:04<00:13,  5.32it/s]
Computing max image from bright frames:  15%|█▌        | 12/80 [00:04<00:09,  6.92it/s]
Computing max image from bright frames:  18%|█▊        | 14/80 [00:05<00:08,  7.85it/s]
Computing max image from bright frames:  20%|██        | 16/80 [00:05<00:07,  8.93it/s]
Computing max image from bright frames:  22%|██▎       | 18/80 [00:05<00:08,  7.28it/s]
Computing max image from bright frames:  25%|██▌       | 20/80 [00:05<00:07,  8.28it/s]
Computing max image from bright frames:  28%|██▊       | 22/80 [00:05<00:05,  9.77it/s]
Computing max image from bright frames:  30%|███       | 24/80 [00:06<00:05,  9.93it/s]
Computing max image from bright frames:  32%|███▎      | 26/80 [00:06<00:05,  9.11it/s]
Computing max image from bright frames:  35%|███▌      | 28/80 [00:06<00:05,  9.50it/s]
Computing max image from bright frames:  38%|███▊      | 30/80 [00:06<00:04, 11.22it/s]
Computing max image from bright frames:  40%|████      | 32/80 [00:06<00:04, 11.09it/s]
Computing max image from bright frames:  42%|████▎     | 34/80 [00:06<00:03, 11.61it/s]
Computing max image from bright frames:  45%|████▌     | 36/80 [00:08<00:14,  3.00it/s]
Computing max image from bright frames:  48%|████▊     | 38/80 [00:08<00:10,  3.93it/s]
Computing max image from bright frames:  50%|█████     | 40/80 [00:09<00:08,  4.63it/s]
Computing max image from bright frames:  51%|█████▏    | 41/80 [00:09<00:08,  4.77it/s]
Computing max image from bright frames:  54%|█████▍    | 43/80 [00:09<00:05,  6.35it/s]
Computing max image from bright frames:  56%|█████▋    | 45/80 [00:09<00:04,  7.79it/s]
Computing max image from bright frames:  59%|█████▉    | 47/80 [00:09<00:03,  8.99it/s]
Computing max image from bright frames:  61%|██████▏   | 49/80 [00:09<00:03,  9.90it/s]
Computing max image from bright frames:  64%|██████▍   | 51/80 [00:10<00:04,  7.15it/s]
Computing max image from bright frames:  68%|██████▊   | 54/80 [00:10<00:02,  9.86it/s]
Computing max image from bright frames:  70%|███████   | 56/80 [00:10<00:02,  9.84it/s]
Computing max image from bright frames:  74%|███████▍  | 59/80 [00:10<00:01, 12.76it/s]
Computing max image from bright frames:  76%|███████▋  | 61/80 [00:11<00:01, 11.56it/s]
Computing max image from bright frames:  79%|███████▉  | 63/80 [00:11<00:01, 10.59it/s]
Computing max image from bright frames:  81%|████████▏ | 65/80 [00:11<00:01,  9.86it/s]
Computing max image from bright frames:  84%|████████▍ | 67/80 [00:11<00:01,  8.33it/s]
Computing max image from bright frames:  85%|████████▌ | 68/80 [00:12<00:02,  5.67it/s]
Computing max image from bright frames:  86%|████████▋ | 69/80 [00:12<00:01,  6.12it/s]
Computing max image from bright frames:  90%|█████████ | 72/80 [00:12<00:00,  8.80it/s]
Computing max image from bright frames:  92%|█████████▎| 74/80 [00:12<00:00,  9.02it/s]
Computing max image from bright frames:  98%|█████████▊| 78/80 [00:12<00:00, 13.60it/s]
                                                                                       
[✅] Casing detection complete: cx=903.0, cy=919.0

-------------------------------------------------------------------
                        Step 3: Calibration                        
-------------------------------------------------------------------


  0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:28,  3.52it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:28,  3.52it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   2%|▏         | 2/100 [00:00<00:27,  3.52it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.000 | Best: {'fx': 321.212} (0.000):   3%|▎         | 3/100 [00:00<00:27,  3.52it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   4%|▍         | 4/100 [00:00<00:27,  3.52it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   5%|▌         | 5/100 [00:00<00:07, 12.76it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.000 | Best: {'fx': 335.354} (0.000):   5%|▌         | 5/100 [00:00<00:07, 12.76it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.001 | Best: {'fx': 356.566} (0.001):   6%|▌         | 6/100 [00:00<00:07, 12.76it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.001 | Best: {'fx': 356.566} (0.001):   7%|▋         | 7/100 [00:00<00:06, 13.77it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.000 | Best: {'fx': 356.566} (0.001):   7%|▋         | 7/100 [00:00<00:06, 13.77it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.001 | Best: {'fx': 356.566} (0.001):   8%|▊         | 8/100 [00:00<00:06, 13.77it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.002 | Best: {'fx': 370.707} (0.002):   9%|▉         | 9/100 [00:00<00:06, 13.77it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.002 | Best: {'fx': 370.707} (0.002):  10%|█         | 10/100 [00:00<00:05, 16.91it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.003 | Best: {'fx': 377.778} (0.003):  10%|█         | 10/100 [00:00<00:05, 16.91it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.001 | Best: {'fx': 377.778} (0.003):  11%|█         | 11/100 [00:00<00:05, 16.91it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.004 | Best: {'fx': 384.848} (0.004):  12%|█▏        | 12/100 [00:00<00:05, 16.91it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.004 | Best: {'fx': 391.919} (0.004):  13%|█▎        | 13/100 [00:00<00:05, 16.91it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.004 | Best: {'fx': 398.99} (0.004):  14%|█▍        | 14/100 [00:00<00:05, 16.91it/s] 
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.004 | Best: {'fx': 398.99} (0.004):  15%|█▌        | 15/100 [00:00<00:03, 25.17it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.005 | Best: {'fx': 406.061} (0.005):  15%|█▌        | 15/100 [00:00<00:03, 25.17it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.005 | Best: {'fx': 413.131} (0.005):  16%|█▌        | 16/100 [00:00<00:03, 25.17it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.006 | Best: {'fx': 420.202} (0.006):  17%|█▋        | 17/100 [00:00<00:03, 25.17it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.006 | Best: {'fx': 420.202} (0.006):  18%|█▊        | 18/100 [00:00<00:03, 23.37it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.006 | Best: {'fx': 427.273} (0.006):  18%|█▊        | 18/100 [00:01<00:03, 23.37it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.008 | Best: {'fx': 434.343} (0.008):  19%|█▉        | 19/100 [00:01<00:03, 23.37it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.014 | Best: {'fx': 455.556} (0.014):  20%|██        | 20/100 [00:01<00:03, 23.37it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.014 | Best: {'fx': 455.556} (0.014):  21%|██        | 21/100 [00:01<00:03, 20.53it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.009 | Best: {'fx': 455.556} (0.014):  21%|██        | 21/100 [00:01<00:03, 20.53it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.011 | Best: {'fx': 455.556} (0.014):  22%|██▏       | 22/100 [00:01<00:03, 20.53it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.015 | Best: {'fx': 462.626} (0.015):  23%|██▎       | 23/100 [00:01<00:03, 20.53it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 476.768} (0.020):  24%|██▍       | 24/100 [00:01<00:03, 20.53it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 476.768} (0.020):  25%|██▌       | 25/100 [00:01<00:03, 23.72it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.017 | Best: {'fx': 476.768} (0.020):  25%|██▌       | 25/100 [00:01<00:03, 23.72it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.026 | Best: {'fx': 483.838} (0.026):  26%|██▌       | 26/100 [00:01<00:03, 23.72it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.032 | Best: {'fx': 490.909} (0.032):  27%|██▋       | 27/100 [00:01<00:03, 23.72it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.047 | Best: {'fx': 505.051} (0.047):  28%|██▊       | 28/100 [00:01<00:03, 23.72it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.047 | Best: {'fx': 505.051} (0.047):  29%|██▉       | 29/100 [00:01<00:02, 25.21it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.039 | Best: {'fx': 505.051} (0.047):  29%|██▉       | 29/100 [00:01<00:02, 25.21it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.056 | Best: {'fx': 512.121} (0.056):  30%|███       | 30/100 [00:01<00:02, 25.21it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.068 | Best: {'fx': 519.192} (0.068):  31%|███       | 31/100 [00:01<00:02, 25.21it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.068 | Best: {'fx': 519.192} (0.068):  32%|███▏      | 32/100 [00:01<00:04, 16.41it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.079 | Best: {'fx': 526.263} (0.079):  32%|███▏      | 32/100 [00:01<00:04, 16.41it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.076 | Best: {'fx': 526.263} (0.079):  33%|███▎      | 33/100 [00:01<00:04, 16.41it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.073 | Best: {'fx': 526.263} (0.079):  34%|███▍      | 34/100 [00:01<00:04, 16.41it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.049 | Best: {'fx': 526.263} (0.079):  35%|███▌      | 35/100 [00:01<00:03, 16.41it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.049 | Best: {'fx': 526.263} (0.079):  36%|███▌      | 36/100 [00:01<00:03, 18.26it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.054 | Best: {'fx': 526.263} (0.079):  36%|███▌      | 36/100 [00:01<00:03, 18.26it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.064 | Best: {'fx': 526.263} (0.079):  37%|███▋      | 37/100 [00:02<00:03, 18.26it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.045 | Best: {'fx': 526.263} (0.079):  38%|███▊      | 38/100 [00:02<00:03, 18.26it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.045 | Best: {'fx': 526.263} (0.079):  39%|███▉      | 39/100 [00:02<00:03, 18.92it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.034 | Best: {'fx': 526.263} (0.079):  39%|███▉      | 39/100 [00:02<00:03, 18.92it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.039 | Best: {'fx': 526.263} (0.079):  40%|████      | 40/100 [00:02<00:03, 18.92it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.033 | Best: {'fx': 526.263} (0.079):  41%|████      | 41/100 [00:02<00:03, 18.92it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.036 | Best: {'fx': 526.263} (0.079):  42%|████▏     | 42/100 [00:02<00:03, 18.92it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.041 | Best: {'fx': 526.263} (0.079):  43%|████▎     | 43/100 [00:02<00:03, 18.92it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.031 | Best: {'fx': 526.263} (0.079):  44%|████▍     | 44/100 [00:02<00:02, 18.92it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.029 | Best: {'fx': 526.263} (0.079):  45%|████▌     | 45/100 [00:02<00:02, 18.92it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.029 | Best: {'fx': 526.263} (0.079):  46%|████▌     | 46/100 [00:02<00:02, 25.49it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.028 | Best: {'fx': 526.263} (0.079):  46%|████▌     | 46/100 [00:02<00:02, 25.49it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.030 | Best: {'fx': 526.263} (0.079):  47%|████▋     | 47/100 [00:02<00:02, 25.49it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.027 | Best: {'fx': 526.263} (0.079):  48%|████▊     | 48/100 [00:02<00:02, 25.49it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.027 | Best: {'fx': 526.263} (0.079):  49%|████▉     | 49/100 [00:02<00:02, 23.34it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.025 | Best: {'fx': 526.263} (0.079):  49%|████▉     | 49/100 [00:02<00:02, 23.34it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.025 | Best: {'fx': 526.263} (0.079):  50%|█████     | 50/100 [00:02<00:02, 23.34it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.024 | Best: {'fx': 526.263} (0.079):  51%|█████     | 51/100 [00:02<00:02, 23.34it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.022 | Best: {'fx': 526.263} (0.079):  52%|█████▏    | 52/100 [00:02<00:02, 23.34it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.022 | Best: {'fx': 526.263} (0.079):  53%|█████▎    | 53/100 [00:02<00:02, 23.46it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.021 | Best: {'fx': 526.263} (0.079):  53%|█████▎    | 53/100 [00:02<00:02, 23.46it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.023 | Best: {'fx': 526.263} (0.079):  54%|█████▍    | 54/100 [00:02<00:01, 23.46it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.027 | Best: {'fx': 526.263} (0.079):  55%|█████▌    | 55/100 [00:02<00:01, 23.46it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.021 | Best: {'fx': 526.263} (0.079):  56%|█████▌    | 56/100 [00:02<00:01, 23.46it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.026 | Best: {'fx': 526.263} (0.079):  57%|█████▋    | 57/100 [00:02<00:01, 23.46it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.024 | Best: {'fx': 526.263} (0.079):  58%|█████▊    | 58/100 [00:02<00:01, 23.46it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 526.263} (0.079):  59%|█████▉    | 59/100 [00:02<00:01, 23.46it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.021 | Best: {'fx': 526.263} (0.079):  60%|██████    | 60/100 [00:02<00:01, 23.46it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.021 | Best: {'fx': 526.263} (0.079):  61%|██████    | 61/100 [00:02<00:01, 33.72it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.021 | Best: {'fx': 526.263} (0.079):  61%|██████    | 61/100 [00:02<00:01, 33.72it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.021 | Best: {'fx': 526.263} (0.079):  62%|██████▏   | 62/100 [00:02<00:01, 33.72it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 526.263} (0.079):  63%|██████▎   | 63/100 [00:02<00:01, 33.72it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.023 | Best: {'fx': 526.263} (0.079):  64%|██████▍   | 64/100 [00:02<00:01, 33.72it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.024 | Best: {'fx': 526.263} (0.079):  65%|██████▌   | 65/100 [00:02<00:01, 33.72it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.022 | Best: {'fx': 526.263} (0.079):  66%|██████▌   | 66/100 [00:02<00:01, 33.72it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.022 | Best: {'fx': 526.263} (0.079):  67%|██████▋   | 67/100 [00:02<00:00, 37.14it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.022 | Best: {'fx': 526.263} (0.079):  67%|██████▋   | 67/100 [00:02<00:00, 37.14it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 526.263} (0.079):  68%|██████▊   | 68/100 [00:02<00:00, 37.14it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 526.263} (0.079):  69%|██████▉   | 69/100 [00:02<00:00, 37.14it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.022 | Best: {'fx': 526.263} (0.079):  70%|███████   | 70/100 [00:02<00:00, 37.14it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 526.263} (0.079):  71%|███████   | 71/100 [00:02<00:00, 37.14it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 526.263} (0.079):  72%|███████▏  | 72/100 [00:02<00:00, 37.14it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.022 | Best: {'fx': 526.263} (0.079):  73%|███████▎  | 73/100 [00:02<00:00, 37.14it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  74%|███████▍  | 74/100 [00:02<00:00, 37.14it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  75%|███████▌  | 75/100 [00:02<00:00, 43.01it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 526.263} (0.079):  75%|███████▌  | 75/100 [00:02<00:00, 43.01it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  76%|███████▌  | 76/100 [00:02<00:00, 43.01it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  77%|███████▋  | 77/100 [00:03<00:00, 43.01it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  78%|███████▊  | 78/100 [00:03<00:00, 43.01it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  79%|███████▉  | 79/100 [00:03<00:00, 43.01it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  80%|████████  | 80/100 [00:03<00:00, 42.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  80%|████████  | 80/100 [00:03<00:00, 42.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  81%|████████  | 81/100 [00:03<00:00, 42.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  82%|████████▏ | 82/100 [00:03<00:00, 42.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 526.263} (0.079):  83%|████████▎ | 83/100 [00:03<00:00, 42.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  84%|████████▍ | 84/100 [00:03<00:00, 42.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  85%|████████▌ | 85/100 [00:03<00:00, 33.09it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  85%|████████▌ | 85/100 [00:03<00:00, 33.09it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  86%|████████▌ | 86/100 [00:03<00:00, 33.09it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 526.263} (0.079):  87%|████████▋ | 87/100 [00:03<00:00, 33.09it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  88%|████████▊ | 88/100 [00:03<00:00, 33.09it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  89%|████████▉ | 89/100 [00:03<00:00, 32.77it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 526.263} (0.079):  89%|████████▉ | 89/100 [00:03<00:00, 32.77it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 526.263} (0.079):  90%|█████████ | 90/100 [00:03<00:00, 32.77it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 526.263} (0.079):  91%|█████████ | 91/100 [00:03<00:00, 32.77it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 526.263} (0.079):  92%|█████████▏| 92/100 [00:03<00:00, 32.77it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 526.263} (0.079):  93%|█████████▎| 93/100 [00:03<00:00, 32.51it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 526.263} (0.079):  93%|█████████▎| 93/100 [00:03<00:00, 32.51it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 526.263} (0.079):  94%|█████████▍| 94/100 [00:03<00:00, 32.51it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 526.263} (0.079):  95%|█████████▌| 95/100 [00:03<00:00, 32.51it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 526.263} (0.079):  96%|█████████▌| 96/100 [00:03<00:00, 32.51it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 526.263} (0.079):  97%|█████████▋| 97/100 [00:03<00:00, 32.51it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 526.263} (0.079):  98%|█████████▊| 98/100 [00:03<00:00, 33.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 526.263} (0.079):  98%|█████████▊| 98/100 [00:03<00:00, 33.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 526.263} (0.079):  99%|█████████▉| 99/100 [00:03<00:00, 33.61it/s]
                                                                                                                                       

  0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.042 | Best: {'fx': 501.263} (0.042):   0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.042 | Best: {'fx': 501.263} (0.042):   2%|▏         | 1/50 [00:00<00:27,  1.79it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.043 | Best: {'fx': 502.283} (0.043):   2%|▏         | 1/50 [00:00<00:27,  1.79it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.044 | Best: {'fx': 503.303} (0.044):   4%|▍         | 2/50 [00:00<00:26,  1.79it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.044 | Best: {'fx': 503.303} (0.044):   6%|▌         | 3/50 [00:00<00:09,  5.13it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.045 | Best: {'fx': 504.324} (0.045):   6%|▌         | 3/50 [00:00<00:09,  5.13it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.047 | Best: {'fx': 505.344} (0.047):   8%|▊         | 4/50 [00:00<00:08,  5.13it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.050 | Best: {'fx': 507.385} (0.050):  10%|█         | 5/50 [00:00<00:08,  5.13it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.050 | Best: {'fx': 507.385} (0.050):  12%|█▏        | 6/50 [00:00<00:04,  9.71it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.048 | Best: {'fx': 507.385} (0.050):  12%|█▏        | 6/50 [00:00<00:04,  9.71it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.052 | Best: {'fx': 508.405} (0.052):  14%|█▍        | 7/50 [00:00<00:04,  9.71it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.053 | Best: {'fx': 509.426} (0.053):  16%|█▌        | 8/50 [00:00<00:04,  9.71it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.053 | Best: {'fx': 509.426} (0.053):  18%|█▊        | 9/50 [00:00<00:03, 13.21it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.054 | Best: {'fx': 510.446} (0.054):  18%|█▊        | 9/50 [00:01<00:03, 13.21it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.056 | Best: {'fx': 512.487} (0.056):  20%|██        | 10/50 [00:01<00:03, 13.21it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.056 | Best: {'fx': 512.487} (0.056):  22%|██▏       | 11/50 [00:01<00:02, 13.21it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.058 | Best: {'fx': 513.508} (0.058):  24%|██▍       | 12/50 [00:01<00:02, 13.21it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.058 | Best: {'fx': 513.508} (0.058):  26%|██▌       | 13/50 [00:01<00:02, 18.30it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.060 | Best: {'fx': 514.528} (0.060):  26%|██▌       | 13/50 [00:01<00:02, 18.30it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.060 | Best: {'fx': 515.548} (0.060):  28%|██▊       | 14/50 [00:01<00:01, 18.30it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.064 | Best: {'fx': 517.589} (0.064):  30%|███       | 15/50 [00:01<00:01, 18.30it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.064 | Best: {'fx': 517.589} (0.064):  32%|███▏      | 16/50 [00:01<00:02, 16.63it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.062 | Best: {'fx': 517.589} (0.064):  32%|███▏      | 16/50 [00:01<00:02, 16.63it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.066 | Best: {'fx': 518.61} (0.066):  34%|███▍      | 17/50 [00:01<00:01, 16.63it/s] 
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.071 | Best: {'fx': 520.65} (0.071):  36%|███▌      | 18/50 [00:01<00:01, 16.63it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.071 | Best: {'fx': 520.65} (0.071):  38%|███▊      | 19/50 [00:01<00:01, 18.90it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.069 | Best: {'fx': 520.65} (0.071):  38%|███▊      | 19/50 [00:01<00:01, 18.90it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.073 | Best: {'fx': 521.671} (0.073):  40%|████      | 20/50 [00:01<00:01, 18.90it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.073 | Best: {'fx': 522.691} (0.073):  42%|████▏     | 21/50 [00:01<00:01, 18.90it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.073 | Best: {'fx': 522.691} (0.073):  44%|████▍     | 22/50 [00:01<00:01, 20.82it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.075 | Best: {'fx': 523.712} (0.075):  44%|████▍     | 22/50 [00:01<00:01, 20.82it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.079 | Best: {'fx': 525.752} (0.079):  46%|████▌     | 23/50 [00:01<00:01, 20.82it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.078 | Best: {'fx': 525.752} (0.079):  48%|████▊     | 24/50 [00:01<00:01, 20.82it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.078 | Best: {'fx': 525.752} (0.079):  50%|█████     | 25/50 [00:01<00:01, 22.46it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.076 | Best: {'fx': 525.752} (0.079):  50%|█████     | 25/50 [00:01<00:01, 22.46it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.076 | Best: {'fx': 525.752} (0.079):  52%|█████▏    | 26/50 [00:01<00:01, 22.46it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.076 | Best: {'fx': 525.752} (0.079):  54%|█████▍    | 27/50 [00:01<00:01, 22.46it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.078 | Best: {'fx': 525.752} (0.079):  56%|█████▌    | 28/50 [00:01<00:00, 22.46it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.078 | Best: {'fx': 525.752} (0.079):  58%|█████▊    | 29/50 [00:01<00:00, 26.62it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.076 | Best: {'fx': 525.752} (0.079):  58%|█████▊    | 29/50 [00:01<00:00, 26.62it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.076 | Best: {'fx': 525.752} (0.079):  60%|██████    | 30/50 [00:01<00:00, 26.62it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.077 | Best: {'fx': 525.752} (0.079):  62%|██████▏   | 31/50 [00:01<00:00, 26.62it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.075 | Best: {'fx': 525.752} (0.079):  64%|██████▍   | 32/50 [00:01<00:00, 26.62it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.075 | Best: {'fx': 525.752} (0.079):  66%|██████▌   | 33/50 [00:01<00:00, 29.84it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.073 | Best: {'fx': 525.752} (0.079):  66%|██████▌   | 33/50 [00:01<00:00, 29.84it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.075 | Best: {'fx': 525.752} (0.079):  68%|██████▊   | 34/50 [00:01<00:00, 29.84it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.080 | Best: {'fx': 526.773} (0.080):  70%|███████   | 35/50 [00:01<00:00, 29.84it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.080 | Best: {'fx': 526.773} (0.080):  72%|███████▏  | 36/50 [00:01<00:00, 29.84it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.073 | Best: {'fx': 526.773} (0.080):  74%|███████▍  | 37/50 [00:01<00:00, 29.84it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.073 | Best: {'fx': 526.773} (0.080):  76%|███████▌  | 38/50 [00:01<00:00, 33.95it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.076 | Best: {'fx': 526.773} (0.080):  76%|███████▌  | 38/50 [00:01<00:00, 33.95it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.075 | Best: {'fx': 526.773} (0.080):  78%|███████▊  | 39/50 [00:02<00:00, 33.95it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.069 | Best: {'fx': 526.773} (0.080):  80%|████████  | 40/50 [00:02<00:00, 33.95it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.065 | Best: {'fx': 526.773} (0.080):  82%|████████▏ | 41/50 [00:02<00:00, 33.95it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.072 | Best: {'fx': 526.773} (0.080):  84%|████████▍ | 42/50 [00:02<00:00, 33.95it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.072 | Best: {'fx': 526.773} (0.080):  86%|████████▌ | 43/50 [00:02<00:00, 36.67it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.063 | Best: {'fx': 526.773} (0.080):  86%|████████▌ | 43/50 [00:02<00:00, 36.67it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.070 | Best: {'fx': 526.773} (0.080):  88%|████████▊ | 44/50 [00:02<00:00, 36.67it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.067 | Best: {'fx': 526.773} (0.080):  90%|█████████ | 45/50 [00:02<00:00, 36.67it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.064 | Best: {'fx': 526.773} (0.080):  92%|█████████▏| 46/50 [00:02<00:00, 36.67it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.060 | Best: {'fx': 526.773} (0.080):  94%|█████████▍| 47/50 [00:02<00:00, 36.67it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.062 | Best: {'fx': 526.773} (0.080):  96%|█████████▌| 48/50 [00:02<00:00, 36.67it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.062 | Best: {'fx': 526.773} (0.080):  98%|█████████▊| 49/50 [00:02<00:00, 42.56it/s]
Brute | Start: {'fx': 526.263} (0.079) | Current: 0.059 | Best: {'fx': 526.773} (0.080):  98%|█████████▊| 49/50 [00:02<00:00, 42.56it/s]
                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 526.772830344259
    px: 903.0
    py: 919.0
    k1: 0.0
    k2: 0.0
    k3: 0.0
    k4: 0.0
    p1: 0.0
    p2: 0.0
    p3: 0.0
    p4: 0.0
    scale: 3.0
    rotation: 0.0


