🟢 Starting Calibration Pipeline

=== Processing MDCP3D-SL-010_W046(6)_2026-04-09 ===

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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 410 stationary frames, 570 remain


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                                                                            [PASS2] Frame 0000246: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000590: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000630: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000642: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000643: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000644: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000645: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000654: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000655: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000656: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000657: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000694: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000695: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000696: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000697: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000700: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000701: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000702: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000703: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000706: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000707: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000708: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000709: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000724: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000742: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001076: fixed corners {1, 2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001182: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0000246: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000656: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000696: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000702: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000246: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Summary: 14 frames fixed, 32 untrusted, 569 total


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→ 2000R Phase 3: finalize:  78%|███████▊  | 446/569 [00:09<00:02, 48.80it/s]

→ 2000R Phase 3: finalize:  79%|███████▉  | 451/569 [00:09<00:02, 48.65it/s]

→ 2000R Phase 3: finalize:  80%|████████  | 456/569 [00:09<00:02, 48.88it/s]

→ 2000R Phase 3: finalize:  81%|████████  | 461/569 [00:09<00:02, 48.99it/s]

→ 2000R Phase 3: finalize:  82%|████████▏ | 466/569 [00:09<00:02, 49.00it/s]

→ 2000R Phase 3: finalize:  83%|████████▎ | 471/569 [00:09<00:02, 48.93it/s]

→ 2000R Phase 3: finalize:  84%|████████▎ | 476/569 [00:09<00:01, 48.89it/s]

→ 2000R Phase 3: finalize:  85%|████████▍ | 481/569 [00:09<00:01, 49.05it/s]

→ 2000R Phase 3: finalize:  85%|████████▌ | 486/569 [00:09<00:01, 49.24it/s]

→ 2000R Phase 3: finalize:  86%|████████▋ | 491/569 [00:10<00:01, 49.41it/s]

→ 2000R Phase 3: finalize:  87%|████████▋ | 496/569 [00:10<00:01, 49.48it/s]

→ 2000R Phase 3: finalize:  88%|████████▊ | 501/569 [00:10<00:01, 49.48it/s]

→ 2000R Phase 3: finalize:  89%|████████▉ | 506/569 [00:10<00:01, 49.61it/s]

→ 2000R Phase 3: finalize:  90%|████████▉ | 511/569 [00:10<00:01, 49.68it/s]

→ 2000R Phase 3: finalize:  91%|█████████ | 516/569 [00:10<00:01, 49.75it/s]

→ 2000R Phase 3: finalize:  92%|█████████▏| 521/569 [00:10<00:00, 49.39it/s]

→ 2000R Phase 3: finalize:  92%|█████████▏| 526/569 [00:10<00:00, 49.04it/s]

→ 2000R Phase 3: finalize:  93%|█████████▎| 531/569 [00:10<00:00, 49.32it/s]

→ 2000R Phase 3: finalize:  94%|█████████▍| 537/569 [00:10<00:00, 49.94it/s]

→ 2000R Phase 3: finalize:  95%|█████████▌| 542/569 [00:11<00:00, 49.55it/s]

→ 2000R Phase 3: finalize:  96%|█████████▌| 547/569 [00:11<00:00, 49.14it/s]

→ 2000R Phase 3: finalize:  97%|█████████▋| 553/569 [00:11<00:00, 49.54it/s]

→ 2000R Phase 3: finalize:  98%|█████████▊| 558/569 [00:11<00:00, 48.92it/s]

→ 2000R Phase 3: finalize:  99%|█████████▉| 565/569 [00:11<00:00, 51.93it/s]

                                                                            
[TIMING] 2000R — 570 frames
  Phase 1  radial detect   (parallel)  :   8.70s  (15.3 ms/frame)
  Phase 2a corner detect   (parallel)  :   4.24s  (7.5 ms/frame)
  Phase 2b corner fix      (sequential):   0.77s
  Phase 3  finalize        (sequential):  11.60s  (20.4 ms/frame)
    decode + undistort                 :   6.18s  (10.8 ms/frame)
    corner apply + refinement          :   2.57s  (4.5 ms/frame)
    segment                            :   2.31s  (4.1 ms/frame)
    smooth                             :   0.34s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  25.32s


Processing Rigs:  25%|██▌       | 1/4 [00:29<01:29, 29.96s/it][INFO] Filtered 384 stationary frames, 491 remain


→ 1500 (491 images) Phase 1:   0%|          | 0/491 [00:00<?, ?it/s]

→ 1500 (491 images) Phase 1:   0%|          | 1/491 [00:00<05:02,  1.62it/s]

→ 1500 (491 images) Phase 1:   0%|          | 2/491 [00:00<02:40,  3.04it/s]

→ 1500 (491 images) Phase 1:   4%|▎         | 18/491 [00:00<00:13, 34.95it/s]

→ 1500 (491 images) Phase 1:   7%|▋         | 33/491 [00:01<00:09, 46.77it/s]

→ 1500 (491 images) Phase 1:   8%|▊         | 41/491 [00:01<00:10, 44.21it/s]

→ 1500 (491 images) Phase 1:  13%|█▎        | 65/491 [00:01<00:06, 66.77it/s]

→ 1500 (491 images) Phase 1:  15%|█▍        | 73/491 [00:01<00:07, 54.33it/s]

→ 1500 (491 images) Phase 1:  20%|█▉        | 97/491 [00:01<00:05, 72.65it/s]

→ 1500 (491 images) Phase 1:  21%|██▏       | 105/491 [00:02<00:06, 59.82it/s]

→ 1500 (491 images) Phase 1:  26%|██▌       | 127/491 [00:02<00:04, 86.16it/s]

→ 1500 (491 images) Phase 1:  28%|██▊       | 139/491 [00:02<00:05, 60.60it/s]

→ 1500 (491 images) Phase 1:  33%|███▎      | 161/491 [00:02<00:04, 73.65it/s]

→ 1500 (491 images) Phase 1:  35%|███▍      | 171/491 [00:03<00:05, 62.22it/s]

→ 1500 (491 images) Phase 1:  39%|███▊      | 190/491 [00:03<00:03, 81.69it/s]

→ 1500 (491 images) Phase 1:  41%|████      | 202/491 [00:03<00:04, 60.76it/s]

→ 1500 (491 images) Phase 1:  44%|████▍     | 218/491 [00:03<00:03, 75.16it/s]

→ 1500 (491 images) Phase 1:  47%|████▋     | 229/491 [00:04<00:04, 58.69it/s]

→ 1500 (491 images) Phase 1:  49%|████▉     | 241/491 [00:04<00:03, 67.14it/s]

→ 1500 (491 images) Phase 1:  52%|█████▏    | 256/491 [00:04<00:02, 81.01it/s]

→ 1500 (491 images) Phase 1:  54%|█████▍    | 267/491 [00:04<00:03, 63.17it/s]

→ 1500 (491 images) Phase 1:  57%|█████▋    | 281/491 [00:04<00:02, 75.46it/s]

→ 1500 (491 images) Phase 1:  59%|█████▉    | 291/491 [00:04<00:03, 54.50it/s]

→ 1500 (491 images) Phase 1:  62%|██████▏   | 302/491 [00:05<00:02, 63.07it/s]

→ 1500 (491 images) Phase 1:  64%|██████▍   | 315/491 [00:05<00:02, 73.72it/s]

→ 1500 (491 images) Phase 1:  66%|██████▌   | 325/491 [00:05<00:03, 54.55it/s]

→ 1500 (491 images) Phase 1:  69%|██████▊   | 337/491 [00:05<00:02, 65.08it/s]

→ 1500 (491 images) Phase 1:  71%|███████▏  | 351/491 [00:05<00:01, 77.75it/s]

→ 1500 (491 images) Phase 1:  74%|███████▎  | 361/491 [00:05<00:02, 61.37it/s]

→ 1500 (491 images) Phase 1:  76%|███████▌  | 371/491 [00:06<00:01, 67.05it/s]

→ 1500 (491 images) Phase 1:  78%|███████▊  | 385/491 [00:06<00:01, 76.11it/s]

→ 1500 (491 images) Phase 1:  80%|████████  | 394/491 [00:06<00:01, 61.05it/s]

→ 1500 (491 images) Phase 1:  83%|████████▎ | 407/491 [00:06<00:01, 74.15it/s]

→ 1500 (491 images) Phase 1:  85%|████████▍ | 417/491 [00:06<00:00, 75.24it/s]

→ 1500 (491 images) Phase 1:  87%|████████▋ | 426/491 [00:06<00:01, 61.58it/s]

→ 1500 (491 images) Phase 1:  89%|████████▉ | 436/491 [00:07<00:00, 69.27it/s]

→ 1500 (491 images) Phase 1:  91%|█████████▏| 449/491 [00:07<00:00, 77.04it/s]

→ 1500 (491 images) Phase 1:  93%|█████████▎| 458/491 [00:07<00:00, 61.46it/s]

→ 1500 (491 images) Phase 1:  96%|█████████▌| 470/491 [00:07<00:00, 71.75it/s]

→ 1500 (491 images) Phase 1:  98%|█████████▊| 482/491 [00:07<00:00, 77.62it/s]

                                                                              

→ 1500 Phase 2: corners:   0%|          | 0/490 [00:00<?, ?it/s]

→ 1500 Phase 2: corners:   0%|          | 1/490 [00:00<03:05,  2.63it/s]

→ 1500 Phase 2: corners:   3%|▎         | 16/490 [00:00<00:11, 42.86it/s]

→ 1500 Phase 2: corners:   6%|▌         | 27/490 [00:00<00:07, 59.75it/s]

→ 1500 Phase 2: corners:   9%|▉         | 43/490 [00:00<00:05, 85.26it/s]

→ 1500 Phase 2: corners:  12%|█▏        | 59/490 [00:00<00:04, 104.25it/s]

→ 1500 Phase 2: corners:  15%|█▍        | 72/490 [00:00<00:04, 104.45it/s]

→ 1500 Phase 2: corners:  17%|█▋        | 84/490 [00:01<00:03, 104.76it/s]

→ 1500 Phase 2: corners:  20%|█▉        | 96/490 [00:01<00:03, 105.48it/s]

→ 1500 Phase 2: corners:  22%|██▏       | 110/490 [00:01<00:03, 112.11it/s]

→ 1500 Phase 2: corners:  26%|██▌       | 126/490 [00:01<00:02, 123.50it/s]

→ 1500 Phase 2: corners:  30%|███       | 148/490 [00:01<00:02, 148.68it/s]

→ 1500 Phase 2: corners:  33%|███▎      | 164/490 [00:01<00:02, 148.95it/s]

→ 1500 Phase 2: corners:  37%|███▋      | 180/490 [00:01<00:02, 130.59it/s]

→ 1500 Phase 2: corners:  40%|███▉      | 194/490 [00:01<00:02, 132.11it/s]

→ 1500 Phase 2: corners:  43%|████▎     | 210/490 [00:01<00:02, 135.42it/s]

→ 1500 Phase 2: corners:  46%|████▌     | 224/490 [00:02<00:02, 132.39it/s]

→ 1500 Phase 2: corners:  49%|████▉     | 241/490 [00:02<00:01, 141.89it/s]

→ 1500 Phase 2: corners:  53%|█████▎    | 258/490 [00:02<00:01, 148.46it/s]

→ 1500 Phase 2: corners:  56%|█████▌    | 274/490 [00:02<00:01, 147.35it/s]

→ 1500 Phase 2: corners:  59%|█████▉    | 289/490 [00:02<00:01, 142.25it/s]

→ 1500 Phase 2: corners:  62%|██████▏   | 304/490 [00:02<00:01, 117.25it/s]

→ 1500 Phase 2: corners:  66%|██████▌   | 321/490 [00:02<00:01, 128.43it/s]

→ 1500 Phase 2: corners:  68%|██████▊   | 335/490 [00:02<00:01, 130.77it/s]

→ 1500 Phase 2: corners:  72%|███████▏  | 352/490 [00:02<00:00, 140.51it/s]

→ 1500 Phase 2: corners:  75%|███████▍  | 367/490 [00:03<00:00, 135.38it/s]

→ 1500 Phase 2: corners:  78%|███████▊  | 382/490 [00:03<00:00, 138.72it/s]

→ 1500 Phase 2: corners:  81%|████████▏ | 399/490 [00:03<00:00, 145.54it/s]

→ 1500 Phase 2: corners:  84%|████████▍ | 414/490 [00:03<00:00, 145.95it/s]

→ 1500 Phase 2: corners:  88%|████████▊ | 430/490 [00:03<00:00, 149.76it/s]