[🔲] Square Reference Optimization
    Including tangential distortion parameters (p1, p2, p3, p4) in joint optimization
  Selecting up to 20 frames per rig (excluded 0 incomplete frames): 80 frames will be used for optimization
  Rigs: 2000L(2000mm):20/20, 2000R(2000mm):20/20, 1500(1500mm):20/20, 1000(1000mm):20/20
  Total: 80/80 frames used for optimization

Initial score: 56.8679: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 56.8679, picklable_objective(x0) = 56.9013

Best score: 56.9013: : 0iter [00:02, ?iter/s] 
Best score: 56.9013: : 1iter [00:02,  2.00s/iter]
Best score: 56.9013: : 1iter [00:02,  2.00s/iter]
Best score: 56.9013: : 2iter [00:02,  2.00s/iter]
Best score: 56.9013: : 3iter [00:02,  1.71iter/s]
Best score: 56.9013: : 3iter [00:02,  1.71iter/s]
Best score: 56.9013: : 4iter [00:02,  1.71iter/s]
Best score: 56.9013: : 5iter [00:02,  3.05iter/s]
Best score: 56.9013: : 5iter [00:02,  3.05iter/s]
Best score: 56.9013: : 6iter [00:02,  3.05iter/s]
Best score: 56.9013: : 7iter [00:02,  4.43iter/s]
Best score: 56.9013: : 7iter [00:02,  4.43iter/s]
Best score: 56.9013: : 8iter [00:02,  4.43iter/s]
Best score: 56.9013: : 9iter [00:02,  5.77iter/s]
Best score: 56.9013: : 9iter [00:02,  5.77iter/s]
Best score: 56.9013: : 10iter [00:02,  5.77iter/s]
Best score: 56.9013: : 11iter [00:02,  6.93iter/s]
Best score: 56.9013: : 11iter [00:02,  6.93iter/s]
Best score: 56.9013: : 12iter [00:03,  6.93iter/s]
Best score: 56.9013: : 13iter [00:03,  8.00iter/s]
Best score: 56.9013: : 13iter [00:03,  8.00iter/s]
Best score: 56.9013: : 14iter [00:03,  8.00iter/s]
Best score: 56.9013: : 15iter [00:03,  8.90iter/s]
Best score: 56.9013: : 15iter [00:03,  8.90iter/s]
Best score: 56.9013: : 16iter [00:03,  8.90iter/s]
Best score: 56.9013: : 17iter [00:03,  9.60iter/s]
Best score: 56.9013: : 17iter [00:03,  9.60iter/s]
Best score: 56.9013: : 18iter [00:03,  9.60iter/s]
Best score: 56.9013: : 19iter [00:03, 10.17iter/s]
Best score: 56.9013: : 19iter [00:03, 10.17iter/s]
Best score: 56.9013: : 20iter [00:03, 10.17iter/s]
Best score: 56.9013: : 21iter [00:03, 10.44iter/s]
Best score: 56.9013: : 21iter [00:03, 10.44iter/s]
Best score: 56.9013: : 22iter [00:03, 10.44iter/s]
Best score: 56.9013: : 23iter [00:03, 10.76iter/s]
Best score: 56.9013: : 23iter [00:04, 10.76iter/s]
Best score: 56.9013: : 24iter [00:04, 10.76iter/s]
Best score: 56.9013: : 25iter [00:04, 11.02iter/s]
Best score: 56.9013: : 25iter [00:04, 11.02iter/s]
Best score: 56.9013: : 26iter [00:04, 11.02iter/s]
Best score: 56.9013: : 27iter [00:04, 11.20iter/s]
Best score: 56.9013: : 27iter [00:04, 11.20iter/s]
Best score: 56.9013: : 28iter [00:04, 11.20iter/s]
Best score: 56.9013: : 29iter [00:04, 11.35iter/s]
Best score: 56.9013: : 29iter [00:04, 11.35iter/s]
Best score: 56.9013: : 30iter [00:04, 11.35iter/s]
Best score: 56.9013: : 31iter [00:04, 11.33iter/s]
Best score: 56.9013: : 31iter [00:04, 11.33iter/s]
Best score: 56.9013: : 32iter [00:04, 11.33iter/s]
Best score: 56.9013: : 33iter [00:04, 11.46iter/s]
Best score: 56.9013: : 33iter [00:04, 11.46iter/s]
Best score: 56.9013: : 34iter [00:04, 11.46iter/s]
Best score: 56.9013: : 35iter [00:04, 11.53iter/s]
Best score: 56.9013: : 35iter [00:05, 11.53iter/s]
Best score: 56.9013: : 36iter [00:05, 11.53iter/s]
Best score: 56.9013: : 37iter [00:05, 11.52iter/s]
Best score: 56.9013: : 37iter [00:05, 11.52iter/s]
Best score: 56.9013: : 38iter [00:05, 11.52iter/s]
Best score: 56.9013: : 39iter [00:05, 11.59iter/s]
Best score: 56.9013: : 39iter [00:05, 11.59iter/s]
Best score: 56.9013: : 40iter [00:05, 11.59iter/s]
Best score: 56.9013: : 41iter [00:05, 11.45iter/s]
Best score: 56.9013: : 41iter [00:05, 11.45iter/s]
Best score: 56.9013: : 42iter [00:05, 11.45iter/s]
Best score: 56.9013: : 43iter [00:05, 11.62iter/s]
Best score: 56.9013: : 43iter [00:05, 11.62iter/s]
Best score: 56.9013: : 44iter [00:05, 11.62iter/s]
Best score: 56.9013: : 45iter [00:05, 11.65iter/s]
Best score: 56.9013: : 45iter [00:05, 11.65iter/s]
Best score: 56.9013: : 46iter [00:05, 11.65iter/s]
Best score: 56.9013: : 47iter [00:05, 11.68iter/s]
Best score: 56.9013: : 47iter [00:06, 11.68iter/s]
Best score: 56.9013: : 48iter [00:06, 11.68iter/s]
Best score: 56.9013: : 49iter [00:06, 11.75iter/s]
[ITER 50] Best: 42.5934
[PARAMS] Current best parameters:
  fx: 514.9862
  fy: 511.6387
  px: 927.5615
  py: 933.4258
  k1: -0.07596760
  k2: 0.08080157
  k3: -0.02909310
  k4: 0.00598879
  p1: -0.00208415
  p2: 0.00319306
  p3: -0.00018320
  p4: 0.02625645
  s1: -0.0152
  s2: -0.0191
  s3: -0.0061
  s4: 0.0103
  tilt_x: 0.0011
  tilt_y: -0.0728
  scale: 3.2220
  rotation: 0.4357

Best score: 42.5934: : 49iter [00:06, 11.75iter/s]
Best score: 42.5934: : 50iter [00:06, 11.75iter/s]
Best score: 42.5934: : 51iter [00:06, 11.64iter/s]
Best score: 42.5934: : 51iter [00:06, 11.64iter/s]
Best score: 42.5934: : 52iter [00:06, 11.64iter/s]
Best score: 42.5934: : 53iter [00:06, 11.75iter/s]
Best score: 42.5934: : 53iter [00:06, 11.75iter/s]
Best score: 42.5934: : 54iter [00:06, 11.75iter/s]
Best score: 42.5934: : 55iter [00:06, 11.75iter/s]
Best score: 42.5934: : 55iter [00:06, 11.75iter/s]
Best score: 42.5934: : 56iter [00:06, 11.75iter/s]
Best score: 42.5934: : 57iter [00:06, 11.81iter/s]
Best score: 42.5934: : 57iter [00:06, 11.81iter/s]
Best score: 42.5934: : 58iter [00:06, 11.81iter/s]
Best score: 42.5934: : 59iter [00:06, 11.82iter/s]
Best score: 42.0711: : 59iter [00:07, 11.82iter/s]
Best score: 42.0711: : 60iter [00:07, 11.82iter/s]
Best score: 42.0711: : 61iter [00:07, 11.66iter/s]
Best score: 42.0711: : 61iter [00:07, 11.66iter/s]
Best score: 42.0711: : 62iter [00:07, 11.66iter/s]
Best score: 42.0711: : 63iter [00:07, 11.69iter/s]
Best score: 42.0711: : 63iter [00:07, 11.69iter/s]
Best score: 42.0711: : 64iter [00:07, 11.69iter/s]
Best score: 42.0711: : 65iter [00:07, 11.73iter/s]
Best score: 42.0711: : 65iter [00:07, 11.73iter/s]
Best score: 42.0711: : 66iter [00:07, 11.73iter/s]
Best score: 42.0711: : 67iter [00:07, 11.72iter/s]
Best score: 42.0711: : 67iter [00:07, 11.72iter/s]
Best score: 42.0711: : 68iter [00:07, 11.72iter/s]
Best score: 42.0711: : 69iter [00:07, 11.77iter/s]
Best score: 36.6475: : 69iter [00:07, 11.77iter/s]
Best score: 36.6475: : 70iter [00:08, 11.77iter/s]
Best score: 36.6475: : 71iter [00:08, 11.57iter/s]
Best score: 36.6475: : 71iter [00:08, 11.57iter/s]
Best score: 36.6475: : 72iter [00:08, 11.57iter/s]
Best score: 36.6475: : 73iter [00:08, 11.66iter/s]
Best score: 36.6475: : 73iter [00:08, 11.66iter/s]
Best score: 36.6475: : 74iter [00:08, 11.66iter/s]
Best score: 36.6475: : 75iter [00:08, 11.73iter/s]
Best score: 36.6475: : 75iter [00:08, 11.73iter/s]
Best score: 36.6475: : 76iter [00:08, 11.73iter/s]
Best score: 36.6475: : 77iter [00:08, 11.80iter/s]
Best score: 36.6475: : 77iter [00:08, 11.80iter/s]
Best score: 36.6475: : 78iter [00:08, 11.80iter/s]
Best score: 36.6475: : 79iter [00:08, 11.81iter/s]
Best score: 15.4079: : 79iter [00:08, 11.81iter/s]
Best score: 15.4079: : 80iter [00:08, 11.81iter/s]
Best score: 15.4079: : 81iter [00:08, 11.61iter/s]
Best score: 15.4079: : 81iter [00:08, 11.61iter/s]
Best score: 15.4079: : 82iter [00:09, 11.61iter/s]
Best score: 15.4079: : 83iter [00:09, 11.64iter/s]
Best score: 15.4079: : 83iter [00:09, 11.64iter/s]
Best score: 15.4079: : 84iter [00:09, 11.64iter/s]
Best score: 15.4079: : 85iter [00:09, 11.66iter/s]
Best score: 15.4079: : 85iter [00:09, 11.66iter/s]
Best score: 15.4079: : 86iter [00:09, 11.66iter/s]
Best score: 15.4079: : 87iter [00:09, 11.70iter/s]
Best score: 15.4079: : 87iter [00:09, 11.70iter/s]
Best score: 15.4079: : 88iter [00:09, 11.70iter/s]
Best score: 15.4079: : 89iter [00:09, 11.71iter/s]
Best score: 15.4079: : 89iter [00:09, 11.71iter/s]
Best score: 15.4079: : 90iter [00:09, 11.71iter/s]
Best score: 15.4079: : 91iter [00:09, 11.52iter/s]
Best score: 15.4079: : 91iter [00:09, 11.52iter/s]
Best score: 15.4079: : 92iter [00:09, 11.52iter/s]
Best score: 15.4079: : 93iter [00:09, 11.60iter/s]
Best score: 15.4079: : 93iter [00:10, 11.60iter/s]
Best score: 15.4079: : 94iter [00:10, 11.60iter/s]
Best score: 15.4079: : 95iter [00:10, 11.60iter/s]
Best score: 15.4079: : 95iter [00:10, 11.60iter/s]
Best score: 15.4079: : 96iter [00:10, 11.60iter/s]
Best score: 15.4079: : 97iter [00:10, 11.64iter/s]
Best score: 15.4079: : 97iter [00:10, 11.64iter/s]
Best score: 15.4079: : 98iter [00:10, 11.64iter/s]
Best score: 15.4079: : 99iter [00:10, 11.56iter/s]
[ITER 100] Best: 15.2737
[PARAMS] Current best parameters:
  fx: 526.2996
  fy: 519.4419
  px: 897.6032
  py: 926.4103
  k1: 0.03445007
  k2: -0.05512106
  k3: 0.04321255
  k4: -0.01150405
  p1: -0.01488007
  p2: -0.01996576
  p3: 0.00041291
  p4: 0.02826470
  s1: 0.0056
  s2: -0.0205
  s3: 0.0155
  s4: -0.0234
  tilt_x: -0.0113
  tilt_y: 0.0188
  scale: 2.9320
  rotation: -1.4347

Best score: 15.2737: : 99iter [00:10, 11.56iter/s]
Best score: 15.2737: : 100iter [00:10, 11.56iter/s]
Best score: 15.2737: : 101iter [00:10,  9.92iter/s]
Best score: 15.2737: : 101iter [00:10,  9.92iter/s]
Best score: 15.2737: : 102iter [00:10,  9.92iter/s]
Best score: 15.2737: : 103iter [00:10, 10.39iter/s]
Best score: 15.2737: : 103iter [00:10, 10.39iter/s]
Best score: 15.2737: : 104iter [00:11, 10.39iter/s]
Best score: 15.2737: : 105iter [00:11, 10.70iter/s]
Best score: 15.2737: : 105iter [00:11, 10.70iter/s]
Best score: 15.2737: : 106iter [00:11, 10.70iter/s]
Best score: 15.2737: : 107iter [00:11, 10.94iter/s]
Best score: 15.2737: : 107iter [00:11, 10.94iter/s]
Best score: 15.2737: : 108iter [00:11, 10.94iter/s]
Best score: 15.2737: : 109iter [00:11, 11.13iter/s]
Best score: 15.2737: : 109iter [00:11, 11.13iter/s]
Best score: 15.2737: : 110iter [00:11, 11.13iter/s]
Best score: 15.2737: : 111iter [00:11, 11.11iter/s]
Best score: 15.2737: : 111iter [00:11, 11.11iter/s]
Best score: 15.2737: : 112iter [00:11, 11.11iter/s]
Best score: 15.2737: : 113iter [00:11, 11.23iter/s]
Best score: 15.2737: : 113iter [00:11, 11.23iter/s]
Best score: 15.2737: : 114iter [00:11, 11.23iter/s]
Best score: 15.2737: : 115iter [00:11, 11.36iter/s]
Best score: 15.2737: : 115iter [00:12, 11.36iter/s]
Best score: 15.2737: : 116iter [00:12, 11.36iter/s]
Best score: 15.2737: : 117iter [00:12, 11.47iter/s]
Best score: 15.2737: : 117iter [00:12, 11.47iter/s]
Best score: 15.2737: : 118iter [00:12, 11.47iter/s]
Best score: 15.2737: : 119iter [00:12, 11.54iter/s]
Best score: 15.2737: : 119iter [00:12, 11.54iter/s]
Best score: 15.2737: : 120iter [00:12, 11.54iter/s]
Best score: 15.2737: : 121iter [00:12, 11.41iter/s]
Best score: 15.2737: : 121iter [00:12, 11.41iter/s]
Best score: 15.2737: : 122iter [00:12, 11.41iter/s]
Best score: 15.2737: : 123iter [00:12, 11.47iter/s]
Best score: 15.2737: : 123iter [00:12, 11.47iter/s]
Best score: 15.2737: : 124iter [00:12, 11.47iter/s]
Best score: 15.2737: : 125iter [00:12, 11.53iter/s]
Best score: 15.2737: : 125iter [00:12, 11.53iter/s]
Best score: 15.2737: : 126iter [00:12, 11.53iter/s]
Best score: 15.2737: : 127iter [00:12, 11.59iter/s]
Best score: 15.2737: : 127iter [00:13, 11.59iter/s]
Best score: 15.2737: : 128iter [00:13, 11.59iter/s]
Best score: 15.2737: : 129iter [00:13, 11.65iter/s]
Best score: 15.2737: : 129iter [00:13, 11.65iter/s]
Best score: 15.2737: : 130iter [00:13, 11.65iter/s]
Best score: 15.2737: : 131iter [00:13, 11.37iter/s]
Best score: 15.2737: : 131iter [00:13, 11.37iter/s]
Best score: 15.2737: : 132iter [00:13, 11.37iter/s]
Best score: 15.2737: : 133iter [00:13, 11.45iter/s]
Best score: 15.2737: : 133iter [00:13, 11.45iter/s]
Best score: 15.2737: : 134iter [00:13, 11.45iter/s]
Best score: 15.2737: : 135iter [00:13, 11.47iter/s]
Best score: 15.2737: : 135iter [00:13, 11.47iter/s]
Best score: 15.2737: : 136iter [00:13, 11.47iter/s]
Best score: 15.2737: : 137iter [00:13, 11.55iter/s]
Best score: 15.2737: : 137iter [00:13, 11.55iter/s]
Best score: 15.2737: : 138iter [00:13, 11.55iter/s]
Best score: 15.2737: : 139iter [00:13, 11.57iter/s]
Best score: 15.2737: : 139iter [00:14, 11.57iter/s]
Best score: 15.2737: : 140iter [00:14, 11.57iter/s]
Best score: 15.2737: : 141iter [00:14, 11.42iter/s]
Best score: 15.2737: : 141iter [00:14, 11.42iter/s]
Best score: 15.2737: : 142iter [00:14, 11.42iter/s]
Best score: 15.2737: : 143iter [00:14, 11.54iter/s]
Best score: 15.2737: : 143iter [00:14, 11.54iter/s]
Best score: 15.2737: : 144iter [00:14, 11.54iter/s]
Best score: 15.2737: : 145iter [00:14, 11.57iter/s]
Best score: 15.2737: : 145iter [00:14, 11.57iter/s]
Best score: 15.2737: : 146iter [00:14, 11.57iter/s]
Best score: 15.2737: : 147iter [00:14, 11.58iter/s]
Best score: 15.2737: : 147iter [00:14, 11.58iter/s]
Best score: 15.2737: : 148iter [00:14, 11.58iter/s]
Best score: 15.2737: : 149iter [00:14, 11.66iter/s]
Best score: 15.2737: : 149iter [00:14, 11.66iter/s]
[ITER 150] Best: 15.2737
[PARAMS] Current best parameters:
  fx: 526.2996
  fy: 519.4419
  px: 897.6032
  py: 926.4103
  k1: 0.03445007
  k2: -0.05512106
  k3: 0.04321255
  k4: -0.01150405
  p1: -0.01488007
  p2: -0.01996576
  p3: 0.00041291
  p4: 0.02826470
  s1: 0.0056
  s2: -0.0205
  s3: 0.0155
  s4: -0.0234
  tilt_x: -0.0113
  tilt_y: 0.0188
  scale: 2.9320
  rotation: -1.4347

Best score: 15.2737: : 150iter [00:15, 11.66iter/s]
Best score: 15.2737: : 151iter [00:15,  7.51iter/s]
Best score: 15.2737: : 151iter [00:15,  7.51iter/s]
Best score: 15.2737: : 152iter [00:15,  7.51iter/s]
Best score: 15.2737: : 153iter [00:15,  8.39iter/s]
Best score: 15.2737: : 153iter [00:15,  8.39iter/s]
Best score: 15.2737: : 154iter [00:15,  8.39iter/s]
Best score: 15.2737: : 155iter [00:15,  9.17iter/s]
Best score: 15.2737: : 155iter [00:15,  9.17iter/s]
Best score: 15.2737: : 156iter [00:15,  9.17iter/s]
Best score: 15.2737: : 157iter [00:15,  9.80iter/s]
Best score: 15.2737: : 157iter [00:15,  9.80iter/s]
Best score: 15.2737: : 158iter [00:16,  9.80iter/s]
Best score: 15.2737: : 159iter [00:16, 10.35iter/s]
Best score: 15.2737: : 159iter [00:16, 10.35iter/s]
Best score: 15.2737: : 160iter [00:16, 10.35iter/s]
Best score: 15.2737: : 161iter [00:16, 10.56iter/s]
Best score: 15.2737: : 161iter [00:16, 10.56iter/s]
Best score: 15.2737: : 162iter [00:16, 10.56iter/s]
Best score: 15.2737: : 163iter [00:16, 10.88iter/s]
Best score: 15.2737: : 163iter [00:16, 10.88iter/s]
Best score: 15.2737: : 164iter [00:16, 10.88iter/s]
Best score: 15.2737: : 165iter [00:16, 11.14iter/s]
Best score: 15.2737: : 165iter [00:16, 11.14iter/s]
Best score: 15.2737: : 166iter [00:16, 11.14iter/s]
Best score: 15.2737: : 167iter [00:16, 11.31iter/s]
Best score: 15.2737: : 167iter [00:16, 11.31iter/s]
Best score: 15.2737: : 168iter [00:16, 11.31iter/s]
Best score: 15.2737: : 169iter [00:16, 11.46iter/s]
Best score: 15.2737: : 169iter [00:16, 11.46iter/s]
Best score: 15.2737: : 170iter [00:17, 11.46iter/s]
Best score: 15.2737: : 171iter [00:17, 11.35iter/s]
Best score: 15.2737: : 171iter [00:17, 11.35iter/s]
Best score: 15.2737: : 172iter [00:17, 11.35iter/s]
Best score: 15.2737: : 173iter [00:17, 11.43iter/s]
Best score: 15.2737: : 173iter [00:17, 11.43iter/s]
Best score: 15.2737: : 174iter [00:17, 11.43iter/s]
Best score: 15.2737: : 175iter [00:17, 11.55iter/s]
Best score: 15.2737: : 175iter [00:17, 11.55iter/s]
Best score: 15.2737: : 176iter [00:17, 11.55iter/s]
Best score: 15.2737: : 177iter [00:17, 11.67iter/s]
Best score: 15.2737: : 177iter [00:17, 11.67iter/s]
Best score: 15.2737: : 178iter [00:17, 11.67iter/s]
Best score: 15.2737: : 179iter [00:17, 11.73iter/s]
Best score: 15.2737: : 179iter [00:17, 11.73iter/s]
Best score: 15.2737: : 180iter [00:17, 11.73iter/s]
Best score: 15.2737: : 181iter [00:17, 11.57iter/s]
Best score: 15.2737: : 181iter [00:18, 11.57iter/s]
Best score: 15.2737: : 182iter [00:18, 11.57iter/s]
Best score: 15.2737: : 183iter [00:18, 11.63iter/s]
Best score: 15.2737: : 183iter [00:18, 11.63iter/s]
Best score: 15.2737: : 184iter [00:18, 11.63iter/s]
Best score: 15.2737: : 185iter [00:18,  8.81iter/s]
Best score: 15.2737: : 185iter [00:18,  8.81iter/s]
Best score: 15.2737: : 186iter [00:18,  8.81iter/s]
Best score: 15.2737: : 187iter [00:18,  9.55iter/s]
Best score: 15.2737: : 187iter [00:18,  9.55iter/s]
Best score: 15.2737: : 188iter [00:18,  9.55iter/s]
Best score: 15.2737: : 189iter [00:18, 10.14iter/s]
Best score: 15.2737: : 189iter [00:18, 10.14iter/s]
Best score: 15.2737: : 190iter [00:18, 10.14iter/s]
Best score: 15.2737: : 191iter [00:18, 10.43iter/s]
Best score: 15.2737: : 191iter [00:19, 10.43iter/s]
Best score: 15.2737: : 192iter [00:19, 10.43iter/s]
Best score: 15.2737: : 193iter [00:19, 10.85iter/s]
Best score: 15.2737: : 193iter [00:19, 10.85iter/s]
Best score: 15.2737: : 194iter [00:19, 10.85iter/s]
Best score: 15.2737: : 195iter [00:19, 11.13iter/s]
Best score: 15.2737: : 195iter [00:19, 11.13iter/s]
Best score: 15.2737: : 196iter [00:19, 11.13iter/s]
Best score: 15.2737: : 197iter [00:19, 11.37iter/s]
Best score: 15.2737: : 197iter [00:19, 11.37iter/s]
Best score: 15.2737: : 198iter [00:19, 11.37iter/s]
Best score: 15.2737: : 199iter [00:19, 11.52iter/s]
[ITER 200] Best: 12.1586
[PARAMS] Current best parameters:
  fx: 505.9410
  fy: 506.6097
  px: 894.0379
  py: 921.4223
  k1: 0.04709400
  k2: -0.05867068
  k3: 0.03861573
  k4: -0.00775160
  p1: -0.00422436
  p2: -0.02157944
  p3: -0.00894529
  p4: 0.02539227
  s1: 0.0123
  s2: -0.0230
  s3: 0.0057
  s4: -0.0457
  tilt_x: -0.0010
  tilt_y: 0.0104
  scale: 2.9951
  rotation: -1.5799