→ 1500 Phase 2: corners:  91%|█████████ | 446/490 [00:03<00:00, 145.63it/s]

→ 1500 Phase 2: corners:  95%|█████████▍| 465/490 [00:03<00:00, 156.72it/s]

→ 1500 Phase 2: corners: 100%|██████████| 490/490 [00:03<00:00, 176.80it/s]

                                                                           [PASS2] Frame 0000445: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000930: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000931: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000932: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0000930: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000931: fixed corners {1} (was_fixed=True, trusted=False)
[PASS2] Frame 0000930: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000931: fixed corners {1} (was_fixed=True, trusted=False)
[PASS2] Summary: 3 frames fixed, 33 untrusted, 490 total


→ 1500 Phase 3: finalize:   0%|          | 0/490 [00:00<?, ?it/s]

→ 1500 Phase 3: finalize:   1%|          | 6/490 [00:00<00:09, 51.97it/s]

→ 1500 Phase 3: finalize:   2%|▏         | 12/490 [00:00<00:09, 52.53it/s]

→ 1500 Phase 3: finalize:   4%|▎         | 18/490 [00:00<00:08, 53.63it/s]

→ 1500 Phase 3: finalize:   5%|▍         | 24/490 [00:00<00:08, 55.24it/s]

→ 1500 Phase 3: finalize:   6%|▌         | 30/490 [00:00<00:08, 54.49it/s]

→ 1500 Phase 3: finalize:   7%|▋         | 36/490 [00:00<00:08, 54.16it/s]

→ 1500 Phase 3: finalize:   9%|▊         | 42/490 [00:00<00:08, 53.73it/s]

→ 1500 Phase 3: finalize:  10%|▉         | 48/490 [00:00<00:08, 53.64it/s]

→ 1500 Phase 3: finalize:  11%|█         | 54/490 [00:01<00:08, 53.76it/s]

→ 1500 Phase 3: finalize:  12%|█▏        | 60/490 [00:01<00:07, 53.92it/s]

→ 1500 Phase 3: finalize:  13%|█▎        | 66/490 [00:01<00:07, 53.88it/s]

→ 1500 Phase 3: finalize:  15%|█▍        | 72/490 [00:01<00:07, 54.11it/s]

→ 1500 Phase 3: finalize:  16%|█▌        | 78/490 [00:01<00:07, 52.79it/s]

→ 1500 Phase 3: finalize:  17%|█▋        | 84/490 [00:01<00:07, 51.72it/s]

→ 1500 Phase 3: finalize:  18%|█▊        | 90/490 [00:01<00:07, 50.92it/s]

→ 1500 Phase 3: finalize:  20%|█▉        | 96/490 [00:01<00:07, 50.58it/s]

→ 1500 Phase 3: finalize:  21%|██        | 102/490 [00:01<00:07, 50.37it/s]

→ 1500 Phase 3: finalize:  22%|██▏       | 108/490 [00:02<00:07, 50.04it/s]

→ 1500 Phase 3: finalize:  23%|██▎       | 114/490 [00:02<00:07, 50.17it/s]

→ 1500 Phase 3: finalize:  24%|██▍       | 120/490 [00:02<00:07, 49.94it/s]

→ 1500 Phase 3: finalize:  26%|██▌       | 126/490 [00:02<00:07, 50.07it/s]

→ 1500 Phase 3: finalize:  27%|██▋       | 132/490 [00:02<00:07, 50.22it/s]

→ 1500 Phase 3: finalize:  28%|██▊       | 138/490 [00:02<00:07, 49.90it/s]

→ 1500 Phase 3: finalize:  29%|██▉       | 143/490 [00:02<00:06, 49.81it/s]

→ 1500 Phase 3: finalize:  30%|███       | 148/490 [00:02<00:06, 49.62it/s]

→ 1500 Phase 3: finalize:  31%|███       | 153/490 [00:02<00:06, 49.42it/s]

→ 1500 Phase 3: finalize:  32%|███▏      | 158/490 [00:03<00:06, 49.11it/s]

→ 1500 Phase 3: finalize:  33%|███▎      | 163/490 [00:03<00:06, 48.99it/s]

→ 1500 Phase 3: finalize:  34%|███▍      | 168/490 [00:03<00:06, 48.87it/s]

→ 1500 Phase 3: finalize:  35%|███▌      | 173/490 [00:03<00:06, 48.86it/s]

→ 1500 Phase 3: finalize:  36%|███▋      | 178/490 [00:03<00:06, 48.90it/s]

→ 1500 Phase 3: finalize:  37%|███▋      | 183/490 [00:03<00:06, 49.14it/s]

→ 1500 Phase 3: finalize:  38%|███▊      | 188/490 [00:03<00:06, 49.10it/s]

→ 1500 Phase 3: finalize:  40%|███▉      | 194/490 [00:03<00:05, 49.71it/s]

→ 1500 Phase 3: finalize:  41%|████      | 200/490 [00:03<00:05, 50.15it/s]

→ 1500 Phase 3: finalize:  42%|████▏     | 206/490 [00:04<00:05, 50.38it/s]

→ 1500 Phase 3: finalize:  43%|████▎     | 212/490 [00:04<00:05, 50.58it/s]

→ 1500 Phase 3: finalize:  44%|████▍     | 218/490 [00:04<00:05, 50.69it/s]

→ 1500 Phase 3: finalize:  46%|████▌     | 224/490 [00:04<00:05, 50.80it/s]

→ 1500 Phase 3: finalize:  47%|████▋     | 230/490 [00:04<00:05, 50.77it/s]

→ 1500 Phase 3: finalize:  48%|████▊     | 236/490 [00:04<00:05, 50.59it/s]

→ 1500 Phase 3: finalize:  49%|████▉     | 242/490 [00:04<00:04, 50.51it/s]

→ 1500 Phase 3: finalize:  51%|█████     | 248/490 [00:04<00:04, 50.75it/s]

→ 1500 Phase 3: finalize:  52%|█████▏    | 254/490 [00:04<00:04, 50.85it/s]

→ 1500 Phase 3: finalize:  53%|█████▎    | 260/490 [00:05<00:04, 50.58it/s]

→ 1500 Phase 3: finalize:  54%|█████▍    | 266/490 [00:05<00:04, 50.91it/s]

→ 1500 Phase 3: finalize:  56%|█████▌    | 272/490 [00:05<00:04, 50.90it/s]

→ 1500 Phase 3: finalize:  57%|█████▋    | 278/490 [00:05<00:04, 50.70it/s]

→ 1500 Phase 3: finalize:  58%|█████▊    | 284/490 [00:05<00:04, 50.47it/s]

→ 1500 Phase 3: finalize:  59%|█████▉    | 290/490 [00:05<00:03, 50.27it/s]

→ 1500 Phase 3: finalize:  60%|██████    | 296/490 [00:05<00:03, 50.26it/s]

→ 1500 Phase 3: finalize:  62%|██████▏   | 302/490 [00:05<00:03, 50.29it/s]

→ 1500 Phase 3: finalize:  63%|██████▎   | 308/490 [00:06<00:03, 50.22it/s]

→ 1500 Phase 3: finalize:  64%|██████▍   | 314/490 [00:06<00:03, 50.25it/s]

→ 1500 Phase 3: finalize:  65%|██████▌   | 320/490 [00:06<00:03, 50.17it/s]

→ 1500 Phase 3: finalize:  67%|██████▋   | 326/490 [00:06<00:03, 49.82it/s]

→ 1500 Phase 3: finalize:  68%|██████▊   | 331/490 [00:06<00:03, 49.39it/s]

→ 1500 Phase 3: finalize:  69%|██████▊   | 336/490 [00:06<00:03, 49.09it/s]

→ 1500 Phase 3: finalize:  70%|██████▉   | 341/490 [00:06<00:03, 48.85it/s]

→ 1500 Phase 3: finalize:  71%|███████   | 346/490 [00:06<00:02, 48.67it/s]

→ 1500 Phase 3: finalize:  72%|███████▏  | 351/490 [00:06<00:02, 48.49it/s]

→ 1500 Phase 3: finalize:  73%|███████▎  | 356/490 [00:07<00:02, 48.70it/s]

→ 1500 Phase 3: finalize:  74%|███████▍  | 362/490 [00:07<00:02, 49.34it/s]

→ 1500 Phase 3: finalize:  75%|███████▌  | 368/490 [00:07<00:02, 49.66it/s]

→ 1500 Phase 3: finalize:  76%|███████▋  | 374/490 [00:07<00:02, 49.92it/s]

→ 1500 Phase 3: finalize:  78%|███████▊  | 380/490 [00:07<00:02, 50.06it/s]

→ 1500 Phase 3: finalize:  79%|███████▉  | 386/490 [00:07<00:02, 49.81it/s]

→ 1500 Phase 3: finalize:  80%|███████▉  | 391/490 [00:07<00:01, 49.74it/s]

→ 1500 Phase 3: finalize:  81%|████████  | 396/490 [00:07<00:01, 49.71it/s]

→ 1500 Phase 3: finalize:  82%|████████▏ | 401/490 [00:07<00:01, 49.71it/s]

→ 1500 Phase 3: finalize:  83%|████████▎ | 407/490 [00:08<00:01, 49.82it/s]

→ 1500 Phase 3: finalize:  84%|████████▍ | 413/490 [00:08<00:01, 49.90it/s]

→ 1500 Phase 3: finalize:  86%|████████▌ | 419/490 [00:08<00:01, 50.00it/s]

→ 1500 Phase 3: finalize:  87%|████████▋ | 424/490 [00:08<00:01, 49.96it/s]

→ 1500 Phase 3: finalize:  88%|████████▊ | 429/490 [00:08<00:01, 49.88it/s]

→ 1500 Phase 3: finalize:  89%|████████▊ | 434/490 [00:08<00:01, 49.83it/s]

→ 1500 Phase 3: finalize:  90%|████████▉ | 439/490 [00:08<00:01, 49.73it/s]

→ 1500 Phase 3: finalize:  91%|█████████ | 444/490 [00:08<00:00, 49.73it/s]

→ 1500 Phase 3: finalize:  92%|█████████▏| 449/490 [00:08<00:00, 49.67it/s]

→ 1500 Phase 3: finalize:  93%|█████████▎| 455/490 [00:09<00:00, 49.82it/s]

→ 1500 Phase 3: finalize:  94%|█████████▍| 461/490 [00:09<00:00, 49.88it/s]

→ 1500 Phase 3: finalize:  95%|█████████▌| 467/490 [00:09<00:00, 49.96it/s]

→ 1500 Phase 3: finalize:  96%|█████████▋| 472/490 [00:09<00:00, 49.80it/s]

→ 1500 Phase 3: finalize:  97%|█████████▋| 477/490 [00:09<00:00, 49.60it/s]

→ 1500 Phase 3: finalize:  99%|█████████▊| 483/490 [00:09<00:00, 50.66it/s]

→ 1500 Phase 3: finalize: 100%|█████████▉| 489/490 [00:09<00:00, 51.10it/s]

                                                                           
[TIMING] 1500 — 491 frames
  Phase 1  radial detect   (parallel)  :   7.83s  (15.9 ms/frame)
  Phase 2a corner detect   (parallel)  :   3.94s  (8.0 ms/frame)
  Phase 2b corner fix      (sequential):   0.38s
  Phase 3  finalize        (sequential):   9.71s  (19.8 ms/frame)
    decode + undistort                 :   5.21s  (10.6 ms/frame)
    corner apply + refinement          :   1.99s  (4.0 ms/frame)
    segment                            :   2.00s  (4.1 ms/frame)
    smooth                             :   0.35s  (0.7 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  21.85s


Processing Rigs:  50%|█████     | 2/4 [00:55<00:55, 27.55s/it][INFO] Filtered 437 stationary frames, 590 remain


→ 2000L (590 images) Phase 1:   0%|          | 0/590 [00:00<?, ?it/s]

→ 2000L (590 images) Phase 1:   0%|          | 1/590 [00:00<06:41,  1.47it/s]

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→ 2000L (590 images) Phase 1:  28%|██▊       | 168/590 [00:03<00:06, 64.48it/s]

→ 2000L (590 images) Phase 1:  33%|███▎      | 192/590 [00:03<00:04, 93.21it/s]

→ 2000L (590 images) Phase 1:  35%|███▍      | 204/590 [00:03<00:06, 62.96it/s]

→ 2000L (590 images) Phase 1:  38%|███▊      | 225/590 [00:03<00:05, 68.53it/s]