Best score: 12.1586: : 199iter [00:19, 11.52iter/s]
Best score: 12.1586: : 200iter [00:20, 11.52iter/s]
Best score: 12.1586: : 201iter [00:20,  7.45iter/s]
Best score: 12.1586: : 201iter [00:20,  7.45iter/s]
Best score: 12.1586: : 202iter [00:20,  7.45iter/s]
Best score: 12.1586: : 203iter [00:20,  8.36iter/s]
Best score: 12.1586: : 203iter [00:20,  8.36iter/s]
Best score: 12.1586: : 204iter [00:20,  8.36iter/s]
Best score: 12.1586: : 205iter [00:20,  9.18iter/s]
Best score: 12.1586: : 205iter [00:20,  9.18iter/s]
Best score: 12.1586: : 206iter [00:20,  9.18iter/s]
Best score: 12.1586: : 207iter [00:20,  9.86iter/s]
Best score: 12.1586: : 207iter [00:20,  9.86iter/s]
Best score: 12.1586: : 208iter [00:20,  9.86iter/s]
Best score: 12.1586: : 209iter [00:20, 10.40iter/s]
Best score: 9.8009: : 209iter [00:20, 10.40iter/s] 
Best score: 9.8009: : 210iter [00:20, 10.40iter/s]
Best score: 9.8009: : 211iter [00:20, 10.68iter/s]
Best score: 9.8009: : 211iter [00:21, 10.68iter/s]
Best score: 9.8009: : 212iter [00:21, 10.68iter/s]
Best score: 9.8009: : 213iter [00:21, 10.98iter/s]
Best score: 9.8009: : 213iter [00:21, 10.98iter/s]
Best score: 9.8009: : 214iter [00:21, 10.98iter/s]
Best score: 9.8009: : 215iter [00:21, 11.22iter/s]
Best score: 9.8009: : 215iter [00:21, 11.22iter/s]
Best score: 9.8009: : 216iter [00:21, 11.22iter/s]
Best score: 9.8009: : 217iter [00:21, 11.42iter/s]
Best score: 9.8009: : 217iter [00:21, 11.42iter/s]
Best score: 9.8009: : 218iter [00:21, 11.42iter/s]
Best score: 9.8009: : 219iter [00:21, 11.55iter/s]
Best score: 9.8009: : 219iter [00:21, 11.55iter/s]
Best score: 9.8009: : 220iter [00:21, 11.55iter/s]
Best score: 9.8009: : 221iter [00:21, 11.51iter/s]
Best score: 9.8009: : 221iter [00:21, 11.51iter/s]
Best score: 9.8009: : 222iter [00:21, 11.51iter/s]
Best score: 9.8009: : 223iter [00:21, 11.59iter/s]
Best score: 9.8009: : 223iter [00:22, 11.59iter/s]
Best score: 9.8009: : 224iter [00:22, 11.59iter/s]
Best score: 9.8009: : 225iter [00:22, 11.72iter/s]
Best score: 9.8009: : 225iter [00:22, 11.72iter/s]
Best score: 9.8009: : 226iter [00:22, 11.72iter/s]
Best score: 9.8009: : 227iter [00:22, 11.77iter/s]
Best score: 9.8009: : 227iter [00:22, 11.77iter/s]
Best score: 9.8009: : 228iter [00:22, 11.77iter/s]
Best score: 9.8009: : 229iter [00:22, 11.86iter/s]
Best score: 4.8421: : 229iter [00:22, 11.86iter/s]
Best score: 4.8421: : 230iter [00:22, 11.86iter/s]
Best score: 4.8421: : 231iter [00:22, 11.68iter/s]
Best score: 4.8421: : 231iter [00:22, 11.68iter/s]
Best score: 4.8421: : 232iter [00:22, 11.68iter/s]
Best score: 4.8421: : 233iter [00:22, 11.77iter/s]
Best score: 4.8421: : 233iter [00:22, 11.77iter/s]
Best score: 4.8421: : 234iter [00:23, 11.77iter/s]
Best score: 4.8421: : 235iter [00:23, 11.86iter/s]
Best score: 4.8421: : 235iter [00:23, 11.86iter/s]
Best score: 4.8421: : 236iter [00:23, 11.86iter/s]
Best score: 4.8421: : 237iter [00:23, 11.85iter/s]
Best score: 4.8421: : 237iter [00:23, 11.85iter/s]
Best score: 4.8421: : 238iter [00:23, 11.85iter/s]
Best score: 4.8421: : 239iter [00:23, 11.89iter/s]
Best score: 4.8421: : 239iter [00:23, 11.89iter/s]
Best score: 4.8421: : 240iter [00:23, 11.89iter/s]
Best score: 4.8421: : 241iter [00:23, 11.73iter/s]
Best score: 4.8421: : 241iter [00:23, 11.73iter/s]
Best score: 4.8421: : 242iter [00:23, 11.73iter/s]
Best score: 4.8421: : 243iter [00:23, 11.84iter/s]
Best score: 4.8421: : 243iter [00:23, 11.84iter/s]
Best score: 4.8421: : 244iter [00:23, 11.84iter/s]
Best score: 4.8421: : 245iter [00:23, 11.89iter/s]
Best score: 4.8421: : 245iter [00:23, 11.89iter/s]
Best score: 4.8421: : 246iter [00:24, 11.89iter/s]
Best score: 4.8421: : 247iter [00:24, 11.89iter/s]
Best score: 4.8421: : 247iter [00:24, 11.89iter/s]
Best score: 4.8421: : 248iter [00:24, 11.89iter/s]
Best score: 4.8421: : 249iter [00:24, 11.90iter/s]
[ITER 250] Best: 4.8421
[PARAMS] Current best parameters:
  fx: 538.2512
  fy: 538.1004
  px: 893.3337
  py: 908.6289
  k1: -0.00241026
  k2: -0.04855937
  k3: 0.04166935
  k4: -0.00958561
  p1: -0.00213568
  p2: -0.01837223
  p3: 0.01376941
  p4: 0.02184520
  s1: -0.0011
  s2: -0.0202
  s3: -0.0199
  s4: -0.0336
  tilt_x: -0.0950
  tilt_y: 0.0335
  scale: 3.0583
  rotation: -1.2142

Best score: 4.8421: : 249iter [00:24, 11.90iter/s]
Best score: 4.8421: : 250iter [00:24, 11.90iter/s]
Best score: 4.8421: : 251iter [00:24,  7.63iter/s]
Best score: 4.8421: : 251iter [00:24,  7.63iter/s]
Best score: 4.8421: : 252iter [00:24,  7.63iter/s]
Best score: 4.8421: : 253iter [00:24,  8.56iter/s]
Best score: 4.8421: : 253iter [00:24,  8.56iter/s]
Best score: 4.8421: : 254iter [00:25,  8.56iter/s]
Best score: 4.8421: : 255iter [00:25,  9.34iter/s]
Best score: 4.8421: : 255iter [00:25,  9.34iter/s]
Best score: 4.8421: : 256iter [00:25,  9.34iter/s]
Best score: 4.8421: : 257iter [00:25, 10.02iter/s]
Best score: 4.8421: : 257iter [00:25, 10.02iter/s]
Best score: 4.8421: : 258iter [00:25, 10.02iter/s]
Best score: 4.8421: : 259iter [00:25, 10.56iter/s]
Best score: 4.2378: : 259iter [00:25, 10.56iter/s]
Best score: 4.2378: : 260iter [00:25, 10.56iter/s]
Best score: 4.2378: : 261iter [00:25, 10.78iter/s]
Best score: 4.2378: : 261iter [00:25, 10.78iter/s]
Best score: 4.2378: : 262iter [00:25, 10.78iter/s]
Best score: 4.2378: : 263iter [00:25, 11.13iter/s]
Best score: 4.2378: : 263iter [00:25, 11.13iter/s]
Best score: 4.2378: : 264iter [00:25, 11.13iter/s]
Best score: 4.2378: : 265iter [00:25, 11.39iter/s]
Best score: 4.2378: : 265iter [00:25, 11.39iter/s]
Best score: 4.2378: : 266iter [00:26, 11.39iter/s]
Best score: 4.2378: : 267iter [00:26, 11.57iter/s]
Best score: 4.2378: : 267iter [00:26, 11.57iter/s]
Best score: 4.2378: : 268iter [00:26, 11.57iter/s]
Best score: 4.2378: : 269iter [00:26, 11.70iter/s]
Best score: 3.8034: : 269iter [00:26, 11.70iter/s]
Best score: 3.8034: : 270iter [00:26, 11.70iter/s]
Best score: 3.8034: : 271iter [00:26, 11.58iter/s]
Best score: 3.8034: : 271iter [00:26, 11.58iter/s]
Best score: 3.8034: : 272iter [00:26, 11.58iter/s]
Best score: 3.8034: : 273iter [00:26, 11.72iter/s]
Best score: 3.8034: : 273iter [00:26, 11.72iter/s]
Best score: 3.8034: : 274iter [00:26, 11.72iter/s]
Best score: 3.8034: : 275iter [00:26, 11.82iter/s]
Best score: 3.8034: : 275iter [00:26, 11.82iter/s]
Best score: 3.8034: : 276iter [00:26, 11.82iter/s]
Best score: 3.8034: : 277iter [00:26, 11.90iter/s]
Best score: 3.8034: : 277iter [00:26, 11.90iter/s]
Best score: 3.8034: : 278iter [00:27, 11.90iter/s]
Best score: 3.8034: : 279iter [00:27, 11.93iter/s]
Best score: 3.6006: : 279iter [00:27, 11.93iter/s]
Best score: 3.6006: : 280iter [00:27, 11.93iter/s]
Best score: 3.6006: : 281iter [00:27, 11.71iter/s]
Best score: 3.6006: : 281iter [00:27, 11.71iter/s]
Best score: 3.6006: : 282iter [00:27, 11.71iter/s]
Best score: 3.6006: : 283iter [00:27, 11.80iter/s]
Best score: 3.6006: : 283iter [00:27, 11.80iter/s]
Best score: 3.6006: : 284iter [00:27, 11.80iter/s]
Best score: 3.6006: : 285iter [00:27, 11.87iter/s]
Best score: 3.6006: : 285iter [00:27, 11.87iter/s]
Best score: 3.6006: : 286iter [00:27, 11.87iter/s]
Best score: 3.6006: : 287iter [00:27, 11.90iter/s]
Best score: 3.6006: : 287iter [00:27, 11.90iter/s]
Best score: 3.6006: : 288iter [00:27, 11.90iter/s]
Best score: 3.6006: : 289iter [00:27, 11.94iter/s]
Best score: 3.2002: : 289iter [00:27, 11.94iter/s]
Best score: 3.2002: : 290iter [00:28, 11.94iter/s]
Best score: 3.2002: : 291iter [00:28, 11.75iter/s]
Best score: 3.2002: : 291iter [00:28, 11.75iter/s]
Best score: 3.2002: : 292iter [00:28, 11.75iter/s]
Best score: 3.2002: : 293iter [00:28, 11.83iter/s]
Best score: 3.2002: : 293iter [00:28, 11.83iter/s]
Best score: 3.2002: : 294iter [00:28, 11.83iter/s]
Best score: 3.2002: : 295iter [00:28, 11.84iter/s]
Best score: 3.2002: : 295iter [00:28, 11.84iter/s]
Best score: 3.2002: : 296iter [00:28, 11.84iter/s]
Best score: 3.2002: : 297iter [00:28, 11.90iter/s]
Best score: 3.2002: : 297iter [00:28, 11.90iter/s]
Best score: 3.2002: : 298iter [00:28, 11.90iter/s]
Best score: 3.2002: : 299iter [00:28, 11.92iter/s]
[ITER 300] Best: 2.6156
[PARAMS] Current best parameters:
  fx: 543.5912
  fy: 541.6775
  px: 899.7796
  py: 920.4445
  k1: -0.01997679
  k2: -0.02000392
  k3: 0.03323043
  k4: -0.01128483
  p1: -0.00768560
  p2: -0.02003338
  p3: 0.01114449
  p4: 0.03426725
  s1: 0.0195
  s2: -0.0441
  s3: -0.0097
  s4: -0.0307
  tilt_x: -0.0384
  tilt_y: 0.0033
  scale: 2.9792
  rotation: -1.3137

Best score: 2.6156: : 299iter [00:28, 11.92iter/s]
Best score: 2.6156: : 300iter [00:29, 11.92iter/s]
Best score: 2.6156: : 301iter [00:29,  7.59iter/s]
Best score: 2.6156: : 301iter [00:29,  7.59iter/s]
Best score: 2.6156: : 302iter [00:29,  7.59iter/s]
Best score: 2.6156: : 303iter [00:29,  8.52iter/s]
Best score: 2.6156: : 303iter [00:29,  8.52iter/s]
Best score: 2.6156: : 304iter [00:29,  8.52iter/s]
Best score: 2.6156: : 305iter [00:29,  9.31iter/s]
Best score: 2.6156: : 305iter [00:29,  9.31iter/s]
Best score: 2.6156: : 306iter [00:29,  9.31iter/s]
Best score: 2.6156: : 307iter [00:29,  9.94iter/s]
Best score: 2.6156: : 307iter [00:29,  9.94iter/s]
Best score: 2.6156: : 308iter [00:29,  9.94iter/s]
Best score: 2.6156: : 309iter [00:29, 10.47iter/s]
Best score: 2.1237: : 309iter [00:29, 10.47iter/s]
Best score: 2.1237: : 310iter [00:30, 10.47iter/s]
Best score: 2.1237: : 311iter [00:30, 10.67iter/s]
Best score: 2.1237: : 311iter [00:30, 10.67iter/s]
Best score: 2.1237: : 312iter [00:30, 10.67iter/s]
Best score: 2.1237: : 313iter [00:30, 11.04iter/s]
Best score: 2.1237: : 313iter [00:30, 11.04iter/s]
Best score: 2.1237: : 314iter [00:30, 11.04iter/s]
Best score: 2.1237: : 315iter [00:30, 11.31iter/s]
Best score: 2.1237: : 315iter [00:30, 11.31iter/s]
Best score: 2.1237: : 316iter [00:30, 11.31iter/s]
Best score: 2.1237: : 317iter [00:30, 11.52iter/s]
Best score: 2.1237: : 317iter [00:30, 11.52iter/s]
Best score: 2.1237: : 318iter [00:30, 11.52iter/s]
Best score: 2.1237: : 319iter [00:30, 11.67iter/s]
Best score: 1.7613: : 319iter [00:30, 11.67iter/s]
Best score: 1.7613: : 320iter [00:30, 11.67iter/s]
Best score: 1.7613: : 321iter [00:30, 11.51iter/s]
Best score: 1.7613: : 321iter [00:30, 11.51iter/s]
Best score: 1.7613: : 322iter [00:31, 11.51iter/s]
Best score: 1.7613: : 323iter [00:31, 11.64iter/s]
Best score: 1.7613: : 323iter [00:31, 11.64iter/s]
Best score: 1.7613: : 324iter [00:31, 11.64iter/s]
Best score: 1.7613: : 325iter [00:31, 11.75iter/s]
Best score: 1.7613: : 325iter [00:31, 11.75iter/s]
Best score: 1.7613: : 326iter [00:31, 11.75iter/s]
Best score: 1.7613: : 327iter [00:31, 11.83iter/s]
Best score: 1.7613: : 327iter [00:31, 11.83iter/s]
Best score: 1.7613: : 328iter [00:31, 11.83iter/s]
Best score: 1.7613: : 329iter [00:31, 11.87iter/s]
Best score: 1.0595: : 329iter [00:31, 11.87iter/s]
Best score: 1.0595: : 330iter [00:31, 11.87iter/s]
Best score: 1.0595: : 331iter [00:31, 11.64iter/s]
Best score: 1.0595: : 331iter [00:31, 11.64iter/s]
Best score: 1.0595: : 332iter [00:31, 11.64iter/s]
Best score: 1.0595: : 333iter [00:31, 11.73iter/s]
Best score: 1.0595: : 333iter [00:31, 11.73iter/s]
Best score: 1.0595: : 334iter [00:32, 11.73iter/s]
Best score: 1.0595: : 335iter [00:32, 11.79iter/s]
Best score: 1.0595: : 335iter [00:32, 11.79iter/s]
Best score: 1.0595: : 336iter [00:32, 11.79iter/s]
Best score: 1.0595: : 337iter [00:32, 11.87iter/s]
Best score: 1.0595: : 337iter [00:32, 11.87iter/s]
Best score: 1.0595: : 338iter [00:32, 11.87iter/s]
Best score: 1.0595: : 339iter [00:32, 11.90iter/s]
Best score: 1.0595: : 339iter [00:32, 11.90iter/s]
Best score: 1.0595: : 340iter [00:32, 11.90iter/s]
Best score: 1.0595: : 341iter [00:32, 11.73iter/s]
Best score: 1.0595: : 341iter [00:32, 11.73iter/s]
Best score: 1.0595: : 342iter [00:32, 11.73iter/s]
Best score: 1.0595: : 343iter [00:32, 11.80iter/s]
Best score: 1.0595: : 343iter [00:32, 11.80iter/s]
Best score: 1.0595: : 344iter [00:32, 11.80iter/s]
Best score: 1.0595: : 345iter [00:32, 11.86iter/s]
Best score: 1.0595: : 345iter [00:33, 11.86iter/s]
Best score: 1.0595: : 346iter [00:33, 11.86iter/s]
Best score: 1.0595: : 347iter [00:33, 11.88iter/s]
Best score: 1.0595: : 347iter [00:33, 11.88iter/s]
Best score: 1.0595: : 348iter [00:33, 11.88iter/s]
Best score: 1.0595: : 349iter [00:33, 11.86iter/s]
[ITER 350] Best: 0.9741
[PARAMS] Current best parameters:
  fx: 550.0614
  fy: 550.2308
  px: 905.9185
  py: 920.9384
  k1: -0.03166896
  k2: 0.01759612
  k3: -0.00913737
  k4: 0.00184025
  p1: -0.00446020
  p2: -0.00934259
  p3: 0.00749130
  p4: 0.03599860
  s1: -0.0134
  s2: -0.0265
  s3: -0.0104
  s4: -0.0290
  tilt_x: -0.0380
  tilt_y: -0.0101
  scale: 2.9687
  rotation: -1.0845

Best score: 0.9741: : 349iter [00:33, 11.86iter/s]
Best score: 0.9741: : 350iter [00:33, 11.86iter/s]
Best score: 0.9741: : 351iter [00:33,  7.60iter/s]
Best score: 0.9741: : 351iter [00:33,  7.60iter/s]
Best score: 0.9741: : 352iter [00:33,  7.60iter/s]
Best score: 0.9741: : 353iter [00:33,  8.52iter/s]
Best score: 0.9741: : 353iter [00:33,  8.52iter/s]
Best score: 0.9741: : 354iter [00:34,  8.52iter/s]
Best score: 0.9741: : 355iter [00:34,  9.32iter/s]
Best score: 0.9741: : 355iter [00:34,  9.32iter/s]
Best score: 0.9741: : 356iter [00:34,  9.32iter/s]
Best score: 0.9741: : 357iter [00:34,  9.97iter/s]
Best score: 0.9741: : 357iter [00:34,  9.97iter/s]
Best score: 0.9741: : 358iter [00:34,  9.97iter/s]
Best score: 0.9741: : 359iter [00:34, 10.49iter/s]
Best score: 0.9741: : 359iter [00:34, 10.49iter/s]
Best score: 0.9741: : 360iter [00:34, 10.49iter/s]
Best score: 0.9741: : 361iter [00:34, 10.70iter/s]
Best score: 0.9741: : 361iter [00:34, 10.70iter/s]
Best score: 0.9741: : 362iter [00:34, 10.70iter/s]
Best score: 0.9741: : 363iter [00:34, 11.07iter/s]
Best score: 0.9741: : 363iter [00:34, 11.07iter/s]
Best score: 0.9741: : 364iter [00:34, 11.07iter/s]
Best score: 0.9741: : 365iter [00:34, 11.33iter/s]
Best score: 0.9741: : 365iter [00:35, 11.33iter/s]
Best score: 0.9741: : 366iter [00:35, 11.33iter/s]
Best score: 0.9741: : 367iter [00:35, 11.49iter/s]
Best score: 0.9741: : 367iter [00:35, 11.49iter/s]
Best score: 0.9741: : 368iter [00:35, 11.49iter/s]
Best score: 0.9741: : 369iter [00:35, 11.59iter/s]
Best score: 0.6759: : 369iter [00:35, 11.59iter/s]
Best score: 0.6759: : 370iter [00:35, 11.59iter/s]
Best score: 0.6759: : 371iter [00:35, 11.50iter/s]
Best score: 0.6759: : 371iter [00:35, 11.50iter/s]
Best score: 0.6759: : 372iter [00:35, 11.50iter/s]
Best score: 0.6759: : 373iter [00:35, 11.65iter/s]
Best score: 0.6759: : 373iter [00:35, 11.65iter/s]
Best score: 0.6759: : 374iter [00:35, 11.65iter/s]
Best score: 0.6759: : 375iter [00:35, 11.76iter/s]
Best score: 0.6759: : 375iter [00:35, 11.76iter/s]
Best score: 0.6759: : 376iter [00:35, 11.76iter/s]
Best score: 0.6759: : 377iter [00:35, 11.83iter/s]
Best score: 0.6759: : 377iter [00:36, 11.83iter/s]
Best score: 0.6759: : 378iter [00:36, 11.83iter/s]
Best score: 0.6759: : 379iter [00:36, 11.87iter/s]
Best score: 0.6722: : 379iter [00:36, 11.87iter/s]
Best score: 0.6722: : 380iter [00:36, 11.87iter/s]
Best score: 0.6722: : 381iter [00:36, 11.68iter/s]
Best score: 0.6722: : 381iter [00:36, 11.68iter/s]
Best score: 0.6722: : 382iter [00:36, 11.68iter/s]
Best score: 0.6722: : 383iter [00:36, 11.78iter/s]
Best score: 0.6722: : 383iter [00:36, 11.78iter/s]
Best score: 0.6722: : 384iter [00:36, 11.78iter/s]
Best score: 0.6722: : 385iter [00:36, 11.86iter/s]
Best score: 0.6722: : 385iter [00:36, 11.86iter/s]
Best score: 0.6722: : 386iter [00:36, 11.86iter/s]
Best score: 0.6722: : 387iter [00:36, 11.89iter/s]
Best score: 0.6722: : 387iter [00:36, 11.89iter/s]
Best score: 0.6722: : 388iter [00:36, 11.89iter/s]
Best score: 0.6722: : 389iter [00:36, 11.92iter/s]
Best score: 0.6635: : 389iter [00:37, 11.92iter/s]
Best score: 0.6635: : 390iter [00:37, 11.92iter/s]
Best score: 0.6635: : 391iter [00:37, 11.73iter/s]
Best score: 0.6635: : 391iter [00:37, 11.73iter/s]
Best score: 0.6635: : 392iter [00:37, 11.73iter/s]
Best score: 0.6635: : 393iter [00:37, 11.78iter/s]
Best score: 0.6635: : 393iter [00:37, 11.78iter/s]
Best score: 0.6635: : 394iter [00:37, 11.78iter/s]
Best score: 0.6635: : 395iter [00:37, 11.82iter/s]
Best score: 0.6635: : 395iter [00:37, 11.82iter/s]
Best score: 0.6635: : 396iter [00:37, 11.82iter/s]
Best score: 0.6635: : 397iter [00:37, 11.87iter/s]
Best score: 0.6635: : 397iter [00:37, 11.87iter/s]
Best score: 0.6635: : 398iter [00:37, 11.87iter/s]
Best score: 0.6635: : 399iter [00:37, 11.90iter/s]
[ITER 400] Best: 0.4325
[PARAMS] Current best parameters:
  fx: 540.4602
  fy: 541.1849
  px: 906.4055
  py: 919.8164
  k1: -0.00566145
  k2: -0.00102310
  k3: -0.00064096
  k4: -0.00018089
  p1: -0.02105850
  p2: -0.00839801
  p3: 0.00808120
  p4: 0.03168478
  s1: 0.0048
  s2: -0.0376
  s3: 0.0023
  s4: -0.0300
  tilt_x: -0.0066
  tilt_y: -0.0128
  scale: 2.9332
  rotation: -1.2717

Best score: 0.4325: : 399iter [00:37, 11.90iter/s]
Best score: 0.4325: : 400iter [00:38, 11.90iter/s]
Best score: 0.4325: : 401iter [00:38,  7.62iter/s]
Best score: 0.4325: : 401iter [00:38,  7.62iter/s]
Best score: 0.4325: : 402iter [00:38,  7.62iter/s]
Best score: 0.4325: : 403iter [00:38,  8.54iter/s]
Best score: 0.4325: : 403iter [00:38,  8.54iter/s]
Best score: 0.4325: : 404iter [00:38,  8.54iter/s]
Best score: 0.4325: : 405iter [00:38,  9.34iter/s]
Best score: 0.4325: : 405iter [00:38,  9.34iter/s]
Best score: 0.4325: : 406iter [00:38,  9.34iter/s]
Best score: 0.4325: : 407iter [00:38, 10.01iter/s]
Best score: 0.4325: : 407iter [00:38, 10.01iter/s]
Best score: 0.4325: : 408iter [00:38, 10.01iter/s]
Best score: 0.4325: : 409iter [00:38, 10.55iter/s]
Best score: 0.4325: : 409iter [00:39, 10.55iter/s]
Best score: 0.4325: : 410iter [00:39, 10.55iter/s]
Best score: 0.4325: : 411iter [00:39, 10.78iter/s]
Best score: 0.4325: : 411iter [00:39, 10.78iter/s]
Best score: 0.4325: : 412iter [00:39, 10.78iter/s]
Best score: 0.4325: : 413iter [00:39, 11.08iter/s]
Best score: 0.4325: : 413iter [00:39, 11.08iter/s]
Best score: 0.4325: : 414iter [00:39, 11.08iter/s]
Best score: 0.4325: : 415iter [00:39, 11.35iter/s]
Best score: 0.4325: : 415iter [00:39, 11.35iter/s]
Best score: 0.4325: : 416iter [00:39, 11.35iter/s]
Best score: 0.4325: : 417iter [00:39, 11.52iter/s]
Best score: 0.4325: : 417iter [00:39, 11.52iter/s]
Best score: 0.4325: : 418iter [00:39, 11.52iter/s]
Best score: 0.4325: : 419iter [00:39, 11.67iter/s]
Best score: 0.3936: : 419iter [00:39, 11.67iter/s]
Best score: 0.3936: : 420iter [00:39, 11.67iter/s]
Best score: 0.3936: : 421iter [00:39, 11.57iter/s]
Best score: 0.3936: : 421iter [00:40, 11.57iter/s]
Best score: 0.3936: : 422iter [00:40, 11.57iter/s]
Best score: 0.3936: : 423iter [00:40, 11.71iter/s]
Best score: 0.3936: : 423iter [00:40, 11.71iter/s]
Best score: 0.3936: : 424iter [00:40, 11.71iter/s]
Best score: 0.3936: : 425iter [00:40, 11.81iter/s]
Best score: 0.3936: : 425iter [00:40, 11.81iter/s]
Best score: 0.3936: : 426iter [00:40, 11.81iter/s]
Best score: 0.3936: : 427iter [00:40, 11.87iter/s]
Best score: 0.3936: : 427iter [00:40, 11.87iter/s]
Best score: 0.3936: : 428iter [00:40, 11.87iter/s]
Best score: 0.3936: : 429iter [00:40, 11.87iter/s]
Best score: 0.3936: : 429iter [00:40, 11.87iter/s]
Best score: 0.3936: : 430iter [00:40, 11.87iter/s]
Best score: 0.3936: : 431iter [00:40, 11.72iter/s]
Best score: 0.3936: : 431iter [00:40, 11.72iter/s]
Best score: 0.3936: : 432iter [00:40, 11.72iter/s]
Best score: 0.3936: : 433iter [00:40, 11.81iter/s]
Best score: 0.3936: : 433iter [00:41, 11.81iter/s]
Best score: 0.3936: : 434iter [00:41, 11.81iter/s]
Best score: 0.3936: : 435iter [00:41, 11.82iter/s]
Best score: 0.3936: : 435iter [00:41, 11.82iter/s]
Best score: 0.3936: : 436iter [00:41, 11.82iter/s]
Best score: 0.3936: : 437iter [00:41, 11.88iter/s]
Best score: 0.3936: : 437iter [00:41, 11.88iter/s]
Best score: 0.3936: : 438iter [00:41, 11.88iter/s]
Best score: 0.3936: : 439iter [00:41, 11.92iter/s]
Best score: 0.3420: : 439iter [00:41, 11.92iter/s]
Best score: 0.3420: : 440iter [00:41, 11.92iter/s]
Best score: 0.3420: : 441iter [00:41, 11.69iter/s]
Best score: 0.3420: : 441iter [00:41, 11.69iter/s]
Best score: 0.3420: : 442iter [00:41, 11.69iter/s]
Best score: 0.3420: : 443iter [00:41, 11.79iter/s]
Best score: 0.3420: : 443iter [00:41, 11.79iter/s]
Best score: 0.3420: : 444iter [00:41, 11.79iter/s]
Best score: 0.3420: : 445iter [00:41, 11.82iter/s]
Best score: 0.3420: : 445iter [00:42, 11.82iter/s]
Best score: 0.3420: : 446iter [00:42, 11.82iter/s]
Best score: 0.3420: : 447iter [00:42, 11.88iter/s]
Best score: 0.3420: : 447iter [00:42, 11.88iter/s]
Best score: 0.3420: : 448iter [00:42, 11.88iter/s]
Best score: 0.3420: : 449iter [00:42, 11.93iter/s]
[ITER 450] Best: 0.2860
[PARAMS] Current best parameters:
  fx: 545.7672
  fy: 545.6679
  px: 905.0854
  py: 919.0717
  k1: -0.02112760
  k2: 0.00469969
  k3: 0.00142239
  k4: -0.00134884
  p1: -0.01719278
  p2: -0.01486788
  p3: 0.01511347
  p4: 0.03060959
  s1: -0.0026
  s2: -0.0307
  s3: -0.0067
  s4: -0.0313
  tilt_x: -0.0182
  tilt_y: -0.0189
  scale: 2.9615
  rotation: -1.1608

Best score: 0.2860: : 449iter [00:42, 11.93iter/s]
Best score: 0.2860: : 450iter [00:42, 11.93iter/s]
Best score: 0.2860: : 451iter [00:42,  7.64iter/s]
Best score: 0.2860: : 451iter [00:42,  7.64iter/s]
Best score: 0.2860: : 452iter [00:42,  7.64iter/s]
Best score: 0.2860: : 453iter [00:42,  8.58iter/s]
Best score: 0.2860: : 453iter [00:43,  8.58iter/s]
Best score: 0.2860: : 454iter [00:43,  8.58iter/s]
Best score: 0.2860: : 455iter [00:43,  9.37iter/s]
Best score: 0.2860: : 455iter [00:43,  9.37iter/s]
Best score: 0.2860: : 456iter [00:43,  9.37iter/s]
Best score: 0.2860: : 457iter [00:43, 10.03iter/s]
Best score: 0.2860: : 457iter [00:43, 10.03iter/s]
Best score: 0.2860: : 458iter [00:43, 10.03iter/s]
Best score: 0.2860: : 459iter [00:43, 10.57iter/s]
Best score: 0.2860: : 459iter [00:43, 10.57iter/s]
Best score: 0.2860: : 460iter [00:43, 10.57iter/s]
Best score: 0.2860: : 461iter [00:43, 10.80iter/s]
Best score: 0.2860: : 461iter [00:43, 10.80iter/s]
Best score: 0.2860: : 462iter [00:43, 10.80iter/s]
Best score: 0.2860: : 463iter [00:43, 11.15iter/s]
Best score: 0.2860: : 463iter [00:43, 11.15iter/s]
Best score: 0.2860: : 464iter [00:43, 11.15iter/s]
Best score: 0.2860: : 465iter [00:43, 11.39iter/s]
Best score: 0.2860: : 465iter [00:44, 11.39iter/s]
Best score: 0.2860: : 466iter [00:44, 11.39iter/s]
Best score: 0.2860: : 467iter [00:44, 11.59iter/s]
Best score: 0.2860: : 467iter [00:44, 11.59iter/s]
Best score: 0.2860: : 468iter [00:44, 11.59iter/s]
Best score: 0.2860: : 469iter [00:44, 11.71iter/s]
Best score: 0.2860: : 469iter [00:44, 11.71iter/s]
Best score: 0.2860: : 470iter [00:44, 11.71iter/s]
Best score: 0.2860: : 471iter [00:44, 11.61iter/s]
Best score: 0.2860: : 471iter [00:44, 11.61iter/s]
Best score: 0.2860: : 472iter [00:44, 11.61iter/s]
Best score: 0.2860: : 473iter [00:44, 11.73iter/s]
Best score: 0.2860: : 473iter [00:44, 11.73iter/s]
Best score: 0.2860: : 474iter [00:44, 11.73iter/s]
Best score: 0.2860: : 475iter [00:44, 11.77iter/s]
Best score: 0.2860: : 475iter [00:44, 11.77iter/s]
Best score: 0.2860: : 476iter [00:44, 11.77iter/s]
Best score: 0.2860: : 477iter [00:44, 11.85iter/s]
Best score: 0.2860: : 477iter [00:45, 11.85iter/s]
Best score: 0.2860: : 478iter [00:45, 11.85iter/s]
Best score: 0.2860: : 479iter [00:45, 11.87iter/s]
Best score: 0.2839: : 479iter [00:45, 11.87iter/s]
Best score: 0.2839: : 480iter [00:45, 11.87iter/s]
Best score: 0.2839: : 481iter [00:45, 11.70iter/s]
Best score: 0.2839: : 481iter [00:45, 11.70iter/s]
Best score: 0.2839: : 482iter [00:45, 11.70iter/s]
Best score: 0.2839: : 483iter [00:45, 11.79iter/s]
Best score: 0.2839: : 483iter [00:45, 11.79iter/s]
Best score: 0.2839: : 484iter [00:45, 11.79iter/s]
Best score: 0.2839: : 485iter [00:45, 11.87iter/s]
Best score: 0.2839: : 485iter [00:45, 11.87iter/s]
Best score: 0.2839: : 486iter [00:45, 11.87iter/s]
Best score: 0.2839: : 487iter [00:45, 11.87iter/s]
Best score: 0.2839: : 487iter [00:45, 11.87iter/s]
Best score: 0.2839: : 488iter [00:45, 11.87iter/s]
Best score: 0.2839: : 489iter [00:45, 11.93iter/s]
Best score: 0.2828: : 489iter [00:46, 11.93iter/s]
Best score: 0.2828: : 490iter [00:46, 11.93iter/s]
Best score: 0.2828: : 491iter [00:46, 11.76iter/s]
Best score: 0.2828: : 491iter [00:46, 11.76iter/s]
Best score: 0.2828: : 492iter [00:46, 11.76iter/s]
Best score: 0.2828: : 493iter [00:46, 11.84iter/s]
Best score: 0.2828: : 493iter [00:46, 11.84iter/s]
Best score: 0.2828: : 494iter [00:46, 11.84iter/s]
Best score: 0.2828: : 495iter [00:46, 11.89iter/s]
Best score: 0.2828: : 495iter [00:46, 11.89iter/s]
Best score: 0.2828: : 496iter [00:46, 11.89iter/s]
Best score: 0.2828: : 497iter [00:46, 11.86iter/s]
Best score: 0.2828: : 497iter [00:46, 11.86iter/s]
Best score: 0.2828: : 498iter [00:46, 11.86iter/s]
Best score: 0.2828: : 499iter [00:46, 11.90iter/s]
[ITER 500] Best: 0.2679
[PARAMS] Current best parameters:
  fx: 542.8848
  fy: 543.0286
  px: 904.6446
  py: 918.8843
  k1: -0.01387855
  k2: -0.00311324
  k3: 0.00684912
  k4: -0.00277716
  p1: -0.02002796
  p2: -0.01666325
  p3: 0.01248785
  p4: 0.02930428
  s1: 0.0027
  s2: -0.0305
  s3: -0.0020
  s4: -0.0293
  tilt_x: -0.0142
  tilt_y: -0.0203
  scale: 2.9574
  rotation: -1.1752

Best score: 0.2679: : 499iter [00:46, 11.90iter/s]
Best score: 0.2679: : 500iter [00:47, 11.90iter/s]
Best score: 0.2679: : 501iter [00:47,  7.64iter/s]
Best score: 0.2679: : 501iter [00:47,  7.64iter/s]
Best score: 0.2679: : 502iter [00:47,  7.64iter/s]
Best score: 0.2679: : 503iter [00:47,  8.56iter/s]
Best score: 0.2679: : 503iter [00:47,  8.56iter/s]
Best score: 0.2679: : 504iter [00:47,  8.56iter/s]
Best score: 0.2679: : 505iter [00:47,  9.33iter/s]
Best score: 0.2679: : 505iter [00:47,  9.33iter/s]
Best score: 0.2679: : 506iter [00:47,  9.33iter/s]
Best score: 0.2679: : 507iter [00:47,  9.97iter/s]
Best score: 0.2679: : 507iter [00:47,  9.97iter/s]
Best score: 0.2679: : 508iter [00:47,  9.97iter/s]
Best score: 0.2679: : 509iter [00:47, 10.52iter/s]
Best score: 0.2641: : 509iter [00:48, 10.52iter/s]
Best score: 0.2641: : 510iter [00:48, 10.52iter/s]
Best score: 0.2641: : 511iter [00:48, 10.77iter/s]
Best score: 0.2641: : 511iter [00:48, 10.77iter/s]
Best score: 0.2641: : 512iter [00:48, 10.77iter/s]
Best score: 0.2641: : 513iter [00:48, 11.11iter/s]
Best score: 0.2641: : 513iter [00:48, 11.11iter/s]
Best score: 0.2641: : 514iter [00:48, 11.11iter/s]
Best score: 0.2641: : 515iter [00:48, 11.39iter/s]
Best score: 0.2641: : 515iter [00:48, 11.39iter/s]
Best score: 0.2641: : 516iter [00:48, 11.39iter/s]
Best score: 0.2641: : 517iter [00:48, 11.54iter/s]
Best score: 0.2641: : 517iter [00:48, 11.54iter/s]
Best score: 0.2641: : 518iter [00:48, 11.54iter/s]
Best score: 0.2641: : 519iter [00:48, 11.62iter/s]
Best score: 0.2509: : 519iter [00:48, 11.62iter/s]
Best score: 0.2509: : 520iter [00:49, 11.62iter/s]
Best score: 0.2509: : 521iter [00:49, 11.52iter/s]
Best score: 0.2509: : 521iter [00:49, 11.52iter/s]
Best score: 0.2509: : 522iter [00:49, 11.52iter/s]
Best score: 0.2509: : 523iter [00:49, 11.67iter/s]
Best score: 0.2509: : 523iter [00:49, 11.67iter/s]
Best score: 0.2509: : 524iter [00:49, 11.67iter/s]
Best score: 0.2509: : 525iter [00:49, 11.70iter/s]
Best score: 0.2509: : 525iter [00:49, 11.70iter/s]
Best score: 0.2509: : 526iter [00:49, 11.70iter/s]
Best score: 0.2509: : 527iter [00:49, 11.80iter/s]
Best score: 0.2509: : 527iter [00:49, 11.80iter/s]
Best score: 0.2509: : 528iter [00:49, 11.80iter/s]
Best score: 0.2509: : 529iter [00:49, 11.85iter/s]
Best score: 0.2509: : 529iter [00:49, 11.85iter/s]
Best score: 0.2509: : 530iter [00:49, 11.85iter/s]
Best score: 0.2509: : 531iter [00:49, 11.66iter/s]
Best score: 0.2509: : 531iter [00:49, 11.66iter/s]
Best score: 0.2509: : 532iter [00:50, 11.66iter/s]
Best score: 0.2509: : 533iter [00:50, 11.69iter/s]
Best score: 0.2509: : 533iter [00:50, 11.69iter/s]
Best score: 0.2509: : 534iter [00:50, 11.69iter/s]
Best score: 0.2509: : 535iter [00:50, 11.67iter/s]
Best score: 0.2509: : 535iter [00:50, 11.67iter/s]
Best score: 0.2509: : 536iter [00:50, 11.67iter/s]
Best score: 0.2509: : 537iter [00:50, 11.74iter/s]
Best score: 0.2509: : 537iter [00:50, 11.74iter/s]
Best score: 0.2509: : 538iter [00:50, 11.74iter/s]
Best score: 0.2509: : 539iter [00:50, 11.81iter/s]
Best score: 0.2414: : 539iter [00:50, 11.81iter/s]
Best score: 0.2414: : 540iter [00:50, 11.81iter/s]
Best score: 0.2414: : 541iter [00:50, 11.66iter/s]
Best score: 0.2414: : 541iter [00:50, 11.66iter/s]
Best score: 0.2414: : 542iter [00:50, 11.66iter/s]
Best score: 0.2414: : 543iter [00:50, 11.73iter/s]
Best score: 0.2414: : 543iter [00:50, 11.73iter/s]
Best score: 0.2414: : 544iter [00:51, 11.73iter/s]
Best score: 0.2414: : 545iter [00:51, 11.80iter/s]
Best score: 0.2414: : 545iter [00:51, 11.80iter/s]
Best score: 0.2414: : 546iter [00:51, 11.80iter/s]
Best score: 0.2414: : 547iter [00:51, 11.87iter/s]
Best score: 0.2414: : 547iter [00:51, 11.87iter/s]
Best score: 0.2414: : 548iter [00:51, 11.87iter/s]
Best score: 0.2414: : 549iter [00:51, 11.92iter/s]
[ITER 550] Best: 0.2414
[PARAMS] Current best parameters:
  fx: 550.5470
  fy: 550.8083
  px: 907.7738
  py: 920.4662
  k1: -0.02830917
  k2: 0.01079516
  k3: -0.00278674
  k4: -0.00030372
  p1: -0.01551090
  p2: -0.01204822
  p3: 0.00650004
  p4: 0.03292444
  s1: 0.0057
  s2: -0.0327
  s3: 0.0001
  s4: -0.0323
  tilt_x: -0.0151
  tilt_y: -0.0252
  scale: 2.9575
  rotation: -1.1691

Best score: 0.2414: : 549iter [00:51, 11.92iter/s]
Best score: 0.2414: : 550iter [00:51, 11.92iter/s]
Best score: 0.2414: : 551iter [00:51,  7.64iter/s]
Best score: 0.2414: : 551iter [00:51,  7.64iter/s]
Best score: 0.2414: : 552iter [00:52,  7.64iter/s]
Best score: 0.2414: : 553iter [00:52,  8.57iter/s]
Best score: 0.2414: : 553iter [00:52,  8.57iter/s]
Best score: 0.2414: : 554iter [00:52,  8.57iter/s]
Best score: 0.2414: : 555iter [00:52,  9.38iter/s]
Best score: 0.2414: : 555iter [00:52,  9.38iter/s]
Best score: 0.2414: : 556iter [00:52,  9.38iter/s]
Best score: 0.2414: : 557iter [00:52, 10.04iter/s]
Best score: 0.2414: : 557iter [00:52, 10.04iter/s]
Best score: 0.2414: : 558iter [00:52, 10.04iter/s]
Best score: 0.2414: : 559iter [00:52, 10.55iter/s]
Best score: 0.2414: : 559iter [00:52, 10.55iter/s]
Best score: 0.2414: : 560iter [00:52, 10.55iter/s]
Best score: 0.2414: : 561iter [00:52, 10.78iter/s]
Best score: 0.2414: : 561iter [00:52, 10.78iter/s]
Best score: 0.2414: : 562iter [00:52, 10.78iter/s]
Best score: 0.2414: : 563iter [00:52, 11.12iter/s]
Best score: 0.2414: : 563iter [00:52, 11.12iter/s]
Best score: 0.2414: : 564iter [00:53, 11.12iter/s]
Best score: 0.2414: : 565iter [00:53, 11.37iter/s]
Best score: 0.2414: : 565iter [00:53, 11.37iter/s]
Best score: 0.2414: : 566iter [00:53, 11.37iter/s]
Best score: 0.2414: : 567iter [00:53, 11.57iter/s]
Best score: 0.2414: : 567iter [00:53, 11.57iter/s]
Best score: 0.2414: : 568iter [00:53, 11.57iter/s]
Best score: 0.2414: : 569iter [00:53, 11.72iter/s]
Best score: 0.2414: : 569iter [00:53, 11.72iter/s]
Best score: 0.2414: : 570iter [00:53, 11.72iter/s]
Best score: 0.2414: : 571iter [00:53, 11.61iter/s]
Best score: 0.2414: : 571iter [00:53, 11.61iter/s]
Best score: 0.2414: : 572iter [00:53, 11.61iter/s]
Best score: 0.2414: : 573iter [00:53, 11.71iter/s]
Best score: 0.2414: : 573iter [00:53, 11.71iter/s]
Best score: 0.2414: : 574iter [00:53, 11.71iter/s]
Best score: 0.2414: : 575iter [00:53, 11.81iter/s]
Best score: 0.2414: : 575iter [00:53, 11.81iter/s]
Best score: 0.2414: : 576iter [00:54, 11.81iter/s]
Best score: 0.2414: : 577iter [00:54, 11.89iter/s]
Best score: 0.2414: : 577iter [00:54, 11.89iter/s]
Best score: 0.2414: : 578iter [00:54, 11.89iter/s]
Best score: 0.2414: : 579iter [00:54, 11.93iter/s]
Best score: 0.2414: : 579iter [00:54, 11.93iter/s]
Best score: 0.2414: : 580iter [00:54, 11.93iter/s]
Best score: 0.2414: : 581iter [00:54, 11.75iter/s]
Best score: 0.2414: : 581iter [00:54, 11.75iter/s]
Best score: 0.2414: : 582iter [00:54, 11.75iter/s]
Best score: 0.2414: : 583iter [00:54, 11.80iter/s]
Best score: 0.2414: : 583iter [00:54, 11.80iter/s]
Best score: 0.2414: : 584iter [00:54, 11.80iter/s]
Best score: 0.2414: : 585iter [00:54, 11.87iter/s]
Best score: 0.2414: : 585iter [00:54, 11.87iter/s]
Best score: 0.2414: : 586iter [00:54, 11.87iter/s]
Best score: 0.2414: : 587iter [00:54, 11.90iter/s]
Best score: 0.2414: : 587iter [00:54, 11.90iter/s]
Best score: 0.2414: : 588iter [00:55, 11.90iter/s]
Best score: 0.2414: : 589iter [00:55, 11.94iter/s]
Best score: 0.2414: : 589iter [00:55, 11.94iter/s]
Best score: 0.2414: : 590iter [00:55, 11.94iter/s]
Best score: 0.2414: : 591iter [00:55, 11.74iter/s]
Best score: 0.2414: : 591iter [00:55, 11.74iter/s]
Best score: 0.2414: : 592iter [00:55, 11.74iter/s]
Best score: 0.2414: : 593iter [00:55, 11.83iter/s]
Best score: 0.2414: : 593iter [00:55, 11.83iter/s]
Best score: 0.2414: : 594iter [00:55, 11.83iter/s]
Best score: 0.2414: : 595iter [00:55, 11.90iter/s]
Best score: 0.2414: : 595iter [00:55, 11.90iter/s]
Best score: 0.2414: : 596iter [00:55, 11.90iter/s]
Best score: 0.2414: : 597iter [00:55, 11.94iter/s]
Best score: 0.2414: : 597iter [00:55, 11.94iter/s]
Best score: 0.2414: : 598iter [00:55, 11.94iter/s]
Best score: 0.2414: : 599iter [00:55, 11.98iter/s]
[ITER 600] Best: 0.2414
[PARAMS] Current best parameters:
  fx: 550.5470
  fy: 550.8083
  px: 907.7738
  py: 920.4662
  k1: -0.02830917
  k2: 0.01079516
  k3: -0.00278674
  k4: -0.00030372
  p1: -0.01551090
  p2: -0.01204822
  p3: 0.00650004
  p4: 0.03292444
  s1: 0.0057
  s2: -0.0327
  s3: 0.0001
  s4: -0.0323
  tilt_x: -0.0151
  tilt_y: -0.0252
  scale: 2.9575
  rotation: -1.1691