→ 2000L (590 images) Phase 1:  40%|███▉      | 234/590 [00:04<00:05, 62.21it/s]

→ 2000L (590 images) Phase 1:  43%|████▎     | 254/590 [00:04<00:04, 81.47it/s]

→ 2000L (590 images) Phase 1:  45%|████▍     | 265/590 [00:04<00:05, 58.50it/s]

→ 2000L (590 images) Phase 1:  48%|████▊     | 286/590 [00:04<00:03, 76.67it/s]

→ 2000L (590 images) Phase 1:  50%|█████     | 297/590 [00:05<00:04, 58.80it/s]

→ 2000L (590 images) Phase 1:  54%|█████▍    | 318/590 [00:05<00:03, 78.53it/s]

→ 2000L (590 images) Phase 1:  56%|█████▌    | 330/590 [00:05<00:04, 59.82it/s]

→ 2000L (590 images) Phase 1:  59%|█████▉    | 350/590 [00:05<00:03, 78.91it/s]

→ 2000L (590 images) Phase 1:  61%|██████▏   | 362/590 [00:06<00:03, 59.87it/s]

→ 2000L (590 images) Phase 1:  65%|██████▍   | 381/590 [00:06<00:02, 78.25it/s]

→ 2000L (590 images) Phase 1:  67%|██████▋   | 393/590 [00:06<00:03, 61.53it/s]

→ 2000L (590 images) Phase 1:  69%|██████▉   | 406/590 [00:06<00:02, 71.33it/s]

→ 2000L (590 images) Phase 1:  71%|███████   | 417/590 [00:06<00:02, 66.05it/s]

→ 2000L (590 images) Phase 1:  72%|███████▏  | 426/590 [00:06<00:02, 61.87it/s]

→ 2000L (590 images) Phase 1:  74%|███████▍  | 439/590 [00:07<00:02, 73.78it/s]

→ 2000L (590 images) Phase 1:  76%|███████▌  | 449/590 [00:07<00:02, 63.71it/s]

→ 2000L (590 images) Phase 1:  77%|███████▋  | 457/590 [00:07<00:02, 63.52it/s]

→ 2000L (590 images) Phase 1:  79%|███████▉  | 469/590 [00:07<00:01, 73.60it/s]

→ 2000L (590 images) Phase 1:  81%|████████  | 478/590 [00:07<00:01, 69.24it/s]

→ 2000L (590 images) Phase 1:  82%|████████▏ | 486/590 [00:07<00:01, 57.70it/s]

→ 2000L (590 images) Phase 1:  84%|████████▍ | 496/590 [00:07<00:01, 64.92it/s]

→ 2000L (590 images) Phase 1:  86%|████████▌ | 508/590 [00:08<00:01, 76.37it/s]

→ 2000L (590 images) Phase 1:  88%|████████▊ | 517/590 [00:08<00:01, 60.85it/s]

→ 2000L (590 images) Phase 1:  89%|████████▉ | 525/590 [00:08<00:01, 62.28it/s]

→ 2000L (590 images) Phase 1:  91%|█████████ | 537/590 [00:08<00:00, 74.28it/s]

→ 2000L (590 images) Phase 1:  93%|█████████▎| 546/590 [00:08<00:00, 61.54it/s]

→ 2000L (590 images) Phase 1:  94%|█████████▍| 554/590 [00:08<00:00, 63.59it/s]

→ 2000L (590 images) Phase 1:  96%|█████████▌| 565/590 [00:08<00:00, 73.92it/s]

→ 2000L (590 images) Phase 1:  97%|█████████▋| 575/590 [00:09<00:00, 74.79it/s]

→ 2000L (590 images) Phase 1:  99%|█████████▉| 584/590 [00:09<00:00, 74.69it/s]

                                                                               

→ 2000L Phase 2: corners:   0%|          | 0/589 [00:00<?, ?it/s]

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→ 2000L Phase 2: corners:  15%|█▍        | 88/589 [00:01<00:04, 106.02it/s]

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→ 2000L Phase 2: corners:  26%|██▋       | 156/589 [00:01<00:03, 122.63it/s]

→ 2000L Phase 2: corners:  29%|██▉       | 170/589 [00:01<00:03, 124.94it/s]

→ 2000L Phase 2: corners:  31%|███       | 183/589 [00:01<00:03, 126.29it/s]

→ 2000L Phase 2: corners:  33%|███▎      | 196/589 [00:02<00:03, 124.65it/s]

→ 2000L Phase 2: corners:  35%|███▌      | 209/589 [00:02<00:03, 124.14it/s]

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→ 2000L Phase 2: corners:  41%|████      | 240/589 [00:02<00:02, 134.34it/s]

→ 2000L Phase 2: corners:  43%|████▎     | 256/589 [00:02<00:02, 139.66it/s]

→ 2000L Phase 2: corners:  46%|████▌     | 271/589 [00:02<00:02, 138.85it/s]

→ 2000L Phase 2: corners:  49%|████▉     | 289/589 [00:02<00:02, 149.19it/s]

→ 2000L Phase 2: corners:  52%|█████▏    | 307/589 [00:02<00:01, 154.33it/s]

→ 2000L Phase 2: corners:  55%|█████▍    | 323/589 [00:02<00:01, 147.40it/s]

→ 2000L Phase 2: corners:  57%|█████▋    | 338/589 [00:03<00:01, 144.70it/s]

→ 2000L Phase 2: corners:  60%|██████    | 354/589 [00:03<00:01, 147.29it/s]

→ 2000L Phase 2: corners:  63%|██████▎   | 369/589 [00:03<00:01, 146.53it/s]

→ 2000L Phase 2: corners:  65%|██████▌   | 384/589 [00:03<00:01, 143.18it/s]

→ 2000L Phase 2: corners:  68%|██████▊   | 403/589 [00:03<00:01, 154.80it/s]

→ 2000L Phase 2: corners:  71%|███████▏  | 421/589 [00:03<00:01, 161.58it/s]

→ 2000L Phase 2: corners:  75%|███████▍  | 439/589 [00:03<00:00, 164.14it/s]

→ 2000L Phase 2: corners:  77%|███████▋  | 456/589 [00:03<00:00, 163.76it/s]

→ 2000L Phase 2: corners:  80%|████████  | 473/589 [00:03<00:00, 153.29it/s]