Best score: 0.2414: : 599iter [00:55, 11.98iter/s]
Best score: 0.2414: : 600iter [00:56, 11.98iter/s]
Best score: 0.2414: : 601iter [00:56,  7.63iter/s]
Best score: 0.2414: : 601iter [00:56,  7.63iter/s]
Best score: 0.2414: : 602iter [00:56,  7.63iter/s]
Best score: 0.2414: : 603iter [00:56,  8.57iter/s]
Best score: 0.2414: : 603iter [00:56,  8.57iter/s]
Best score: 0.2414: : 604iter [00:56,  8.57iter/s]
Best score: 0.2414: : 605iter [00:56,  9.39iter/s]
Best score: 0.2414: : 605iter [00:56,  9.39iter/s]
Best score: 0.2414: : 606iter [00:56,  9.39iter/s]
Best score: 0.2414: : 607iter [00:56, 10.06iter/s]
Best score: 0.2414: : 607iter [00:56, 10.06iter/s]
Best score: 0.2414: : 608iter [00:57, 10.06iter/s]
Best score: 0.2414: : 609iter [00:57, 10.54iter/s]
Best score: 0.2372: : 609iter [00:57, 10.54iter/s]
Best score: 0.2372: : 610iter [00:57, 10.54iter/s]
Best score: 0.2372: : 611iter [00:57, 10.75iter/s]
Best score: 0.2372: : 611iter [00:57, 10.75iter/s]
Best score: 0.2372: : 612iter [00:57, 10.75iter/s]
Best score: 0.2372: : 613iter [00:57, 11.10iter/s]
Best score: 0.2372: : 613iter [00:57, 11.10iter/s]
Best score: 0.2372: : 614iter [00:57, 11.10iter/s]
Best score: 0.2372: : 615iter [00:57, 11.34iter/s]
Best score: 0.2372: : 615iter [00:57, 11.34iter/s]
Best score: 0.2372: : 616iter [00:57, 11.34iter/s]
Best score: 0.2372: : 617iter [00:57, 11.54iter/s]
Best score: 0.2372: : 617iter [00:57, 11.54iter/s]
Best score: 0.2372: : 618iter [00:57, 11.54iter/s]
Best score: 0.2372: : 619iter [00:57, 11.68iter/s]
Best score: 0.2334: : 619iter [00:57, 11.68iter/s]
Best score: 0.2334: : 620iter [00:58, 11.68iter/s]
Best score: 0.2334: : 621iter [00:58, 11.58iter/s]
Best score: 0.2334: : 621iter [00:58, 11.58iter/s]
Best score: 0.2334: : 622iter [00:58, 11.58iter/s]
Best score: 0.2334: : 623iter [00:58, 11.72iter/s]
Best score: 0.2334: : 623iter [00:58, 11.72iter/s]
Best score: 0.2334: : 624iter [00:58, 11.72iter/s]
Best score: 0.2334: : 625iter [00:58, 11.76iter/s]
Best score: 0.2334: : 625iter [00:58, 11.76iter/s]
Best score: 0.2334: : 626iter [00:58, 11.76iter/s]
Best score: 0.2334: : 627iter [00:58, 11.86iter/s]
Best score: 0.2334: : 627iter [00:58, 11.86iter/s]
Best score: 0.2334: : 628iter [00:58, 11.86iter/s]
Best score: 0.2334: : 629iter [00:58, 11.93iter/s]
Best score: 0.2322: : 629iter [00:58, 11.93iter/s]
Best score: 0.2322: : 630iter [00:58, 11.93iter/s]
Best score: 0.2322: : 631iter [00:58, 11.71iter/s]
Best score: 0.2322: : 631iter [00:58, 11.71iter/s]
Best score: 0.2322: : 632iter [00:59, 11.71iter/s]
Best score: 0.2322: : 633iter [00:59, 11.81iter/s]
Best score: 0.2322: : 633iter [00:59, 11.81iter/s]
Best score: 0.2322: : 634iter [00:59, 11.81iter/s]
Best score: 0.2322: : 635iter [00:59, 11.86iter/s]
Best score: 0.2322: : 635iter [00:59, 11.86iter/s]
Best score: 0.2322: : 636iter [00:59, 11.86iter/s]
Best score: 0.2322: : 637iter [00:59, 11.91iter/s]
Best score: 0.2322: : 637iter [00:59, 11.91iter/s]
Best score: 0.2322: : 638iter [00:59, 11.91iter/s]
Best score: 0.2322: : 639iter [00:59, 11.95iter/s]
Best score: 0.2308: : 639iter [00:59, 11.95iter/s]
Best score: 0.2308: : 640iter [00:59, 11.95iter/s]
Best score: 0.2308: : 641iter [00:59, 11.78iter/s]
Best score: 0.2308: : 641iter [00:59, 11.78iter/s]
Best score: 0.2308: : 642iter [00:59, 11.78iter/s]
Best score: 0.2308: : 643iter [00:59, 11.79iter/s]
Best score: 0.2308: : 643iter [01:00, 11.79iter/s]
Best score: 0.2308: : 644iter [01:00, 11.79iter/s]
Best score: 0.2308: : 645iter [01:00, 11.85iter/s]
Best score: 0.2308: : 645iter [01:00, 11.85iter/s]
Best score: 0.2308: : 646iter [01:00, 11.85iter/s]
Best score: 0.2308: : 647iter [01:00, 11.87iter/s]
Best score: 0.2308: : 647iter [01:00, 11.87iter/s]
Best score: 0.2308: : 648iter [01:00, 11.87iter/s]
Best score: 0.2308: : 649iter [01:00, 11.92iter/s]
[ITER 650] Best: 0.2308
[PARAMS] Current best parameters:
  fx: 556.9001
  fy: 557.0548
  px: 905.8557
  py: 923.7439
  k1: -0.02473720
  k2: -0.00697704
  k3: 0.00916181
  k4: -0.00292019
  p1: -0.01653988
  p2: -0.01388939
  p3: 0.00128819
  p4: 0.03538572
  s1: 0.0125
  s2: -0.0370
  s3: 0.0097
  s4: -0.0354
  tilt_x: 0.0020
  tilt_y: -0.0188
  scale: 2.9473
  rotation: -1.1837

Best score: 0.2308: : 649iter [01:00, 11.92iter/s]
Best score: 0.2308: : 650iter [01:00, 11.92iter/s]
Best score: 0.2308: : 651iter [01:00,  7.63iter/s]
Best score: 0.2308: : 651iter [01:00,  7.63iter/s]
Best score: 0.2308: : 652iter [01:01,  7.63iter/s]
Best score: 0.2308: : 653iter [01:01,  8.58iter/s]
Best score: 0.2308: : 653iter [01:01,  8.58iter/s]
Best score: 0.2308: : 654iter [01:01,  8.58iter/s]
Best score: 0.2308: : 655iter [01:01,  9.39iter/s]
Best score: 0.2308: : 655iter [01:01,  9.39iter/s]
Best score: 0.2308: : 656iter [01:01,  9.39iter/s]
Best score: 0.2308: : 657iter [01:01, 10.05iter/s]
Best score: 0.2308: : 657iter [01:01, 10.05iter/s]
Best score: 0.2308: : 658iter [01:01, 10.05iter/s]
Best score: 0.2308: : 659iter [01:01, 10.57iter/s]
Best score: 0.2304: : 659iter [01:01, 10.57iter/s]
Best score: 0.2304: : 660iter [01:01, 10.57iter/s]
Best score: 0.2304: : 661iter [01:01, 10.80iter/s]
Best score: 0.2304: : 661iter [01:01, 10.80iter/s]
Best score: 0.2304: : 662iter [01:01, 10.80iter/s]
Best score: 0.2304: : 663iter [01:01, 11.15iter/s]
Best score: 0.2304: : 663iter [01:01, 11.15iter/s]
Best score: 0.2304: : 664iter [01:02, 11.15iter/s]
Best score: 0.2304: : 665iter [01:02, 11.40iter/s]
Best score: 0.2304: : 665iter [01:02, 11.40iter/s]
Best score: 0.2304: : 666iter [01:02, 11.40iter/s]
Best score: 0.2304: : 667iter [01:02, 11.58iter/s]
Best score: 0.2304: : 667iter [01:02, 11.58iter/s]
Best score: 0.2304: : 668iter [01:02, 11.58iter/s]
Best score: 0.2304: : 669iter [01:02, 11.72iter/s]
Best score: 0.2304: : 669iter [01:02, 11.72iter/s]
Best score: 0.2304: : 670iter [01:02, 11.72iter/s]
Best score: 0.2304: : 671iter [01:02, 11.61iter/s]
Best score: 0.2304: : 671iter [01:02, 11.61iter/s]
Best score: 0.2304: : 672iter [01:02, 11.61iter/s]
Best score: 0.2304: : 673iter [01:02, 11.74iter/s]
Best score: 0.2304: : 673iter [01:02, 11.74iter/s]
Best score: 0.2304: : 674iter [01:02, 11.74iter/s]
Best score: 0.2304: : 675iter [01:02, 11.83iter/s]
Best score: 0.2304: : 675iter [01:02, 11.83iter/s]
Best score: 0.2304: : 676iter [01:03, 11.83iter/s]
Best score: 0.2304: : 677iter [01:03, 11.87iter/s]
Best score: 0.2304: : 677iter [01:03, 11.87iter/s]
Best score: 0.2304: : 678iter [01:03, 11.87iter/s]
Best score: 0.2304: : 679iter [01:03, 11.91iter/s]
Best score: 0.2285: : 679iter [01:03, 11.91iter/s]
Best score: 0.2285: : 680iter [01:03, 11.91iter/s]
Best score: 0.2285: : 681iter [01:03, 11.74iter/s]
Best score: 0.2285: : 681iter [01:03, 11.74iter/s]
Best score: 0.2285: : 682iter [01:03, 11.74iter/s]
Best score: 0.2285: : 683iter [01:03, 11.81iter/s]
Best score: 0.2285: : 683iter [01:03, 11.81iter/s]
Best score: 0.2285: : 684iter [01:03, 11.81iter/s]
Best score: 0.2285: : 685iter [01:03, 11.87iter/s]
Best score: 0.2285: : 685iter [01:03, 11.87iter/s]
Best score: 0.2285: : 686iter [01:03, 11.87iter/s]
Best score: 0.2285: : 687iter [01:03, 11.91iter/s]
Best score: 0.2285: : 687iter [01:04, 11.91iter/s]
Best score: 0.2285: : 688iter [01:04, 11.91iter/s]
Best score: 0.2285: : 689iter [01:04, 11.95iter/s]
Best score: 0.2281: : 689iter [01:04, 11.95iter/s]
Best score: 0.2281: : 690iter [01:04, 11.95iter/s]
Best score: 0.2281: : 691iter [01:04, 11.76iter/s]
Best score: 0.2281: : 691iter [01:04, 11.76iter/s]
Best score: 0.2281: : 692iter [01:04, 11.76iter/s]
Best score: 0.2281: : 693iter [01:04, 11.82iter/s]
Best score: 0.2281: : 693iter [01:04, 11.82iter/s]
Best score: 0.2281: : 694iter [01:04, 11.82iter/s]
Best score: 0.2281: : 695iter [01:04, 11.87iter/s]
Best score: 0.2281: : 695iter [01:04, 11.87iter/s]
Best score: 0.2281: : 696iter [01:04, 11.87iter/s]
Best score: 0.2281: : 697iter [01:04, 11.93iter/s]
Best score: 0.2281: : 697iter [01:04, 11.93iter/s]
Best score: 0.2281: : 698iter [01:04, 11.93iter/s]
Best score: 0.2281: : 699iter [01:04, 11.97iter/s]
[ITER 700] Best: 0.2281
[PARAMS] Current best parameters:
  fx: 554.1561
  fy: 554.3357
  px: 905.4945
  py: 923.1209
  k1: -0.02313060
  k2: -0.00658638
  k3: 0.00976075
  k4: -0.00329449
  p1: -0.01651798
  p2: -0.01487097
  p3: 0.00158115
  p4: 0.03480066
  s1: 0.0115
  s2: -0.0347
  s3: 0.0084
  s4: -0.0347
  tilt_x: -0.0003
  tilt_y: -0.0192
  scale: 2.9501
  rotation: -1.1781

Best score: 0.2281: : 699iter [01:05, 11.97iter/s]
Best score: 0.2281: : 700iter [01:05, 11.97iter/s]
Best score: 0.2281: : 701iter [01:05,  7.59iter/s]
Best score: 0.2281: : 701iter [01:05,  7.59iter/s]
Best score: 0.2281: : 702iter [01:05,  7.59iter/s]
Best score: 0.2281: : 703iter [01:05,  8.51iter/s]
Best score: 0.2281: : 703iter [01:05,  8.51iter/s]
Best score: 0.2281: : 704iter [01:05,  8.51iter/s]
Best score: 0.2281: : 705iter [01:05,  9.34iter/s]
Best score: 0.2281: : 705iter [01:05,  9.34iter/s]
Best score: 0.2281: : 706iter [01:05,  9.34iter/s]
Best score: 0.2281: : 707iter [01:05, 10.01iter/s]
Best score: 0.2281: : 707iter [01:06, 10.01iter/s]
Best score: 0.2281: : 708iter [01:06, 10.01iter/s]
Best score: 0.2281: : 709iter [01:06, 10.55iter/s]
Best score: 0.2280: : 709iter [01:06, 10.55iter/s]
Best score: 0.2280: : 710iter [01:06, 10.55iter/s]
Best score: 0.2280: : 711iter [01:06, 10.79iter/s]
Best score: 0.2280: : 711iter [01:06, 10.79iter/s]
Best score: 0.2280: : 712iter [01:06, 10.79iter/s]
Best score: 0.2280: : 713iter [01:06, 11.13iter/s]
Best score: 0.2280: : 713iter [01:06, 11.13iter/s]
Best score: 0.2280: : 714iter [01:06, 11.13iter/s]
Best score: 0.2280: : 715iter [01:06, 11.39iter/s]
Best score: 0.2280: : 715iter [01:06, 11.39iter/s]
Best score: 0.2280: : 716iter [01:06, 11.39iter/s]
Best score: 0.2280: : 717iter [01:06, 11.53iter/s]
Best score: 0.2280: : 717iter [01:06, 11.53iter/s]
Best score: 0.2280: : 718iter [01:06, 11.53iter/s]
Best score: 0.2280: : 719iter [01:06, 11.62iter/s]
Best score: 0.2271: : 719iter [01:07, 11.62iter/s]
Best score: 0.2271: : 720iter [01:07, 11.62iter/s]
Best score: 0.2271: : 721iter [01:07, 11.52iter/s]
Best score: 0.2271: : 721iter [01:07, 11.52iter/s]
Best score: 0.2271: : 722iter [01:07, 11.52iter/s]
Best score: 0.2271: : 723iter [01:07, 11.56iter/s]
Best score: 0.2271: : 723iter [01:07, 11.56iter/s]
Best score: 0.2271: : 724iter [01:07, 11.56iter/s]
Best score: 0.2271: : 725iter [01:07, 11.65iter/s]
Best score: 0.2271: : 725iter [01:07, 11.65iter/s]
Best score: 0.2271: : 726iter [01:07, 11.65iter/s]
Best score: 0.2271: : 727iter [01:07, 11.75iter/s]
Best score: 0.2271: : 727iter [01:07, 11.75iter/s]
Best score: 0.2271: : 728iter [01:07, 11.75iter/s]
Best score: 0.2271: : 729iter [01:07, 11.83iter/s]
Best score: 0.2271: : 729iter [01:07, 11.83iter/s]
Best score: 0.2271: : 730iter [01:07, 11.83iter/s]
Best score: 0.2271: : 731iter [01:07, 11.68iter/s]
Best score: 0.2271: : 731iter [01:08, 11.68iter/s]
Best score: 0.2271: : 732iter [01:08, 11.68iter/s]
Best score: 0.2271: : 733iter [01:08, 11.79iter/s]
Best score: 0.2271: : 733iter [01:08, 11.79iter/s]
Best score: 0.2271: : 734iter [01:08, 11.79iter/s]
Best score: 0.2271: : 735iter [01:08, 11.87iter/s]
Best score: 0.2271: : 735iter [01:08, 11.87iter/s]
Best score: 0.2271: : 736iter [01:08, 11.87iter/s]
Best score: 0.2271: : 737iter [01:08, 11.93iter/s]
Best score: 0.2271: : 737iter [01:08, 11.93iter/s]
Best score: 0.2271: : 738iter [01:08, 11.93iter/s]
Best score: 0.2271: : 739iter [01:08, 11.97iter/s]
Best score: 0.2271: : 739iter [01:08, 11.97iter/s]
Best score: 0.2271: : 740iter [01:08, 11.97iter/s]
Best score: 0.2271: : 741iter [01:08, 11.73iter/s]
Best score: 0.2271: : 741iter [01:08, 11.73iter/s]
Best score: 0.2271: : 742iter [01:08, 11.73iter/s]
Best score: 0.2271: : 743iter [01:08, 11.82iter/s]
Best score: 0.2271: : 743iter [01:09, 11.82iter/s]
Best score: 0.2271: : 744iter [01:09, 11.82iter/s]
Best score: 0.2271: : 745iter [01:09, 11.88iter/s]
Best score: 0.2271: : 745iter [01:09, 11.88iter/s]
Best score: 0.2271: : 746iter [01:09, 11.88iter/s]
Best score: 0.2271: : 747iter [01:09, 11.93iter/s]
Best score: 0.2271: : 747iter [01:09, 11.93iter/s]
Best score: 0.2271: : 748iter [01:09, 11.93iter/s]
Best score: 0.2271: : 749iter [01:09, 11.97iter/s]
[ITER 750] Best: 0.2262
[PARAMS] Current best parameters:
  fx: 556.9008
  fy: 557.0780
  px: 906.3911
  py: 923.7831
  k1: -0.02878471
  k2: -0.00198060
  k3: 0.00758040
  k4: -0.00293831
  p1: -0.01493252
  p2: -0.01374886
  p3: 0.00007498
  p4: 0.03450525
  s1: 0.0127
  s2: -0.0348
  s3: 0.0090
  s4: -0.0341
  tilt_x: -0.0007
  tilt_y: -0.0212
  scale: 2.9514
  rotation: -1.1717

Best score: 0.2262: : 749iter [01:09, 11.97iter/s]
Best score: 0.2262: : 750iter [01:09, 11.97iter/s]
Best score: 0.2262: : 751iter [01:09,  7.63iter/s]
Best score: 0.2262: : 751iter [01:10,  7.63iter/s]
Best score: 0.2262: : 752iter [01:10,  7.63iter/s]
Best score: 0.2262: : 753iter [01:10,  8.56iter/s]
Best score: 0.2262: : 753iter [01:10,  8.56iter/s]
Best score: 0.2262: : 754iter [01:10,  8.56iter/s]
Best score: 0.2262: : 755iter [01:10,  9.35iter/s]
Best score: 0.2262: : 755iter [01:10,  9.35iter/s]
Best score: 0.2262: : 756iter [01:10,  9.35iter/s]
Best score: 0.2262: : 757iter [01:10,  9.96iter/s]
Best score: 0.2262: : 757iter [01:10,  9.96iter/s]
Best score: 0.2262: : 758iter [01:10,  9.96iter/s]
Best score: 0.2262: : 759iter [01:10, 10.48iter/s]
Best score: 0.2259: : 759iter [01:10, 10.48iter/s]
Best score: 0.2259: : 760iter [01:10, 10.48iter/s]
Best score: 0.2259: : 761iter [01:10, 10.74iter/s]
Best score: 0.2259: : 761iter [01:10, 10.74iter/s]
Best score: 0.2259: : 762iter [01:10, 10.74iter/s]
Best score: 0.2259: : 763iter [01:10, 11.06iter/s]
Best score: 0.2259: : 763iter [01:11, 11.06iter/s]
Best score: 0.2259: : 764iter [01:11, 11.06iter/s]
Best score: 0.2259: : 765iter [01:11, 11.27iter/s]
Best score: 0.2259: : 765iter [01:11, 11.27iter/s]
Best score: 0.2259: : 766iter [01:11, 11.27iter/s]
Best score: 0.2259: : 767iter [01:11, 11.47iter/s]
Best score: 0.2259: : 767iter [01:11, 11.47iter/s]
Best score: 0.2259: : 768iter [01:11, 11.47iter/s]
Best score: 0.2259: : 769iter [01:11, 11.61iter/s]
Best score: 0.2255: : 769iter [01:11, 11.61iter/s]
Best score: 0.2255: : 770iter [01:11, 11.61iter/s]
Best score: 0.2255: : 771iter [01:11, 11.45iter/s]
Best score: 0.2255: : 771iter [01:11, 11.45iter/s]
Best score: 0.2255: : 772iter [01:11, 11.45iter/s]
Best score: 0.2255: : 773iter [01:11, 11.63iter/s]
Best score: 0.2255: : 773iter [01:11, 11.63iter/s]
Best score: 0.2255: : 774iter [01:11, 11.63iter/s]
Best score: 0.2255: : 775iter [01:11, 11.75iter/s]
Best score: 0.2255: : 775iter [01:12, 11.75iter/s]
Best score: 0.2255: : 776iter [01:12, 11.75iter/s]
Best score: 0.2255: : 777iter [01:12, 11.83iter/s]
Best score: 0.2255: : 777iter [01:12, 11.83iter/s]
Best score: 0.2255: : 778iter [01:12, 11.83iter/s]
Best score: 0.2255: : 779iter [01:12, 11.84iter/s]
Best score: 0.2249: : 779iter [01:12, 11.84iter/s]
Best score: 0.2249: : 780iter [01:12, 11.84iter/s]
Best score: 0.2249: : 781iter [01:12, 11.69iter/s]
Best score: 0.2249: : 781iter [01:12, 11.69iter/s]
Best score: 0.2249: : 782iter [01:12, 11.69iter/s]
Best score: 0.2249: : 783iter [01:12, 11.75iter/s]
Best score: 0.2249: : 783iter [01:12, 11.75iter/s]
Best score: 0.2249: : 784iter [01:12, 11.75iter/s]
Best score: 0.2249: : 785iter [01:12, 11.84iter/s]
Best score: 0.2249: : 785iter [01:12, 11.84iter/s]
Best score: 0.2249: : 786iter [01:12, 11.84iter/s]
Best score: 0.2249: : 787iter [01:12, 11.90iter/s]
Best score: 0.2249: : 787iter [01:13, 11.90iter/s]
Best score: 0.2249: : 788iter [01:13, 11.90iter/s]
Best score: 0.2249: : 789iter [01:13, 11.93iter/s]
Best score: 0.2243: : 789iter [01:13, 11.93iter/s]
Best score: 0.2243: : 790iter [01:13, 11.93iter/s]
Best score: 0.2243: : 791iter [01:13, 11.72iter/s]
Best score: 0.2243: : 791iter [01:13, 11.72iter/s]
Best score: 0.2243: : 792iter [01:13, 11.72iter/s]
Best score: 0.2243: : 793iter [01:13, 11.82iter/s]
Best score: 0.2243: : 793iter [01:13, 11.82iter/s]
Best score: 0.2243: : 794iter [01:13, 11.82iter/s]
Best score: 0.2243: : 795iter [01:13, 11.90iter/s]
Best score: 0.2243: : 795iter [01:13, 11.90iter/s]
Best score: 0.2243: : 796iter [01:13, 11.90iter/s]
Best score: 0.2243: : 797iter [01:13, 11.93iter/s]
Best score: 0.2243: : 797iter [01:13, 11.93iter/s]
Best score: 0.2243: : 798iter [01:14, 11.93iter/s]
Best score: 0.2243: : 799iter [01:14, 11.97iter/s]
[ITER 800] Best: 0.2227
[PARAMS] Current best parameters:
  fx: 562.6882
  fy: 562.8842
  px: 907.5150
  py: 924.9158
  k1: -0.03017420
  k2: -0.00901690
  k3: 0.01192519
  k4: -0.00369091
  p1: -0.01211488
  p2: -0.00978480
  p3: -0.00249649
  p4: 0.03202748
  s1: 0.0130
  s2: -0.0329
  s3: 0.0106
  s4: -0.0323
  tilt_x: -0.0010
  tilt_y: -0.0187
  scale: 2.9452
  rotation: -1.1761

Best score: 0.2227: : 799iter [01:14, 11.97iter/s]
Best score: 0.2227: : 800iter [01:14, 11.97iter/s]
Best score: 0.2227: : 801iter [01:14,  7.65iter/s]
Best score: 0.2227: : 801iter [01:14,  7.65iter/s]
Best score: 0.2227: : 802iter [01:14,  7.65iter/s]
Best score: 0.2227: : 803iter [01:14,  8.60iter/s]
Best score: 0.2227: : 803iter [01:14,  8.60iter/s]
Best score: 0.2227: : 804iter [01:14,  8.60iter/s]
Best score: 0.2227: : 805iter [01:14,  9.38iter/s]
Best score: 0.2227: : 805iter [01:14,  9.38iter/s]
Best score: 0.2227: : 806iter [01:14,  9.38iter/s]
Best score: 0.2227: : 807iter [01:14, 10.01iter/s]
Best score: 0.2227: : 807iter [01:15, 10.01iter/s]
Best score: 0.2227: : 808iter [01:15, 10.01iter/s]
Best score: 0.2227: : 809iter [01:15, 10.52iter/s]
Best score: 0.2226: : 809iter [01:15, 10.52iter/s]
Best score: 0.2226: : 810iter [01:15, 10.52iter/s]
Best score: 0.2226: : 811iter [01:15, 10.75iter/s]
Best score: 0.2226: : 811iter [01:15, 10.75iter/s]
Best score: 0.2226: : 812iter [01:15, 10.75iter/s]
Best score: 0.2226: : 813iter [01:15, 11.07iter/s]
Best score: 0.2226: : 813iter [01:15, 11.07iter/s]
Best score: 0.2226: : 814iter [01:15, 11.07iter/s]
Best score: 0.2226: : 815iter [01:15, 11.35iter/s]
Best score: 0.2226: : 815iter [01:15, 11.35iter/s]
Best score: 0.2226: : 816iter [01:15, 11.35iter/s]
Best score: 0.2226: : 817iter [01:15, 11.55iter/s]
Best score: 0.2226: : 817iter [01:15, 11.55iter/s]
Best score: 0.2226: : 818iter [01:15, 11.55iter/s]
Best score: 0.2226: : 819iter [01:15, 11.69iter/s]
Best score: 0.2222: : 819iter [01:16, 11.69iter/s]
Best score: 0.2222: : 820iter [01:16, 11.69iter/s]
Best score: 0.2222: : 821iter [01:16, 11.60iter/s]
Best score: 0.2222: : 821iter [01:16, 11.60iter/s]
Best score: 0.2222: : 822iter [01:16, 11.60iter/s]
Best score: 0.2222: : 823iter [01:16, 11.70iter/s]
Best score: 0.2222: : 823iter [01:16, 11.70iter/s]
Best score: 0.2222: : 824iter [01:16, 11.70iter/s]
Best score: 0.2222: : 825iter [01:16, 11.82iter/s]
Best score: 0.2222: : 825iter [01:16, 11.82iter/s]
Best score: 0.2222: : 826iter [01:16, 11.82iter/s]
Best score: 0.2222: : 827iter [01:16, 11.88iter/s]
Best score: 0.2222: : 827iter [01:16, 11.88iter/s]
Best score: 0.2222: : 828iter [01:16, 11.88iter/s]
Best score: 0.2222: : 829iter [01:16, 11.92iter/s]
Best score: 0.2217: : 829iter [01:16, 11.92iter/s]
Best score: 0.2217: : 830iter [01:17, 11.92iter/s]
Best score: 0.2217: : 831iter [01:17, 11.76iter/s]
Best score: 0.2217: : 831iter [01:17, 11.76iter/s]
Best score: 0.2217: : 832iter [01:17, 11.76iter/s]
Best score: 0.2217: : 833iter [01:17, 11.84iter/s]
Best score: 0.2217: : 833iter [01:17, 11.84iter/s]
Best score: 0.2217: : 834iter [01:17, 11.84iter/s]
Best score: 0.2217: : 835iter [01:17, 11.81iter/s]
Best score: 0.2217: : 835iter [01:17, 11.81iter/s]
Best score: 0.2217: : 836iter [01:17, 11.81iter/s]
Best score: 0.2217: : 837iter [01:17, 11.89iter/s]
Best score: 0.2217: : 837iter [01:17, 11.89iter/s]
Best score: 0.2217: : 838iter [01:17, 11.89iter/s]
Best score: 0.2217: : 839iter [01:17, 11.90iter/s]
Best score: 0.2202: : 839iter [01:17, 11.90iter/s]
Best score: 0.2202: : 840iter [01:17, 11.90iter/s]
Best score: 0.2202: : 841iter [01:17, 11.72iter/s]
Best score: 0.2202: : 841iter [01:17, 11.72iter/s]
Best score: 0.2202: : 842iter [01:18, 11.72iter/s]
Best score: 0.2202: : 843iter [01:18, 11.83iter/s]
Best score: 0.2202: : 843iter [01:18, 11.83iter/s]
Best score: 0.2202: : 844iter [01:18, 11.83iter/s]
Best score: 0.2202: : 845iter [01:18, 11.86iter/s]
Best score: 0.2202: : 845iter [01:18, 11.86iter/s]
Best score: 0.2202: : 846iter [01:18, 11.86iter/s]
Best score: 0.2202: : 847iter [01:18, 11.81iter/s]
Best score: 0.2202: : 847iter [01:18, 11.81iter/s]
Best score: 0.2202: : 848iter [01:18, 11.81iter/s]
Best score: 0.2202: : 849iter [01:18, 11.86iter/s]
[ITER 850] Best: 0.2199
[PARAMS] Current best parameters:
  fx: 563.7220
  fy: 563.9738
  px: 908.0812
  py: 925.4460
  k1: -0.03300015
  k2: -0.00664487
  k3: 0.01071575
  k4: -0.00342541
  p1: -0.00913403
  p2: -0.00604929
  p3: -0.00172617
  p4: 0.02594249
  s1: 0.0090
  s2: -0.0268
  s3: 0.0068
  s4: -0.0257
  tilt_x: -0.0041
  tilt_y: -0.0141
  scale: 2.9479
  rotation: -1.1791

Best score: 0.2199: : 849iter [01:18, 11.86iter/s]
Best score: 0.2199: : 850iter [01:19, 11.86iter/s]
Best score: 0.2199: : 851iter [01:19,  7.62iter/s]
Best score: 0.2199: : 851iter [01:19,  7.62iter/s]
Best score: 0.2199: : 852iter [01:19,  7.62iter/s]
Best score: 0.2199: : 853iter [01:19,  8.57iter/s]
Best score: 0.2199: : 853iter [01:19,  8.57iter/s]
Best score: 0.2199: : 854iter [01:19,  8.57iter/s]
Best score: 0.2199: : 855iter [01:19,  9.36iter/s]
Best score: 0.2199: : 855iter [01:19,  9.36iter/s]
Best score: 0.2199: : 856iter [01:19,  9.36iter/s]
Best score: 0.2199: : 857iter [01:19,  9.99iter/s]
Best score: 0.2199: : 857iter [01:19,  9.99iter/s]
Best score: 0.2199: : 858iter [01:19,  9.99iter/s]
Best score: 0.2199: : 859iter [01:19, 10.53iter/s]
Best score: 0.2191: : 859iter [01:19, 10.53iter/s]
Best score: 0.2191: : 860iter [01:19, 10.53iter/s]
Best score: 0.2191: : 861iter [01:19, 10.79iter/s]
Best score: 0.2191: : 861iter [01:19, 10.79iter/s]
Best score: 0.2191: : 862iter [01:20, 10.79iter/s]
Best score: 0.2191: : 863iter [01:20, 11.08iter/s]
Best score: 0.2191: : 863iter [01:20, 11.08iter/s]
Best score: 0.2191: : 864iter [01:20, 11.08iter/s]
Best score: 0.2191: : 865iter [01:20, 11.29iter/s]
Best score: 0.2191: : 865iter [01:20, 11.29iter/s]
Best score: 0.2191: : 866iter [01:20, 11.29iter/s]
Best score: 0.2191: : 867iter [01:20, 11.47iter/s]
Best score: 0.2191: : 867iter [01:20, 11.47iter/s]
Best score: 0.2191: : 868iter [01:20, 11.47iter/s]
Best score: 0.2191: : 869iter [01:20, 11.62iter/s]
Best score: 0.2191: : 869iter [01:20, 11.62iter/s]
Best score: 0.2191: : 870iter [01:20, 11.62iter/s]
Best score: 0.2191: : 871iter [01:20, 11.55iter/s]
Best score: 0.2191: : 871iter [01:20, 11.55iter/s]
Best score: 0.2191: : 872iter [01:20, 11.55iter/s]
Best score: 0.2191: : 873iter [01:20, 11.68iter/s]
Best score: 0.2191: : 873iter [01:20, 11.68iter/s]
Best score: 0.2191: : 874iter [01:21, 11.68iter/s]
Best score: 0.2191: : 875iter [01:21, 11.69iter/s]
Best score: 0.2191: : 875iter [01:21, 11.69iter/s]
Best score: 0.2191: : 876iter [01:21, 11.69iter/s]
Best score: 0.2191: : 877iter [01:21, 11.80iter/s]
Best score: 0.2191: : 877iter [01:21, 11.80iter/s]
Best score: 0.2191: : 878iter [01:21, 11.80iter/s]
Best score: 0.2191: : 879iter [01:21, 11.89iter/s]
Best score: 0.2190: : 879iter [01:21, 11.89iter/s]
Best score: 0.2190: : 880iter [01:21, 11.89iter/s]
Best score: 0.2190: : 881iter [01:21, 11.74iter/s]
Best score: 0.2190: : 881iter [01:21, 11.74iter/s]
Best score: 0.2190: : 882iter [01:21, 11.74iter/s]
Best score: 0.2190: : 883iter [01:21, 11.84iter/s]
Best score: 0.2190: : 883iter [01:21, 11.84iter/s]
Best score: 0.2190: : 884iter [01:21, 11.84iter/s]
Best score: 0.2190: : 885iter [01:21, 11.91iter/s]
Best score: 0.2190: : 885iter [01:21, 11.91iter/s]
Best score: 0.2190: : 886iter [01:22, 11.91iter/s]
Best score: 0.2190: : 887iter [01:22, 11.94iter/s]
Best score: 0.2190: : 887iter [01:22, 11.94iter/s]
Best score: 0.2190: : 888iter [01:22, 11.94iter/s]
Best score: 0.2190: : 889iter [01:22, 11.98iter/s]
Best score: 0.2186: : 889iter [01:22, 11.98iter/s]
Best score: 0.2186: : 890iter [01:22, 11.98iter/s]
Best score: 0.2186: : 891iter [01:22, 11.77iter/s]
Best score: 0.2186: : 891iter [01:22, 11.77iter/s]
Best score: 0.2186: : 892iter [01:22, 11.77iter/s]
Best score: 0.2186: : 893iter [01:22, 11.86iter/s]
Best score: 0.2186: : 893iter [01:22, 11.86iter/s]
Best score: 0.2186: : 894iter [01:22, 11.86iter/s]
Best score: 0.2186: : 895iter [01:22, 11.91iter/s]
Best score: 0.2186: : 895iter [01:22, 11.91iter/s]
Best score: 0.2186: : 896iter [01:22, 11.91iter/s]
Best score: 0.2186: : 897iter [01:22, 11.96iter/s]
Best score: 0.2186: : 897iter [01:22, 11.96iter/s]
Best score: 0.2186: : 898iter [01:23, 11.96iter/s]
Best score: 0.2186: : 899iter [01:23, 11.99iter/s]
[ITER 900] Best: 0.2186
[PARAMS] Current best parameters:
  fx: 562.2357
  fy: 562.4650
  px: 907.9322
  py: 925.3681
  k1: -0.03176148
  k2: -0.00492846
  k3: 0.00843224
  k4: -0.00267435
  p1: -0.00618339
  p2: -0.00313968
  p3: 0.00220788
  p4: 0.01824777
  s1: 0.0021
  s2: -0.0191
  s3: -0.0008
  s4: -0.0176
  tilt_x: -0.0103
  tilt_y: -0.0075
  scale: 2.9484
  rotation: -1.1740

Best score: 0.2186: : 899iter [01:23, 11.99iter/s]
Best score: 0.2186: : 900iter [01:23, 11.99iter/s]
Best score: 0.2186: : 901iter [01:23,  7.67iter/s]
Best score: 0.2186: : 901iter [01:23,  7.67iter/s]
Best score: 0.2186: : 902iter [01:23,  7.67iter/s]
Best score: 0.2186: : 903iter [01:23,  8.60iter/s]
Best score: 0.2186: : 903iter [01:23,  8.60iter/s]
Best score: 0.2186: : 904iter [01:23,  8.60iter/s]
Best score: 0.2186: : 905iter [01:23,  9.41iter/s]
Best score: 0.2186: : 905iter [01:23,  9.41iter/s]
Best score: 0.2186: : 906iter [01:24,  9.41iter/s]
Best score: 0.2186: : 907iter [01:24, 10.06iter/s]
Best score: 0.2186: : 907iter [01:24, 10.06iter/s]
Best score: 0.2186: : 908iter [01:24, 10.06iter/s]
Best score: 0.2186: : 909iter [01:24, 10.60iter/s]
Best score: 0.2182: : 909iter [01:24, 10.60iter/s]
Best score: 0.2182: : 910iter [01:24, 10.60iter/s]
Best score: 0.2182: : 911iter [01:24, 10.78iter/s]
Best score: 0.2182: : 911iter [01:24, 10.78iter/s]
Best score: 0.2182: : 912iter [01:24, 10.78iter/s]
Best score: 0.2182: : 913iter [01:24, 11.14iter/s]
Best score: 0.2182: : 913iter [01:24, 11.14iter/s]
Best score: 0.2182: : 914iter [01:24, 11.14iter/s]
Best score: 0.2182: : 915iter [01:24, 11.39iter/s]
Best score: 0.2182: : 915iter [01:24, 11.39iter/s]
Best score: 0.2182: : 916iter [01:24, 11.39iter/s]
Best score: 0.2182: : 917iter [01:24, 11.58iter/s]
Best score: 0.2182: : 917iter [01:24, 11.58iter/s]
Best score: 0.2182: : 918iter [01:25, 11.58iter/s]
Best score: 0.2182: : 919iter [01:25, 11.72iter/s]
Best score: 0.2172: : 919iter [01:25, 11.72iter/s]
Best score: 0.2172: : 920iter [01:25, 11.72iter/s]
Best score: 0.2172: : 921iter [01:25, 11.62iter/s]
Best score: 0.2172: : 921iter [01:25, 11.62iter/s]
Best score: 0.2172: : 922iter [01:25, 11.62iter/s]
Best score: 0.2172: : 923iter [01:25, 11.69iter/s]
Best score: 0.2172: : 923iter [01:25, 11.69iter/s]
Best score: 0.2172: : 924iter [01:25, 11.69iter/s]
Best score: 0.2172: : 925iter [01:25, 11.80iter/s]
Best score: 0.2172: : 925iter [01:25, 11.80iter/s]
Best score: 0.2172: : 926iter [01:25, 11.80iter/s]
Best score: 0.2172: : 927iter [01:25, 11.86iter/s]
Best score: 0.2172: : 927iter [01:25, 11.86iter/s]
Best score: 0.2172: : 928iter [01:25, 11.86iter/s]
Best score: 0.2172: : 929iter [01:25, 11.92iter/s]
Best score: 0.2169: : 929iter [01:25, 11.92iter/s]
Best score: 0.2169: : 930iter [01:26, 11.92iter/s]
Best score: 0.2169: : 931iter [01:26, 11.77iter/s]
Best score: 0.2169: : 931iter [01:26, 11.77iter/s]
Best score: 0.2169: : 932iter [01:26, 11.77iter/s]
Best score: 0.2169: : 933iter [01:26, 11.76iter/s]
Best score: 0.2169: : 933iter [01:26, 11.76iter/s]
Best score: 0.2169: : 934iter [01:26, 11.76iter/s]
Best score: 0.2169: : 935iter [01:26, 11.84iter/s]
Best score: 0.2169: : 935iter [01:26, 11.84iter/s]
Best score: 0.2169: : 936iter [01:26, 11.84iter/s]
Best score: 0.2169: : 937iter [01:26, 11.87iter/s]
Best score: 0.2169: : 937iter [01:26, 11.87iter/s]
Best score: 0.2169: : 938iter [01:26, 11.87iter/s]
Best score: 0.2169: : 939iter [01:26, 11.90iter/s]
Best score: 0.2169: : 939iter [01:26, 11.90iter/s]
Best score: 0.2169: : 940iter [01:26, 11.90iter/s]
Best score: 0.2169: : 941iter [01:26, 11.76iter/s]
Best score: 0.2169: : 941iter [01:26, 11.76iter/s]
Best score: 0.2169: : 942iter [01:27, 11.76iter/s]
Best score: 0.2169: : 943iter [01:27, 11.81iter/s]
Best score: 0.2169: : 943iter [01:27, 11.81iter/s]
Best score: 0.2169: : 944iter [01:27, 11.81iter/s]
Best score: 0.2169: : 945iter [01:27, 11.79iter/s]
Best score: 0.2169: : 945iter [01:27, 11.79iter/s]
Best score: 0.2169: : 946iter [01:27, 11.79iter/s]
Best score: 0.2169: : 947iter [01:27, 11.87iter/s]
Best score: 0.2169: : 947iter [01:27, 11.87iter/s]
Best score: 0.2169: : 948iter [01:27, 11.87iter/s]
Best score: 0.2169: : 949iter [01:27, 11.87iter/s]
[ITER 950] Best: 0.2169
[PARAMS] Current best parameters:
  fx: 561.2494
  fy: 561.5151
  px: 908.1178
  py: 924.4189
  k1: -0.02915527
  k2: -0.00653989
  k3: 0.00868904
  k4: -0.00261606
  p1: -0.00499339
  p2: -0.00205627
  p3: 0.00134113
  p4: 0.01686532
  s1: 0.0023
  s2: -0.0177
  s3: -0.0018
  s4: -0.0165
  tilt_x: -0.0172
  tilt_y: -0.0062
  scale: 2.9462
  rotation: -1.1799

Best score: 0.2169: : 949iter [01:27, 11.87iter/s]
Best score: 0.2169: : 950iter [01:28, 11.87iter/s]
Best score: 0.2169: : 951iter [01:28,  7.62iter/s]
Best score: 0.2169: : 951iter [01:28,  7.62iter/s]
Best score: 0.2169: : 952iter [01:28,  7.62iter/s]
Best score: 0.2169: : 953iter [01:28,  8.57iter/s]
Best score: 0.2169: : 953iter [01:28,  8.57iter/s]
Best score: 0.2169: : 954iter [01:28,  8.57iter/s]
Best score: 0.2169: : 955iter [01:28,  9.39iter/s]
Best score: 0.2169: : 955iter [01:28,  9.39iter/s]
Best score: 0.2169: : 956iter [01:28,  9.39iter/s]
Best score: 0.2169: : 957iter [01:28, 10.06iter/s]
Best score: 0.2169: : 957iter [01:28, 10.06iter/s]
Best score: 0.2169: : 958iter [01:28, 10.06iter/s]
Best score: 0.2169: : 959iter [01:28, 10.55iter/s]
Best score: 0.2162: : 959iter [01:28, 10.55iter/s]
Best score: 0.2162: : 960iter [01:28, 10.55iter/s]
Best score: 0.2162: : 961iter [01:28, 10.80iter/s]
Best score: 0.2162: : 961iter [01:28, 10.80iter/s]
Best score: 0.2162: : 962iter [01:29, 10.80iter/s]
Best score: 0.2162: : 963iter [01:29, 11.15iter/s]
Best score: 0.2162: : 963iter [01:29, 11.15iter/s]
Best score: 0.2162: : 964iter [01:29, 11.15iter/s]
Best score: 0.2162: : 965iter [01:29, 11.39iter/s]
Best score: 0.2162: : 965iter [01:29, 11.39iter/s]
Best score: 0.2162: : 966iter [01:29, 11.39iter/s]
Best score: 0.2162: : 967iter [01:29, 11.58iter/s]
Best score: 0.2162: : 967iter [01:29, 11.58iter/s]
Best score: 0.2162: : 968iter [01:29, 11.58iter/s]
Best score: 0.2162: : 969iter [01:29, 11.73iter/s]
Best score: 0.2160: : 969iter [01:29, 11.73iter/s]
Best score: 0.2160: : 970iter [01:29, 11.73iter/s]
Best score: 0.2160: : 971iter [01:29, 11.63iter/s]
Best score: 0.2160: : 971iter [01:29, 11.63iter/s]
Best score: 0.2160: : 972iter [01:29, 11.63iter/s]
Best score: 0.2160: : 973iter [01:29, 11.75iter/s]
Best score: 0.2160: : 973iter [01:29, 11.75iter/s]
Best score: 0.2160: : 974iter [01:30, 11.75iter/s]
Best score: 0.2160: : 975iter [01:30, 11.85iter/s]
Best score: 0.2160: : 975iter [01:30, 11.85iter/s]
Best score: 0.2160: : 976iter [01:30, 11.85iter/s]
Best score: 0.2160: : 977iter [01:30, 11.87iter/s]
Best score: 0.2160: : 977iter [01:30, 11.87iter/s]
Best score: 0.2160: : 978iter [01:30, 11.87iter/s]
Best score: 0.2160: : 979iter [01:30, 11.94iter/s]
Best score: 0.2152: : 979iter [01:30, 11.94iter/s]
Best score: 0.2152: : 980iter [01:30, 11.94iter/s]
Best score: 0.2152: : 981iter [01:30, 11.77iter/s]
Best score: 0.2152: : 981iter [01:30, 11.77iter/s]
Best score: 0.2152: : 982iter [01:30, 11.77iter/s]
Best score: 0.2152: : 983iter [01:30, 11.86iter/s]
Best score: 0.2152: : 983iter [01:30, 11.86iter/s]
Best score: 0.2152: : 984iter [01:30, 11.86iter/s]
Best score: 0.2152: : 985iter [01:30, 11.90iter/s]
Best score: 0.2152: : 985iter [01:30, 11.90iter/s]
Best score: 0.2152: : 986iter [01:31, 11.90iter/s]
Best score: 0.2152: : 987iter [01:31, 11.89iter/s]
Best score: 0.2152: : 987iter [01:31, 11.89iter/s]
Best score: 0.2152: : 988iter [01:31, 11.89iter/s]
Best score: 0.2152: : 989iter [01:31, 11.95iter/s]
Best score: 0.2150: : 989iter [01:31, 11.95iter/s]
Best score: 0.2150: : 990iter [01:31, 11.95iter/s]
Best score: 0.2150: : 991iter [01:31, 11.77iter/s]
Best score: 0.2150: : 991iter [01:31, 11.77iter/s]
Best score: 0.2150: : 992iter [01:31, 11.77iter/s]
Best score: 0.2150: : 993iter [01:31, 11.84iter/s]
Best score: 0.2150: : 993iter [01:31, 11.84iter/s]
Best score: 0.2150: : 994iter [01:31, 11.84iter/s]
Best score: 0.2150: : 995iter [01:31, 11.90iter/s]
Best score: 0.2150: : 995iter [01:31, 11.90iter/s]
Best score: 0.2150: : 996iter [01:31, 11.90iter/s]
Best score: 0.2150: : 997iter [01:31, 11.94iter/s]
Best score: 0.2150: : 997iter [01:31, 11.94iter/s]
Best score: 0.2150: : 998iter [01:32, 11.94iter/s]
Best score: 0.2150: : 999iter [01:32, 11.97iter/s]
[ITER 1000] Best: 0.2148
[PARAMS] Current best parameters:
  fx: 557.4948
  fy: 557.8511
  px: 909.1838
  py: 924.1859
  k1: -0.02636351
  k2: -0.00464683
  k3: 0.00698679
  k4: -0.00221953
  p1: 0.00111899
  p2: 0.00320831
  p3: 0.00036870
  p4: 0.00780743
  s1: -0.0002
  s2: -0.0094
  s3: -0.0069
  s4: -0.0076
  tilt_x: -0.0304
  tilt_y: -0.0010
  scale: 2.9490
  rotation: -1.1825