→ 2000L Phase 2: corners:  83%|████████▎ | 490/589 [00:03<00:00, 155.60it/s]

→ 2000L Phase 2: corners:  86%|████████▌ | 506/589 [00:04<00:00, 156.55it/s]

→ 2000L Phase 2: corners:  89%|████████▊ | 522/589 [00:04<00:00, 150.64it/s]

→ 2000L Phase 2: corners:  91%|█████████▏| 538/589 [00:04<00:00, 149.55it/s]

→ 2000L Phase 2: corners:  94%|█████████▍| 555/589 [00:04<00:00, 152.43it/s]

→ 2000L Phase 2: corners:  97%|█████████▋| 571/589 [00:04<00:00, 154.39it/s]

                                                                            [PASS2] Frame 0000233: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000338: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000339: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000340: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000341: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000635: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000686: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000687: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000688: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000689: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000690: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000692: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000693: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000694: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000695: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000696: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000697: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000698: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000736: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000737: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000738: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000739: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000741: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000742: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000743: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000745: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000746: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000747: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000749: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000820: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000822: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000824: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000865: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000866: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000867: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000868: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001239: fixed corners {1} (was_fixed=True, trusted=False)
[PASS2] Frame 0001240: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0000233: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000689: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000697: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000738: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000743: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000744: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000747: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001149: fixed corners {1, 2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001239: fixed corners {1} (was_fixed=True, trusted=False)
[PASS2] Frame 0000233: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0001149: fixed corners {1, 2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001239: fixed corners {1} (was_fixed=True, trusted=False)
[PASS2] Summary: 21 frames fixed, 44 untrusted, 589 total


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→ 2000L Phase 3: finalize:  72%|███████▏  | 427/589 [00:08<00:03, 48.28it/s]

→ 2000L Phase 3: finalize:  73%|███████▎  | 432/589 [00:08<00:03, 48.50it/s]

→ 2000L Phase 3: finalize:  74%|███████▍  | 437/589 [00:08<00:03, 48.28it/s]

→ 2000L Phase 3: finalize:  75%|███████▌  | 442/589 [00:09<00:03, 47.87it/s]

→ 2000L Phase 3: finalize:  76%|███████▌  | 447/589 [00:09<00:02, 47.93it/s]

→ 2000L Phase 3: finalize:  77%|███████▋  | 452/589 [00:09<00:02, 48.22it/s]

→ 2000L Phase 3: finalize:  78%|███████▊  | 457/589 [00:09<00:02, 48.28it/s]

→ 2000L Phase 3: finalize:  78%|███████▊  | 462/589 [00:09<00:02, 48.50it/s]

→ 2000L Phase 3: finalize:  79%|███████▉  | 467/589 [00:09<00:02, 48.24it/s]

→ 2000L Phase 3: finalize:  80%|████████  | 472/589 [00:09<00:02, 48.15it/s]

→ 2000L Phase 3: finalize:  81%|████████  | 477/589 [00:09<00:02, 48.43it/s]

→ 2000L Phase 3: finalize:  82%|████████▏ | 482/589 [00:09<00:02, 48.49it/s]

→ 2000L Phase 3: finalize:  83%|████████▎ | 487/589 [00:09<00:02, 48.63it/s]

→ 2000L Phase 3: finalize:  84%|████████▎ | 492/589 [00:10<00:01, 48.83it/s]

→ 2000L Phase 3: finalize:  84%|████████▍ | 497/589 [00:10<00:01, 49.02it/s]

→ 2000L Phase 3: finalize:  85%|████████▌ | 502/589 [00:10<00:01, 49.21it/s]

→ 2000L Phase 3: finalize:  86%|████████▌ | 507/589 [00:10<00:01, 49.20it/s]

→ 2000L Phase 3: finalize:  87%|████████▋ | 512/589 [00:10<00:01, 49.17it/s]

→ 2000L Phase 3: finalize:  88%|████████▊ | 517/589 [00:10<00:01, 49.33it/s]

→ 2000L Phase 3: finalize:  89%|████████▊ | 522/589 [00:10<00:01, 49.32it/s]

→ 2000L Phase 3: finalize:  89%|████████▉ | 527/589 [00:10<00:01, 49.42it/s]

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→ 2000L Phase 3: finalize:  91%|█████████ | 537/589 [00:11<00:01, 49.06it/s]

→ 2000L Phase 3: finalize:  92%|█████████▏| 542/589 [00:11<00:00, 48.60it/s]

→ 2000L Phase 3: finalize:  93%|█████████▎| 547/589 [00:11<00:00, 48.09it/s]

→ 2000L Phase 3: finalize:  94%|█████████▎| 552/589 [00:11<00:00, 48.00it/s]

→ 2000L Phase 3: finalize:  95%|█████████▍| 557/589 [00:11<00:00, 47.96it/s]

→ 2000L Phase 3: finalize:  95%|█████████▌| 562/589 [00:11<00:00, 48.15it/s]

→ 2000L Phase 3: finalize:  96%|█████████▋| 567/589 [00:11<00:00, 48.06it/s]

→ 2000L Phase 3: finalize:  97%|█████████▋| 573/589 [00:11<00:00, 49.27it/s]

→ 2000L Phase 3: finalize:  98%|█████████▊| 580/589 [00:11<00:00, 53.66it/s]

[TIMING] 2000L — 590 frames
  Phase 1  radial detect   (parallel)  :   9.38s  (15.9 ms/frame)
  Phase 2a corner detect   (parallel)  :   4.64s  (7.9 ms/frame)
  Phase 2b corner fix      (sequential):   1.18s
  Phase 3  finalize        (sequential):  12.00s  (20.3 ms/frame)
    decode + undistort                 :   6.34s  (10.7 ms/frame)
    corner apply + refinement          :   2.71s  (4.6 ms/frame)
    segment                            :   2.40s  (4.1 ms/frame)
    smooth                             :   0.34s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  27.20s


→ 2000L Phase 3: finalize: 100%|█████████▉| 587/589 [00:11<00:00, 56.24it/s]

                                                                            
Processing Rigs:  75%|███████▌  | 3/4 [01:27<00:29, 29.57s/it][INFO] Filtered 336 stationary frames, 283 remain


→ 1000 (283 images) Phase 1:   0%|          | 0/283 [00:00<?, ?it/s]

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→ 1000 (283 images) Phase 1:   6%|▌         | 16/283 [00:00<00:09, 28.59it/s]