Best score: 0.2148: : 999iter [01:32, 11.97iter/s]
Best score: 0.2148: : 1000iter [01:32, 11.97iter/s]
Best score: 0.2148: : 1001iter [01:32,  7.63iter/s]
Best score: 0.2148: : 1001iter [01:32,  7.63iter/s]
Best score: 0.2148: : 1002iter [01:32,  7.63iter/s]
Best score: 0.2148: : 1003iter [01:32,  8.58iter/s]
Best score: 0.2148: : 1003iter [01:32,  8.58iter/s]
Best score: 0.2148: : 1004iter [01:32,  8.58iter/s]
Best score: 0.2148: : 1005iter [01:32,  9.39iter/s]
Best score: 0.2148: : 1005iter [01:32,  9.39iter/s]
Best score: 0.2148: : 1006iter [01:33,  9.39iter/s]
Best score: 0.2148: : 1007iter [01:33,  9.98iter/s]
Best score: 0.2148: : 1007iter [01:33,  9.98iter/s]
Best score: 0.2148: : 1008iter [01:33,  9.98iter/s]
Best score: 0.2148: : 1009iter [01:33,  8.34iter/s]
Best score: 0.2148: : 1009iter [01:33,  8.34iter/s]
Best score: 0.2148: : 1010iter [01:33,  8.34iter/s]
Best score: 0.2148: : 1011iter [01:33,  9.05iter/s]
Best score: 0.2148: : 1011iter [01:33,  9.05iter/s]
Best score: 0.2148: : 1012iter [01:33,  9.05iter/s]
Best score: 0.2148: : 1013iter [01:33,  9.73iter/s]
Best score: 0.2148: : 1013iter [01:33,  9.73iter/s]
Best score: 0.2148: : 1014iter [01:33,  9.73iter/s]
Best score: 0.2148: : 1015iter [01:33, 10.32iter/s]
Best score: 0.2148: : 1015iter [01:33, 10.32iter/s]
Best score: 0.2148: : 1016iter [01:34, 10.32iter/s]
Best score: 0.2148: : 1017iter [01:34, 10.77iter/s]
Best score: 0.2148: : 1017iter [01:34, 10.77iter/s]
Best score: 0.2148: : 1018iter [01:34, 10.77iter/s]
Best score: 0.2148: : 1019iter [01:34, 11.13iter/s]
Best score: 0.2143: : 1019iter [01:34, 11.13iter/s]
Best score: 0.2143: : 1020iter [01:34, 11.13iter/s]
Best score: 0.2143: : 1021iter [01:34, 11.20iter/s]
Best score: 0.2143: : 1021iter [01:34, 11.20iter/s]
Best score: 0.2143: : 1022iter [01:34, 11.20iter/s]
Best score: 0.2143: : 1023iter [01:34, 11.46iter/s]
Best score: 0.2143: : 1023iter [01:34, 11.46iter/s]
Best score: 0.2143: : 1024iter [01:34, 11.46iter/s]
Best score: 0.2143: : 1025iter [01:34, 11.54iter/s]
Best score: 0.2143: : 1025iter [01:34, 11.54iter/s]
Best score: 0.2143: : 1026iter [01:34, 11.54iter/s]
Best score: 0.2143: : 1027iter [01:34, 11.69iter/s]
Best score: 0.2143: : 1027iter [01:35, 11.69iter/s]
Best score: 0.2143: : 1028iter [01:35, 11.69iter/s]
Best score: 0.2143: : 1029iter [01:35, 11.81iter/s]
Best score: 0.2140: : 1029iter [01:35, 11.81iter/s]
Best score: 0.2140: : 1030iter [01:35, 11.81iter/s]
Best score: 0.2140: : 1031iter [01:35, 11.68iter/s]
Best score: 0.2140: : 1031iter [01:35, 11.68iter/s]
Best score: 0.2140: : 1032iter [01:35, 11.68iter/s]
Best score: 0.2140: : 1033iter [01:35, 11.76iter/s]
Best score: 0.2140: : 1033iter [01:35, 11.76iter/s]
Best score: 0.2140: : 1034iter [01:35, 11.76iter/s]
Best score: 0.2140: : 1035iter [01:35, 11.85iter/s]
Best score: 0.2140: : 1035iter [01:35, 11.85iter/s]
Best score: 0.2140: : 1036iter [01:35, 11.85iter/s]
Best score: 0.2140: : 1037iter [01:35, 11.89iter/s]
Best score: 0.2140: : 1037iter [01:35, 11.89iter/s]
Best score: 0.2140: : 1038iter [01:35, 11.89iter/s]
Best score: 0.2140: : 1039iter [01:35, 11.95iter/s]
Best score: 0.2140: : 1039iter [01:36, 11.95iter/s]
Best score: 0.2140: : 1040iter [01:36, 11.95iter/s]
Best score: 0.2140: : 1041iter [01:36, 11.77iter/s]
Best score: 0.2140: : 1041iter [01:36, 11.77iter/s]
Best score: 0.2140: : 1042iter [01:36, 11.77iter/s]
Best score: 0.2140: : 1043iter [01:36, 11.87iter/s]
Best score: 0.2140: : 1043iter [01:36, 11.87iter/s]
Best score: 0.2140: : 1044iter [01:36, 11.87iter/s]
Best score: 0.2140: : 1045iter [01:36, 11.91iter/s]
Best score: 0.2140: : 1045iter [01:36, 11.91iter/s]
Best score: 0.2140: : 1046iter [01:36, 11.91iter/s]
Best score: 0.2140: : 1047iter [01:36, 11.95iter/s]
Best score: 0.2140: : 1047iter [01:36, 11.95iter/s]
Best score: 0.2140: : 1048iter [01:36, 11.95iter/s]
Best score: 0.2140: : 1049iter [01:36, 11.97iter/s]
[ITER 1050] Best: 0.2139
[PARAMS] Current best parameters:
  fx: 557.0069
  fy: 557.4027
  px: 909.2531
  py: 924.5311
  k1: -0.02849728
  k2: -0.00037812
  k3: 0.00442160
  k4: -0.00169638
  p1: 0.00374741
  p2: 0.00595591
  p3: 0.00134554
  p4: 0.00527704
  s1: -0.0046
  s2: -0.0063
  s3: -0.0104
  s4: -0.0048
  tilt_x: -0.0339
  tilt_y: 0.0042
  scale: 2.9518
  rotation: -1.1779

Best score: 0.2139: : 1049iter [01:36, 11.97iter/s]
Best score: 0.2139: : 1050iter [01:37, 11.97iter/s]
Best score: 0.2139: : 1051iter [01:37,  7.64iter/s]
Best score: 0.2139: : 1051iter [01:37,  7.64iter/s]
Best score: 0.2139: : 1052iter [01:37,  7.64iter/s]
Best score: 0.2139: : 1053iter [01:37,  8.56iter/s]
Best score: 0.2139: : 1053iter [01:37,  8.56iter/s]
Best score: 0.2139: : 1054iter [01:37,  8.56iter/s]
Best score: 0.2139: : 1055iter [01:37,  9.38iter/s]
Best score: 0.2139: : 1055iter [01:37,  9.38iter/s]
Best score: 0.2139: : 1056iter [01:37,  9.38iter/s]
Best score: 0.2139: : 1057iter [01:37, 10.05iter/s]
Best score: 0.2139: : 1057iter [01:37, 10.05iter/s]
Best score: 0.2139: : 1058iter [01:37, 10.05iter/s]
Best score: 0.2139: : 1059iter [01:37, 10.58iter/s]
Best score: 0.2138: : 1059iter [01:38, 10.58iter/s]
Best score: 0.2138: : 1060iter [01:38, 10.58iter/s]
Best score: 0.2138: : 1061iter [01:38, 10.82iter/s]
Best score: 0.2138: : 1061iter [01:38, 10.82iter/s]
Best score: 0.2138: : 1062iter [01:38, 10.82iter/s]
Best score: 0.2138: : 1063iter [01:38, 11.17iter/s]
Best score: 0.2138: : 1063iter [01:38, 11.17iter/s]
Best score: 0.2138: : 1064iter [01:38, 11.17iter/s]
Best score: 0.2138: : 1065iter [01:38, 11.39iter/s]
Best score: 0.2138: : 1065iter [01:38, 11.39iter/s]
Best score: 0.2138: : 1066iter [01:38, 11.39iter/s]
Best score: 0.2138: : 1067iter [01:38, 11.49iter/s]
Best score: 0.2138: : 1067iter [01:38, 11.49iter/s]
Best score: 0.2138: : 1068iter [01:38, 11.49iter/s]
Best score: 0.2138: : 1069iter [01:38, 11.56iter/s]
Best score: 0.2138: : 1069iter [01:38, 11.56iter/s]
Best score: 0.2138: : 1070iter [01:38, 11.56iter/s]
Best score: 0.2138: : 1071iter [01:38, 11.45iter/s]
Best score: 0.2138: : 1071iter [01:39, 11.45iter/s]
Best score: 0.2138: : 1072iter [01:39, 11.45iter/s]
Best score: 0.2138: : 1073iter [01:39, 11.62iter/s]
Best score: 0.2138: : 1073iter [01:39, 11.62iter/s]
Best score: 0.2138: : 1074iter [01:39, 11.62iter/s]
Best score: 0.2138: : 1075iter [01:39, 11.74iter/s]
Best score: 0.2138: : 1075iter [01:39, 11.74iter/s]
Best score: 0.2138: : 1076iter [01:39, 11.74iter/s]
Best score: 0.2138: : 1077iter [01:39, 11.79iter/s]
Best score: 0.2138: : 1077iter [01:39, 11.79iter/s]
Best score: 0.2138: : 1078iter [01:39, 11.79iter/s]
Best score: 0.2138: : 1079iter [01:39, 11.87iter/s]
Best score: 0.2137: : 1079iter [01:39, 11.87iter/s]
Best score: 0.2137: : 1080iter [01:39, 11.87iter/s]
Best score: 0.2137: : 1081iter [01:39, 11.69iter/s]
Best score: 0.2137: : 1081iter [01:39, 11.69iter/s]
Best score: 0.2137: : 1082iter [01:39, 11.69iter/s]
Best score: 0.2137: : 1083iter [01:39, 11.73iter/s]
Best score: 0.2137: : 1083iter [01:40, 11.73iter/s]
Best score: 0.2137: : 1084iter [01:40, 11.73iter/s]
Best score: 0.2137: : 1085iter [01:40, 11.82iter/s]
Best score: 0.2137: : 1085iter [01:40, 11.82iter/s]
Best score: 0.2137: : 1086iter [01:40, 11.82iter/s]
Best score: 0.2137: : 1087iter [01:40, 11.89iter/s]
Best score: 0.2137: : 1087iter [01:40, 11.89iter/s]
Best score: 0.2137: : 1088iter [01:40, 11.89iter/s]
Best score: 0.2137: : 1089iter [01:40, 11.95iter/s]
Best score: 0.2137: : 1089iter [01:40, 11.95iter/s]
Best score: 0.2137: : 1090iter [01:40, 11.95iter/s]
Best score: 0.2137: : 1091iter [01:40, 11.80iter/s]
Best score: 0.2137: : 1091iter [01:40, 11.80iter/s]
Best score: 0.2137: : 1092iter [01:40, 11.80iter/s]
Best score: 0.2137: : 1093iter [01:40, 11.86iter/s]
Best score: 0.2137: : 1093iter [01:40, 11.86iter/s]
Best score: 0.2137: : 1094iter [01:40, 11.86iter/s]
Best score: 0.2137: : 1095iter [01:40, 11.90iter/s]
Best score: 0.2137: : 1095iter [01:41, 11.90iter/s]
Best score: 0.2137: : 1096iter [01:41, 11.90iter/s]
Best score: 0.2137: : 1097iter [01:41, 11.86iter/s]
Best score: 0.2137: : 1097iter [01:41, 11.86iter/s]
Best score: 0.2137: : 1098iter [01:41, 11.86iter/s]
Best score: 0.2137: : 1099iter [01:41, 11.91iter/s]
[ITER 1100] Best: 0.2136
[PARAMS] Current best parameters:
  fx: 555.8726
  fy: 556.2426
  px: 909.4083
  py: 924.0987
  k1: -0.02782957
  k2: 0.00058076
  k3: 0.00368158
  k4: -0.00153586
  p1: 0.00280678
  p2: 0.00446271
  p3: 0.00072666
  p4: 0.00669423
  s1: -0.0023
  s2: -0.0077
  s3: -0.0091
  s4: -0.0064
  tilt_x: -0.0340
  tilt_y: 0.0004
  scale: 2.9525
  rotation: -1.1791

Best score: 0.2136: : 1099iter [01:41, 11.91iter/s]
[📈] Running L-BFGS-B polish after 1100 DE iterations...

Best score: 0.2136: : 1100iter [01:41, 10.82iter/s]
  Polish improved score: 0.213583 -> 0.213474

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 100,887 → 93,942 within 3500mm ring
  Ring polish did not improve score: 0.213474
  Success: True
  Tangential distortion: p1=0.002808, p2=0.004417, p3=0.000644, p4=0.006749
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.2135
[✅] Parameters copied to: /working/MDCP3D-SL-007_W038_2026_05_05/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


-------------------------------------------------------------------
                        Step 4: Undistortion                       
-------------------------------------------------------------------


[DEBUG] Parameters being applied to PTD conversion:
    fx: 555.8725987171666
    fy: 556.2426297390928
    px: 909.4082866873594
    py: 924.0987492499218
    k1: -0.027759949819631705
    k2: 0.0005733910557664895
    k3: 0.003586387696752838
    k4: -0.0014898138058600935
    p1: 0.002807553346738267
    p2: 0.004417484012452055
    p3: 0.00064353704954665
    p4: 0.00674908226621777
    scale: 2.9524757637291317
    rotation: -1.179102763151445
    mmpp: 3.375325270052303

[🔄] Converting 2852 frames to PTD, creating debug images for 400 calibration frames...

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📁 Rigs:  75%|███████▌  | 3/4 [00:21<00:07,  7.37s/rig]

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   🔄 1000:  81%|████████▏ | 590/724 [00:03<00:00, 187.64frame/s]

   🔄 1000:  84%|████████▍ | 609/724 [00:03<00:00, 188.28frame/s]

   🔄 1000:  87%|████████▋ | 629/724 [00:03<00:00, 189.00frame/s]

   🔄 1000:  90%|████████▉ | 648/724 [00:03<00:00, 189.00frame/s]

   🔄 1000:  92%|█████████▏| 667/724 [00:03<00:00, 188.53frame/s]

   🔄 1000:  95%|█████████▍| 686/724 [00:03<00:00, 187.02frame/s]

   🔄 1000:  97%|█████████▋| 705/724 [00:03<00:00, 185.79frame/s]

   🔄 1000: 100%|██████████| 724/724 [00:03<00:00, 185.05frame/s]

                                                                 
📁 Rigs: 100%|██████████| 4/4 [00:28<00:00,  7.23s/rig]
📁 Rigs: 100%|██████████| 4/4 [00:28<00:00,  7.09s/rig]
[✅] Saved PTDs: /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/4_undistorted/output/ptd

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📁 Rigs:  25%|██▌       | 1/4 [00:00<00:02,  1.09rig/s]

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📁 Rigs:  50%|█████     | 2/4 [00:01<00:01,  1.08rig/s]

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   🔄 1500:  90%|█████████ | 90/100 [00:00<00:00, 178.00frame/s]

                                                                
📁 Rigs:  75%|███████▌  | 3/4 [00:02<00:00,  1.08rig/s]

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   🔄 1000:  19%|█▉        | 19/100 [00:00<00:00, 183.37frame/s]

   🔄 1000:  38%|███▊      | 38/100 [00:00<00:00, 182.35frame/s]

   🔄 1000:  57%|█████▋    | 57/100 [00:00<00:00, 182.37frame/s]

   🔄 1000:  76%|███████▌  | 76/100 [00:00<00:00, 181.85frame/s]

   🔄 1000:  95%|█████████▌| 95/100 [00:00<00:00, 180.91frame/s]

                                                                
📁 Rigs: 100%|██████████| 4/4 [00:03<00:00,  1.08rig/s]
📁 Rigs: 100%|██████████| 4/4 [00:03<00:00,  1.08rig/s]
[✅] Saved PTDs: /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/4_undistorted/temp_ptd
[WARN] No .tfd files found for serial extraction
[WARN] Failed to extract serial number from .tfd file. Check that .tfd files exist and contain 'LASERbidh' or 'LASERbidg' pattern. Using 'unknown' as fallback.

📤 Writing LUT:   0%|          | 0/3240000 [00:00<?, ?px/s]
📤 Writing LUT:   3%|▎         | 81845/3240000 [00:00<00:03, 818442.98px/s]
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📤 Writing LUT:  14%|█▎        | 437696/3240000 [00:00<00:03, 884375.78px/s]
📤 Writing LUT:  16%|█▌        | 526134/3240000 [00:00<00:03, 882229.89px/s]
📤 Writing LUT:  19%|█▉        | 615301/3240000 [00:00<00:02, 885310.61px/s]
📤 Writing LUT:  22%|██▏       | 705040/3240000 [00:00<00:02, 889150.06px/s]
📤 Writing LUT:  25%|██▍       | 795701/3240000 [00:00<00:02, 894601.70px/s]
📤 Writing LUT:  27%|██▋       | 886444/3240000 [00:01<00:02, 898556.24px/s]
📤 Writing LUT:  30%|███       | 977117/3240000 [00:01<00:02, 901055.85px/s]
📤 Writing LUT:  33%|███▎      | 1067645/3240000 [00:01<00:02, 902339.50px/s]
📤 Writing LUT:  36%|███▌      | 1157953/3240000 [00:01<00:02, 902563.39px/s]
📤 Writing LUT:  39%|███▊      | 1248901/3240000 [00:01<00:02, 904650.58px/s]
📤 Writing LUT:  41%|████▏     | 1339367/3240000 [00:01<00:02, 904328.10px/s]
📤 Writing LUT:  44%|████▍     | 1429801/3240000 [00:01<00:02, 902351.02px/s]
📤 Writing LUT:  47%|████▋     | 1521291/3240000 [00:01<00:01, 906116.84px/s]
📤 Writing LUT:  50%|████▉     | 1613134/3240000 [00:01<00:01, 909810.58px/s]
📤 Writing LUT:  53%|█████▎    | 1704117/3240000 [00:01<00:01, 909559.62px/s]
📤 Writing LUT:  55%|█████▌    | 1795074/3240000 [00:02<00:01, 909379.57px/s]
📤 Writing LUT:  58%|█████▊    | 1886013/3240000 [00:02<00:01, 897348.36px/s]
📤 Writing LUT:  61%|██████    | 1977100/3240000 [00:02<00:01, 901365.07px/s]
📤 Writing LUT:  64%|██████▍   | 2069251/3240000 [00:02<00:01, 907366.34px/s]
📤 Writing LUT:  67%|██████▋   | 2160687/3240000 [00:02<00:01, 909453.04px/s]
📤 Writing LUT:  69%|██████▉   | 2251695/3240000 [00:02<00:01, 909637.53px/s]
📤 Writing LUT:  72%|███████▏  | 2342672/3240000 [00:02<00:00, 901008.73px/s]
📤 Writing LUT:  75%|███████▌  | 2432799/3240000 [00:02<00:00, 894211.59px/s]
📤 Writing LUT:  78%|███████▊  | 2522428/3240000 [00:02<00:00, 894827.79px/s]
📤 Writing LUT:  81%|████████  | 2611929/3240000 [00:02<00:00, 890260.81px/s]
📤 Writing LUT:  83%|████████▎ | 2702327/3240000 [00:03<00:00, 894303.86px/s]
📤 Writing LUT:  86%|████████▌ | 2791772/3240000 [00:03<00:00, 894313.36px/s]
📤 Writing LUT:  89%|████████▉ | 2883082/3240000 [00:03<00:00, 899923.46px/s]
📤 Writing LUT:  92%|█████████▏| 2974642/3240000 [00:03<00:00, 904609.17px/s]
📤 Writing LUT:  95%|█████████▍| 3065238/3240000 [00:03<00:00, 905013.13px/s]
📤 Writing LUT:  97%|█████████▋| 3155746/3240000 [00:03<00:00, 899073.13px/s]
📤 Writing LUT: 100%|██████████| 3240000/3240000 [00:03<00:00, 897194.92px/s]
[✅] LUT written to: /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/4_undistorted/output/LUT.lut
[✅] LUT copied to: /working/MDCP3D-SL-007_W038_2026_05_05/calibration/MDCP3D-SL-007_W038_unknown_2026_05_05.lut

-------------------------------------------------------------------
                          Step 5: Heatmap                          
-------------------------------------------------------------------

[ℹ️] Detected device type: SMD_P3D (rigs: [1000, 1500, 2000]mm)

📁 Rigs (heatmap):   0%|          | 0/4 [00:00<?, ?rig/s]

   🔥 2000L:   0%|          | 0/576 [00:00<?, ?frame/s]

   🔥 2000L:   1%|          | 7/576 [00:00<00:08, 69.23frame/s]

   🔥 2000L:   3%|▎         | 15/576 [00:00<00:07, 74.09frame/s]

   🔥 2000L:   4%|▍         | 23/576 [00:00<00:07, 75.79frame/s]

   🔥 2000L:   5%|▌         | 31/576 [00:00<00:07, 76.94frame/s]

   🔥 2000L:   7%|▋         | 39/576 [00:00<00:06, 77.94frame/s]

   🔥 2000L:   8%|▊         | 47/576 [00:00<00:06, 78.25frame/s]

   🔥 2000L:  10%|▉         | 56/576 [00:00<00:06, 79.17frame/s]

   🔥 2000L:  11%|█         | 64/576 [00:00<00:06, 79.07frame/s]

   🔥 2000L:  12%|█▎        | 72/576 [00:00<00:06, 79.05frame/s]

   🔥 2000L:  14%|█▍        | 80/576 [00:01<00:06, 78.63frame/s]

   🔥 2000L:  15%|█▌        | 88/576 [00:01<00:06, 78.93frame/s]

   🔥 2000L:  17%|█▋        | 96/576 [00:01<00:06, 78.71frame/s]

   🔥 2000L:  18%|█▊        | 104/576 [00:01<00:05, 78.89frame/s]

   🔥 2000L:  20%|█▉        | 113/576 [00:01<00:05, 79.45frame/s]

   🔥 2000L:  21%|██        | 122/576 [00:01<00:05, 80.55frame/s]

   🔥 2000L:  23%|██▎       | 131/576 [00:01<00:05, 81.86frame/s]

   🔥 2000L:  24%|██▍       | 140/576 [00:01<00:05, 83.12frame/s]

   🔥 2000L:  26%|██▌       | 149/576 [00:01<00:05, 83.93frame/s]

   🔥 2000L:  27%|██▋       | 158/576 [00:01<00:04, 85.25frame/s]

   🔥 2000L:  29%|██▉       | 168/576 [00:02<00:04, 87.99frame/s]

   🔥 2000L:  31%|███       | 179/576 [00:02<00:04, 92.28frame/s]

   🔥 2000L:  33%|███▎      | 189/576 [00:02<00:04, 93.21frame/s]

   🔥 2000L:  35%|███▍      | 199/576 [00:02<00:04, 93.67frame/s]

   🔥 2000L:  36%|███▋      | 209/576 [00:02<00:03, 94.13frame/s]

   🔥 2000L:  38%|███▊      | 219/576 [00:02<00:03, 94.19frame/s]

   🔥 2000L:  40%|███▉      | 229/576 [00:02<00:03, 94.93frame/s]

   🔥 2000L:  41%|████▏     | 239/576 [00:02<00:03, 96.04frame/s]

   🔥 2000L:  43%|████▎     | 250/576 [00:02<00:03, 97.70frame/s]

   🔥 2000L:  45%|████▌     | 261/576 [00:03<00:03, 98.74frame/s]

   🔥 2000L:  47%|████▋     | 271/576 [00:03<00:03, 99.06frame/s]

   🔥 2000L:  49%|████▉     | 281/576 [00:03<00:02, 98.37frame/s]

   🔥 2000L:  51%|█████     | 291/576 [00:03<00:02, 97.81frame/s]

   🔥 2000L:  52%|█████▏    | 301/576 [00:03<00:02, 96.72frame/s]

   🔥 2000L:  54%|█████▍    | 311/576 [00:03<00:02, 96.44frame/s]

   🔥 2000L:  56%|█████▌    | 321/576 [00:03<00:02, 95.56frame/s]

   🔥 2000L:  57%|█████▋    | 331/576 [00:03<00:02, 95.00frame/s]

   🔥 2000L:  59%|█████▉    | 341/576 [00:03<00:02, 94.78frame/s]

   🔥 2000L:  61%|██████    | 351/576 [00:03<00:02, 94.25frame/s]

   🔥 2000L:  63%|██████▎   | 361/576 [00:04<00:02, 94.94frame/s]

   🔥 2000L:  64%|██████▍   | 371/576 [00:04<00:02, 95.15frame/s]

   🔥 2000L:  66%|██████▌   | 381/576 [00:04<00:02, 95.38frame/s]

   🔥 2000L:  68%|██████▊   | 391/576 [00:04<00:01, 95.89frame/s]

   🔥 2000L:  70%|██████▉   | 401/576 [00:04<00:01, 93.61frame/s]

   🔥 2000L:  71%|███████▏  | 411/576 [00:04<00:01, 91.25frame/s]

   🔥 2000L:  73%|███████▎  | 421/576 [00:04<00:01, 89.97frame/s]

   🔥 2000L:  75%|███████▍  | 431/576 [00:04<00:01, 88.32frame/s]

   🔥 2000L:  76%|███████▋  | 440/576 [00:04<00:01, 87.09frame/s]

   🔥 2000L:  78%|███████▊  | 449/576 [00:05<00:01, 85.97frame/s]

   🔥 2000L:  80%|███████▉  | 458/576 [00:05<00:01, 85.10frame/s]

   🔥 2000L:  81%|████████  | 467/576 [00:05<00:01, 83.83frame/s]

   🔥 2000L:  83%|████████▎ | 476/576 [00:05<00:01, 82.65frame/s]

   🔥 2000L:  84%|████████▍ | 485/576 [00:05<00:01, 81.75frame/s]

   🔥 2000L:  86%|████████▌ | 494/576 [00:05<00:01, 81.16frame/s]

   🔥 2000L:  87%|████████▋ | 503/576 [00:05<00:00, 80.86frame/s]

   🔥 2000L:  89%|████████▉ | 512/576 [00:05<00:00, 80.53frame/s]

   🔥 2000L:  90%|█████████ | 521/576 [00:05<00:00, 80.55frame/s]

   🔥 2000L:  92%|█████████▏| 530/576 [00:06<00:00, 80.34frame/s]

   🔥 2000L:  94%|█████████▎| 539/576 [00:06<00:00, 79.80frame/s]

   🔥 2000L:  95%|█████████▌| 548/576 [00:06<00:00, 80.06frame/s]

   🔥 2000L:  97%|█████████▋| 557/576 [00:06<00:00, 79.84frame/s]

   🔥 2000L:  98%|█████████▊| 565/576 [00:06<00:00, 78.76frame/s]

   🔥 2000L:  99%|█████████▉| 573/576 [00:06<00:00, 77.93frame/s]

                                                                 [✅] 2000L: /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/5_heatmap/2000L_heatmap.png
[✅] 2000L (fitted): /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/5_heatmap/2000L_heatmap_fitted.png

📁 Rigs (heatmap):  25%|██▌       | 1/4 [00:08<00:25,  8.34s/rig]

   🔥 2000R:   0%|          | 0/735 [00:00<?, ?frame/s]

   🔥 2000R:   1%|          | 8/735 [00:00<00:09, 75.27frame/s]

   🔥 2000R:   2%|▏         | 16/735 [00:00<00:09, 76.58frame/s]

   🔥 2000R:   3%|▎         | 24/735 [00:00<00:09, 77.51frame/s]

   🔥 2000R:   4%|▍         | 33/735 [00:00<00:08, 78.68frame/s]

   🔥 2000R:   6%|▌         | 42/735 [00:00<00:08, 79.38frame/s]

   🔥 2000R:   7%|▋         | 50/735 [00:00<00:08, 79.28frame/s]

   🔥 2000R:   8%|▊         | 59/735 [00:00<00:08, 79.58frame/s]

   🔥 2000R:   9%|▉         | 68/735 [00:00<00:08, 80.02frame/s]

   🔥 2000R:  10%|█         | 77/735 [00:00<00:08, 80.74frame/s]

   🔥 2000R:  12%|█▏        | 86/735 [00:01<00:07, 81.99frame/s]

   🔥 2000R:  13%|█▎        | 95/735 [00:01<00:07, 82.85frame/s]

   🔥 2000R:  14%|█▍        | 104/735 [00:01<00:07, 83.90frame/s]

   🔥 2000R:  15%|█▌        | 113/735 [00:01<00:07, 84.89frame/s]

   🔥 2000R:  17%|█▋        | 122/735 [00:01<00:07, 85.17frame/s]

   🔥 2000R:  18%|█▊        | 131/735 [00:01<00:07, 85.87frame/s]

   🔥 2000R:  19%|█▉        | 140/735 [00:01<00:06, 85.94frame/s]

   🔥 2000R:  20%|██        | 149/735 [00:01<00:06, 86.59frame/s]

   🔥 2000R:  21%|██▏       | 158/735 [00:01<00:06, 86.27frame/s]

   🔥 2000R:  23%|██▎       | 167/735 [00:02<00:06, 86.45frame/s]

   🔥 2000R:  24%|██▍       | 176/735 [00:02<00:06, 86.70frame/s]

   🔥 2000R:  25%|██▌       | 185/735 [00:02<00:06, 86.70frame/s]

   🔥 2000R:  27%|██▋       | 195/735 [00:02<00:05, 90.01frame/s]

   🔥 2000R:  28%|██▊       | 207/735 [00:02<00:05, 96.49frame/s]

   🔥 2000R:  30%|██▉       | 218/735 [00:02<00:05, 98.73frame/s]

   🔥 2000R:  31%|███       | 229/735 [00:02<00:05, 99.50frame/s]

   🔥 2000R:  33%|███▎      | 239/735 [00:02<00:05, 99.17frame/s]

   🔥 2000R:  34%|███▍      | 249/735 [00:02<00:04, 98.88frame/s]

   🔥 2000R:  35%|███▌      | 259/735 [00:02<00:04, 98.84frame/s]

   🔥 2000R:  37%|███▋      | 269/735 [00:03<00:04, 99.06frame/s]

   🔥 2000R:  38%|███▊      | 279/735 [00:03<00:04, 99.05frame/s]

   🔥 2000R:  39%|███▉      | 289/735 [00:03<00:04, 99.11frame/s]

   🔥 2000R:  41%|████      | 299/735 [00:03<00:04, 99.12frame/s]

   🔥 2000R:  42%|████▏     | 309/735 [00:03<00:04, 99.23frame/s]

   🔥 2000R:  44%|████▎     | 320/735 [00:03<00:04, 99.78frame/s]

   🔥 2000R:  45%|████▍     | 330/735 [00:03<00:04, 99.61frame/s]

   🔥 2000R:  46%|████▋     | 340/735 [00:03<00:03, 99.33frame/s]

   🔥 2000R:  48%|████▊     | 350/735 [00:03<00:03, 98.41frame/s]

   🔥 2000R:  49%|████▉     | 360/735 [00:03<00:03, 97.69frame/s]

   🔥 2000R:  50%|█████     | 370/735 [00:04<00:03, 96.64frame/s]

   🔥 2000R:  52%|█████▏    | 380/735 [00:04<00:03, 96.28frame/s]

   🔥 2000R:  53%|█████▎    | 390/735 [00:04<00:03, 95.93frame/s]

   🔥 2000R:  54%|█████▍    | 400/735 [00:04<00:03, 95.56frame/s]

   🔥 2000R:  56%|█████▌    | 410/735 [00:04<00:03, 95.46frame/s]

   🔥 2000R:  57%|█████▋    | 420/735 [00:04<00:03, 95.58frame/s]

   🔥 2000R:  59%|█████▊    | 430/735 [00:04<00:03, 96.07frame/s]

   🔥 2000R:  60%|█████▉    | 440/735 [00:04<00:03, 96.82frame/s]

   🔥 2000R:  61%|██████▏   | 451/735 [00:04<00:02, 98.21frame/s]

   🔥 2000R:  63%|██████▎   | 462/735 [00:05<00:02, 99.70frame/s]

   🔥 2000R:  64%|██████▍   | 473/735 [00:05<00:02, 101.86frame/s]

   🔥 2000R:  66%|██████▌   | 485/735 [00:05<00:02, 104.93frame/s]

   🔥 2000R:  68%|██████▊   | 497/735 [00:05<00:02, 108.52frame/s]

   🔥 2000R:  69%|██████▉   | 509/735 [00:05<00:02, 111.27frame/s]

   🔥 2000R:  71%|███████   | 521/735 [00:05<00:01, 111.36frame/s]

   🔥 2000R:  73%|███████▎  | 533/735 [00:05<00:01, 107.98frame/s]

   🔥 2000R:  74%|███████▍  | 544/735 [00:05<00:01, 104.42frame/s]

   🔥 2000R:  76%|███████▌  | 555/735 [00:05<00:01, 99.74frame/s] 

   🔥 2000R:  77%|███████▋  | 566/735 [00:06<00:01, 95.74frame/s]

   🔥 2000R:  78%|███████▊  | 576/735 [00:06<00:01, 93.34frame/s]

   🔥 2000R:  80%|███████▉  | 586/735 [00:06<00:01, 92.02frame/s]

   🔥 2000R:  81%|████████  | 596/735 [00:06<00:01, 90.85frame/s]

   🔥 2000R:  82%|████████▏ | 606/735 [00:06<00:01, 89.75frame/s]

   🔥 2000R:  84%|████████▎ | 615/735 [00:06<00:01, 89.04frame/s]

   🔥 2000R:  85%|████████▍ | 624/735 [00:06<00:01, 88.34frame/s]

   🔥 2000R:  86%|████████▌ | 633/735 [00:06<00:01, 87.10frame/s]

   🔥 2000R:  87%|████████▋ | 642/735 [00:06<00:01, 85.92frame/s]

   🔥 2000R:  89%|████████▊ | 651/735 [00:07<00:00, 84.60frame/s]

   🔥 2000R:  90%|████████▉ | 660/735 [00:07<00:00, 83.21frame/s]

   🔥 2000R:  91%|█████████ | 669/735 [00:07<00:00, 82.21frame/s]

   🔥 2000R:  92%|█████████▏| 678/735 [00:07<00:00, 80.63frame/s]

   🔥 2000R:  93%|█████████▎| 687/735 [00:07<00:00, 80.05frame/s]

   🔥 2000R:  95%|█████████▍| 696/735 [00:07<00:00, 79.80frame/s]

   🔥 2000R:  96%|█████████▌| 704/735 [00:07<00:00, 79.51frame/s]

   🔥 2000R:  97%|█████████▋| 712/735 [00:07<00:00, 79.62frame/s]

   🔥 2000R:  98%|█████████▊| 720/735 [00:07<00:00, 79.41frame/s]

   🔥 2000R:  99%|█████████▉| 728/735 [00:07<00:00, 79.22frame/s]

                                                                 [✅] 2000R: /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/5_heatmap/2000R_heatmap.png
[✅] 2000R (fitted): /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/5_heatmap/2000R_heatmap_fitted.png

📁 Rigs (heatmap):  50%|█████     | 2/4 [00:18<00:18,  9.16s/rig]

   🔥 1500:   0%|          | 0/817 [00:00<?, ?frame/s]

   🔥 1500:   1%|          | 9/817 [00:00<00:09, 84.93frame/s]

   🔥 1500:   2%|▏         | 19/817 [00:00<00:08, 89.47frame/s]

   🔥 1500:   4%|▎         | 29/817 [00:00<00:08, 90.56frame/s]

   🔥 1500:   5%|▍         | 39/817 [00:00<00:08, 92.05frame/s]

   🔥 1500:   6%|▌         | 49/817 [00:00<00:08, 92.26frame/s]

   🔥 1500:   7%|▋         | 59/817 [00:00<00:08, 92.18frame/s]

   🔥 1500:   8%|▊         | 69/817 [00:00<00:08, 93.29frame/s]

   🔥 1500:  10%|▉         | 79/817 [00:00<00:07, 92.92frame/s]

   🔥 1500:  11%|█         | 89/817 [00:00<00:08, 90.82frame/s]

   🔥 1500:  12%|█▏        | 99/817 [00:01<00:08, 87.94frame/s]

   🔥 1500:  13%|█▎        | 108/817 [00:01<00:08, 85.77frame/s]

   🔥 1500:  14%|█▍        | 117/817 [00:01<00:08, 84.18frame/s]

   🔥 1500:  15%|█▌        | 126/817 [00:01<00:08, 82.74frame/s]

   🔥 1500:  17%|█▋        | 135/817 [00:01<00:08, 80.85frame/s]

   🔥 1500:  18%|█▊        | 144/817 [00:01<00:08, 79.55frame/s]

   🔥 1500:  19%|█▊        | 152/817 [00:01<00:08, 79.46frame/s]

   🔥 1500:  20%|█▉        | 160/817 [00:01<00:08, 78.88frame/s]

   🔥 1500:  21%|██        | 168/817 [00:01<00:08, 78.59frame/s]

   🔥 1500:  22%|██▏       | 176/817 [00:02<00:08, 78.58frame/s]

   🔥 1500:  23%|██▎       | 184/817 [00:02<00:08, 78.76frame/s]

   🔥 1500:  24%|██▎       | 193/817 [00:02<00:07, 79.35frame/s]

   🔥 1500:  25%|██▍       | 201/817 [00:02<00:07, 79.44frame/s]

   🔥 1500:  26%|██▌       | 209/817 [00:02<00:07, 79.44frame/s]

   🔥 1500:  27%|██▋       | 217/817 [00:02<00:07, 78.99frame/s]

   🔥 1500:  28%|██▊       | 225/817 [00:02<00:07, 78.94frame/s]

   🔥 1500:  29%|██▊       | 233/817 [00:02<00:07, 79.15frame/s]

   🔥 1500:  29%|██▉       | 241/817 [00:02<00:07, 79.26frame/s]

   🔥 1500:  31%|███       | 250/817 [00:03<00:07, 79.47frame/s]

   🔥 1500:  32%|███▏      | 259/817 [00:03<00:06, 79.78frame/s]

   🔥 1500:  33%|███▎      | 267/817 [00:03<00:06, 79.55frame/s]

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   🔥 1500:  40%|████      | 329/817 [00:03<00:06, 80.36frame/s]

   🔥 1500:  41%|████▏     | 338/817 [00:04<00:05, 80.32frame/s]

   🔥 1500:  42%|████▏     | 347/817 [00:04<00:05, 80.59frame/s]

   🔥 1500:  44%|████▎     | 356/817 [00:04<00:05, 80.93frame/s]

   🔥 1500:  45%|████▍     | 365/817 [00:04<00:05, 81.22frame/s]

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   🔥 1500:  47%|████▋     | 383/817 [00:04<00:05, 81.68frame/s]

   🔥 1500:  48%|████▊     | 392/817 [00:04<00:05, 81.35frame/s]

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   🔥 1500:  56%|█████▌    | 458/817 [00:05<00:03, 89.76frame/s]

   🔥 1500:  57%|█████▋    | 468/817 [00:05<00:03, 90.31frame/s]

   🔥 1500:  59%|█████▊    | 478/817 [00:05<00:03, 89.17frame/s]

   🔥 1500:  60%|█████▉    | 487/817 [00:05<00:03, 87.74frame/s]

   🔥 1500:  61%|██████    | 496/817 [00:05<00:03, 86.32frame/s]

   🔥 1500:  62%|██████▏   | 505/817 [00:06<00:03, 85.55frame/s]

   🔥 1500:  63%|██████▎   | 514/817 [00:06<00:03, 85.08frame/s]

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   🔥 1500:  73%|███████▎  | 595/817 [00:07<00:02, 82.99frame/s]

   🔥 1500:  74%|███████▍  | 604/817 [00:07<00:02, 83.27frame/s]

   🔥 1500:  75%|███████▌  | 613/817 [00:07<00:02, 83.49frame/s]

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   🔥 1500:  78%|███████▊  | 640/817 [00:07<00:02, 84.69frame/s]

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   🔥 1500:  82%|████████▏ | 668/817 [00:07<00:01, 87.04frame/s]

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   🔥 1500:  84%|████████▍ | 688/817 [00:08<00:01, 91.35frame/s]

   🔥 1500:  85%|████████▌ | 698/817 [00:08<00:01, 92.35frame/s]

   🔥 1500:  87%|████████▋ | 708/817 [00:08<00:01, 92.50frame/s]

   🔥 1500:  88%|████████▊ | 718/817 [00:08<00:01, 92.71frame/s]

   🔥 1500:  89%|████████▉ | 728/817 [00:08<00:00, 92.40frame/s]

   🔥 1500:  90%|█████████ | 738/817 [00:08<00:00, 92.29frame/s]

   🔥 1500:  92%|█████████▏| 748/817 [00:08<00:00, 91.50frame/s]

   🔥 1500:  93%|█████████▎| 758/817 [00:08<00:00, 90.72frame/s]

   🔥 1500:  94%|█████████▍| 768/817 [00:09<00:00, 90.44frame/s]

   🔥 1500:  95%|█████████▌| 778/817 [00:09<00:00, 90.37frame/s]

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   🔥 1500:  98%|█████████▊| 798/817 [00:09<00:00, 90.57frame/s]

   🔥 1500:  99%|█████████▉| 808/817 [00:09<00:00, 90.15frame/s]

                                                                [✅] 1500: /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/5_heatmap/1500_heatmap.png
[✅] 1500 (fitted): /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/5_heatmap/1500_heatmap_fitted.png

📁 Rigs (heatmap):  75%|███████▌  | 3/4 [00:29<00:10, 10.05s/rig]

   🔥 1000:   0%|          | 0/724 [00:00<?, ?frame/s]

   🔥 1000:   1%|          | 9/724 [00:00<00:08, 81.29frame/s]

   🔥 1000:   2%|▏         | 18/724 [00:00<00:08, 82.26frame/s]

   🔥 1000:   4%|▎         | 27/724 [00:00<00:08, 83.45frame/s]

   🔥 1000:   5%|▍         | 36/724 [00:00<00:08, 85.50frame/s]

   🔥 1000:   6%|▋         | 46/724 [00:00<00:07, 87.40frame/s]

   🔥 1000:   8%|▊         | 56/724 [00:00<00:07, 88.74frame/s]

   🔥 1000:   9%|▉         | 66/724 [00:00<00:07, 90.80frame/s]

   🔥 1000:  10%|█         | 76/724 [00:00<00:06, 92.89frame/s]

   🔥 1000:  12%|█▏        | 86/724 [00:00<00:06, 94.28frame/s]

   🔥 1000:  13%|█▎        | 96/724 [00:01<00:06, 94.73frame/s]

   🔥 1000:  15%|█▍        | 106/724 [00:01<00:06, 96.07frame/s]

   🔥 1000:  16%|█▌        | 116/724 [00:01<00:06, 96.82frame/s]

   🔥 1000:  17%|█▋        | 126/724 [00:01<00:06, 95.97frame/s]

   🔥 1000:  19%|█▉        | 136/724 [00:01<00:06, 93.69frame/s]

   🔥 1000:  20%|██        | 146/724 [00:01<00:06, 90.98frame/s]

   🔥 1000:  22%|██▏       | 156/724 [00:01<00:06, 89.13frame/s]

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   🔥 1000:  30%|███       | 219/724 [00:02<00:06, 82.08frame/s]

   🔥 1000:  31%|███▏      | 228/724 [00:02<00:05, 82.83frame/s]

   🔥 1000:  33%|███▎      | 237/724 [00:02<00:05, 83.00frame/s]

   🔥 1000:  34%|███▍      | 246/724 [00:02<00:05, 82.68frame/s]

   🔥 1000:  35%|███▌      | 255/724 [00:02<00:05, 82.23frame/s]

   🔥 1000:  36%|███▋      | 264/724 [00:03<00:05, 82.45frame/s]

   🔥 1000:  38%|███▊      | 273/724 [00:03<00:05, 81.83frame/s]

   🔥 1000:  39%|███▉      | 282/724 [00:03<00:05, 81.73frame/s]

   🔥 1000:  40%|████      | 291/724 [00:03<00:05, 81.25frame/s]

   🔥 1000:  41%|████▏     | 300/724 [00:03<00:05, 81.22frame/s]

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   🔥 1000:  44%|████▍     | 318/724 [00:03<00:04, 82.13frame/s]

   🔥 1000:  45%|████▌     | 327/724 [00:03<00:04, 82.42frame/s]

   🔥 1000:  47%|████▋     | 337/724 [00:03<00:04, 84.77frame/s]

   🔥 1000:  48%|████▊     | 347/724 [00:04<00:04, 87.67frame/s]

   🔥 1000:  49%|████▉     | 357/724 [00:04<00:04, 90.43frame/s]

   🔥 1000:  51%|█████     | 367/724 [00:04<00:03, 92.78frame/s]

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   🔥 1000:  53%|█████▎    | 387/724 [00:04<00:03, 95.52frame/s]

   🔥 1000:  55%|█████▍    | 397/724 [00:04<00:03, 95.86frame/s]

   🔥 1000:  56%|█████▌    | 407/724 [00:04<00:03, 95.55frame/s]

   🔥 1000:  58%|█████▊    | 417/724 [00:04<00:03, 94.97frame/s]

   🔥 1000:  59%|█████▉    | 427/724 [00:04<00:03, 94.16frame/s]

   🔥 1000:  60%|██████    | 437/724 [00:04<00:03, 88.30frame/s]

   🔥 1000:  62%|██████▏   | 446/724 [00:05<00:03, 87.02frame/s]

   🔥 1000:  63%|██████▎   | 455/724 [00:05<00:03, 85.97frame/s]

   🔥 1000:  64%|██████▍   | 464/724 [00:05<00:03, 85.23frame/s]

   🔥 1000:  65%|██████▌   | 473/724 [00:05<00:02, 84.90frame/s]

   🔥 1000:  67%|██████▋   | 482/724 [00:05<00:02, 84.98frame/s]

   🔥 1000:  68%|██████▊   | 491/724 [00:05<00:02, 84.69frame/s]

   🔥 1000:  69%|██████▉   | 500/724 [00:05<00:02, 84.83frame/s]

   🔥 1000:  70%|███████   | 509/724 [00:05<00:02, 84.80frame/s]

   🔥 1000:  72%|███████▏  | 518/724 [00:05<00:02, 84.82frame/s]

   🔥 1000:  73%|███████▎  | 527/724 [00:06<00:02, 85.16frame/s]

   🔥 1000:  74%|███████▍  | 536/724 [00:06<00:02, 85.74frame/s]

   🔥 1000:  75%|███████▌  | 545/724 [00:06<00:02, 86.19frame/s]

   🔥 1000:  77%|███████▋  | 554/724 [00:06<00:01, 86.53frame/s]

   🔥 1000:  78%|███████▊  | 563/724 [00:06<00:01, 86.79frame/s]

   🔥 1000:  79%|███████▉  | 572/724 [00:06<00:01, 87.41frame/s]

   🔥 1000:  80%|████████  | 581/724 [00:06<00:01, 88.06frame/s]

   🔥 1000:  82%|████████▏ | 591/724 [00:06<00:01, 89.16frame/s]

   🔥 1000:  83%|████████▎ | 601/724 [00:06<00:01, 90.13frame/s]

   🔥 1000:  84%|████████▍ | 611/724 [00:06<00:01, 90.83frame/s]

   🔥 1000:  86%|████████▌ | 621/724 [00:07<00:01, 91.52frame/s]

   🔥 1000:  87%|████████▋ | 631/724 [00:07<00:01, 91.87frame/s]

   🔥 1000:  89%|████████▊ | 641/724 [00:07<00:00, 92.35frame/s]

   🔥 1000:  90%|████████▉ | 651/724 [00:07<00:00, 92.19frame/s]

   🔥 1000:  91%|█████████▏| 661/724 [00:07<00:00, 91.93frame/s]

   🔥 1000:  93%|█████████▎| 671/724 [00:07<00:00, 91.56frame/s]

   🔥 1000:  94%|█████████▍| 681/724 [00:07<00:00, 91.19frame/s]

   🔥 1000:  95%|█████████▌| 691/724 [00:07<00:00, 90.68frame/s]

   🔥 1000:  97%|█████████▋| 701/724 [00:07<00:00, 90.00frame/s]

   🔥 1000:  98%|█████████▊| 711/724 [00:08<00:00, 88.52frame/s]

   🔥 1000:  99%|█████████▉| 720/724 [00:08<00:00, 87.37frame/s]

                                                                [✅] 1000: /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/5_heatmap/1000_heatmap_fitted.png

📁 Rigs (heatmap): 100%|██████████| 4/4 [00:38<00:00,  9.63s/rig]
📁 Rigs (heatmap): 100%|██████████| 4/4 [00:38<00:00,  9.54s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MDCP3D-SL-007_W038_2026_05_05/calibration/debug/5_heatmap
[🏁] Finished processing MDCP3D-SL-007_W038_2026_05_05


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