→ 1000 (283 images) Phase 1:  12%|█▏        | 33/283 [00:01<00:05, 43.75it/s]

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→ 1000 (283 images) Phase 1:  23%|██▎       | 65/283 [00:01<00:03, 61.17it/s]

→ 1000 (283 images) Phase 1:  25%|██▌       | 72/283 [00:01<00:03, 53.55it/s]

→ 1000 (283 images) Phase 1:  34%|███▎      | 95/283 [00:01<00:02, 77.32it/s]

→ 1000 (283 images) Phase 1:  37%|███▋      | 104/283 [00:02<00:03, 47.94it/s]

→ 1000 (283 images) Phase 1:  46%|████▌     | 129/283 [00:02<00:02, 64.06it/s]

→ 1000 (283 images) Phase 1:  48%|████▊     | 137/283 [00:02<00:02, 55.19it/s]

→ 1000 (283 images) Phase 1:  57%|█████▋    | 161/283 [00:03<00:01, 70.23it/s]

→ 1000 (283 images) Phase 1:  60%|█████▉    | 169/283 [00:03<00:01, 58.78it/s]

→ 1000 (283 images) Phase 1:  67%|██████▋   | 190/283 [00:03<00:01, 80.92it/s]

→ 1000 (283 images) Phase 1:  71%|███████   | 201/283 [00:03<00:01, 58.65it/s]

→ 1000 (283 images) Phase 1:  77%|███████▋  | 218/283 [00:03<00:00, 74.30it/s]

→ 1000 (283 images) Phase 1:  81%|████████  | 229/283 [00:04<00:00, 58.85it/s]

→ 1000 (283 images) Phase 1:  87%|████████▋ | 246/283 [00:04<00:00, 75.04it/s]

→ 1000 (283 images) Phase 1:  91%|█████████ | 257/283 [00:04<00:00, 76.47it/s]

→ 1000 (283 images) Phase 1:  94%|█████████▍| 267/283 [00:04<00:00, 66.44it/s]

                                                                              

→ 1000 Phase 2: corners:   0%|          | 0/282 [00:00<?, ?it/s]

→ 1000 Phase 2: corners:   0%|          | 1/282 [00:00<02:18,  2.03it/s]

→ 1000 Phase 2: corners:   4%|▍         | 12/282 [00:00<00:10, 25.99it/s]

→ 1000 Phase 2: corners:   9%|▊         | 24/282 [00:00<00:05, 48.27it/s]

→ 1000 Phase 2: corners:  13%|█▎        | 37/282 [00:00<00:03, 67.18it/s]

→ 1000 Phase 2: corners:  19%|█▉        | 54/282 [00:00<00:02, 90.66it/s]

→ 1000 Phase 2: corners:  23%|██▎       | 66/282 [00:01<00:02, 78.59it/s]

→ 1000 Phase 2: corners:  28%|██▊       | 79/282 [00:01<00:02, 84.77it/s]

→ 1000 Phase 2: corners:  33%|███▎      | 92/282 [00:01<00:02, 91.78it/s]

→ 1000 Phase 2: corners:  41%|████      | 116/282 [00:01<00:01, 126.51it/s]

→ 1000 Phase 2: corners:  49%|████▉     | 138/282 [00:01<00:00, 149.29it/s]

→ 1000 Phase 2: corners:  55%|█████▍    | 155/282 [00:01<00:00, 128.75it/s]

→ 1000 Phase 2: corners:  61%|██████    | 172/282 [00:01<00:00, 135.20it/s]

→ 1000 Phase 2: corners:  67%|██████▋   | 188/282 [00:01<00:00, 138.27it/s]

→ 1000 Phase 2: corners:  73%|███████▎  | 207/282 [00:02<00:00, 150.09it/s]

→ 1000 Phase 2: corners:  79%|███████▉  | 223/282 [00:02<00:00, 142.30it/s]

→ 1000 Phase 2: corners:  85%|████████▌ | 241/282 [00:02<00:00, 152.17it/s]

→ 1000 Phase 2: corners:  91%|█████████▏| 258/282 [00:02<00:00, 151.64it/s]

→ 1000 Phase 2: corners:  99%|█████████▉| 280/282 [00:02<00:00, 169.03it/s]

                                                                           [PASS2] Frame 0000322: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 1 frames fixed, 16 untrusted, 282 total


→ 1000 Phase 3: finalize:   0%|          | 0/282 [00:00<?, ?it/s]

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→ 1000 Phase 3: finalize:  13%|█▎        | 38/282 [00:00<00:04, 57.38it/s]

→ 1000 Phase 3: finalize:  16%|█▌        | 44/282 [00:00<00:04, 56.69it/s]

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→ 1000 Phase 3: finalize:  22%|██▏       | 62/282 [00:01<00:04, 54.79it/s]

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→ 1000 Phase 3: finalize:  30%|███       | 86/282 [00:01<00:03, 51.38it/s]

→ 1000 Phase 3: finalize:  33%|███▎      | 92/282 [00:01<00:03, 51.13it/s]

→ 1000 Phase 3: finalize:  35%|███▍      | 98/282 [00:01<00:03, 50.86it/s]

→ 1000 Phase 3: finalize:  37%|███▋      | 104/282 [00:01<00:03, 50.83it/s]

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→ 1000 Phase 3: finalize:  41%|████      | 116/282 [00:02<00:03, 50.40it/s]

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→ 1000 Phase 3: finalize:  48%|████▊     | 134/282 [00:02<00:02, 51.77it/s]

→ 1000 Phase 3: finalize:  50%|████▉     | 140/282 [00:02<00:02, 52.06it/s]

→ 1000 Phase 3: finalize:  52%|█████▏    | 146/282 [00:02<00:02, 52.18it/s]

→ 1000 Phase 3: finalize:  54%|█████▍    | 152/282 [00:02<00:02, 51.77it/s]

→ 1000 Phase 3: finalize:  56%|█████▌    | 158/282 [00:02<00:02, 51.72it/s]

→ 1000 Phase 3: finalize:  58%|█████▊    | 164/282 [00:03<00:02, 51.06it/s]

→ 1000 Phase 3: finalize:  60%|██████    | 170/282 [00:03<00:02, 50.54it/s]

→ 1000 Phase 3: finalize:  62%|██████▏   | 176/282 [00:03<00:02, 50.25it/s]

→ 1000 Phase 3: finalize:  65%|██████▍   | 182/282 [00:03<00:01, 50.34it/s]

→ 1000 Phase 3: finalize:  67%|██████▋   | 188/282 [00:03<00:01, 50.42it/s]

→ 1000 Phase 3: finalize:  69%|██████▉   | 194/282 [00:03<00:01, 50.50it/s]

→ 1000 Phase 3: finalize:  71%|███████   | 200/282 [00:03<00:02, 38.56it/s]

→ 1000 Phase 3: finalize:  73%|███████▎  | 206/282 [00:04<00:01, 41.69it/s]

→ 1000 Phase 3: finalize:  75%|███████▌  | 212/282 [00:04<00:01, 44.12it/s]

→ 1000 Phase 3: finalize:  77%|███████▋  | 218/282 [00:04<00:01, 46.04it/s]

→ 1000 Phase 3: finalize:  79%|███████▉  | 224/282 [00:04<00:01, 47.46it/s]

→ 1000 Phase 3: finalize:  82%|████████▏ | 230/282 [00:04<00:01, 48.25it/s]

→ 1000 Phase 3: finalize:  84%|████████▎ | 236/282 [00:04<00:00, 48.98it/s]

→ 1000 Phase 3: finalize:  86%|████████▌ | 242/282 [00:04<00:00, 49.54it/s]

→ 1000 Phase 3: finalize:  88%|████████▊ | 248/282 [00:04<00:00, 49.95it/s]

→ 1000 Phase 3: finalize:  90%|█████████ | 254/282 [00:04<00:00, 50.26it/s]

→ 1000 Phase 3: finalize:  92%|█████████▏| 260/282 [00:05<00:00, 50.47it/s]

→ 1000 Phase 3: finalize:  94%|█████████▍| 266/282 [00:05<00:00, 50.51it/s]

→ 1000 Phase 3: finalize:  96%|█████████▋| 272/282 [00:05<00:00, 50.83it/s]

→ 1000 Phase 3: finalize:  99%|█████████▊| 278/282 [00:05<00:00, 52.25it/s]

                                                                           
[TIMING] 1000 — 283 frames
  Phase 1  radial detect   (parallel)  :   4.96s  (17.5 ms/frame)
  Phase 2a corner detect   (parallel)  :   2.67s  (9.5 ms/frame)
  Phase 2b corner fix      (sequential):   0.12s
  Phase 3  finalize        (sequential):   5.53s  (19.5 ms/frame)
    decode + undistort                 :   3.12s  (11.0 ms/frame)
    corner apply + refinement          :   1.01s  (3.6 ms/frame)
    segment                            :   1.12s  (3.9 ms/frame)
    smooth                             :   0.19s  (0.7 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  13.28s


Processing Rigs: 100%|██████████| 4/4 [01:43<00:00, 24.29s/it]
Processing Rigs: 100%|██████████| 4/4 [01:43<00:00, 26.00s/it]
[💾] Saved RigFrameDataset to /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 1930 frames from 4 rigs to /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 2000R: 100 frames selected from 569
[📋] 1500: 100 frames selected from 490
[📋] 2000L: 100 frames selected from 589
[📋] 1000: 100 frames selected from 282
[💾] Saved RigFrameDataset to /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDCP3D-SL-010_W046(6)_2026-04-09/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 [00:02<03:55,  2.98s/it]
Computing max image from bright frames:   2%|▎         | 2/80 [00:05<03:51,  2.96s/it]
Computing max image from bright frames:   4%|▍         | 3/80 [00:08<03:46,  2.94s/it]
Computing max image from bright frames:   5%|▌         | 4/80 [00:11<03:41,  2.91s/it]
Computing max image from bright frames:   6%|▋         | 5/80 [00:14<03:38,  2.91s/it]
Computing max image from bright frames:   8%|▊         | 6/80 [00:17<03:36,  2.92s/it]
Computing max image from bright frames:   9%|▉         | 7/80 [00:20<03:33,  2.93s/it]
Computing max image from bright frames:  10%|█         | 8/80 [00:23<03:31,  2.94s/it]
Computing max image from bright frames:  11%|█▏        | 9/80 [00:26<03:29,  2.96s/it]
Computing max image from bright frames:  12%|█▎        | 10/80 [00:29<03:26,  2.95s/it]
Computing max image from bright frames:  14%|█▍        | 11/80 [00:32<03:22,  2.94s/it]
Computing max image from bright frames:  15%|█▌        | 12/80 [00:34<03:10,  2.79s/it]
Computing max image from bright frames:  16%|█▋        | 13/80 [00:34<02:13,  2.00s/it]
Computing max image from bright frames:  18%|█▊        | 14/80 [00:35<01:35,  1.44s/it]
Computing max image from bright frames:  19%|█▉        | 15/80 [00:37<01:54,  1.76s/it]
Computing max image from bright frames:  20%|██        | 16/80 [00:40<02:14,  2.11s/it]
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Computing max image from bright frames:  22%|██▎       | 18/80 [00:46<02:37,  2.54s/it]
Computing max image from bright frames:  24%|██▍       | 19/80 [00:49<02:42,  2.66s/it]
Computing max image from bright frames:  25%|██▌       | 20/80 [00:52<02:44,  2.75s/it]
Computing max image from bright frames:  26%|██▋       | 21/80 [00:55<02:45,  2.81s/it]
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Computing max image from bright frames:  30%|███       | 24/80 [01:04<02:42,  2.90s/it]
Computing max image from bright frames:  31%|███▏      | 25/80 [01:07<02:40,  2.91s/it]
Computing max image from bright frames:  32%|███▎      | 26/80 [01:10<02:38,  2.93s/it]
Computing max image from bright frames:  34%|███▍      | 27/80 [01:12<02:35,  2.94s/it]
Computing max image from bright frames:  35%|███▌      | 28/80 [01:15<02:32,  2.94s/it]
Computing max image from bright frames:  36%|███▋      | 29/80 [01:18<02:21,  2.78s/it]
Computing max image from bright frames:  38%|███▊      | 30/80 [01:20<02:13,  2.68s/it]
Computing max image from bright frames:  39%|███▉      | 31/80 [01:23<02:09,  2.65s/it]
Computing max image from bright frames:  40%|████      | 32/80 [01:25<02:04,  2.60s/it]
Computing max image from bright frames:  41%|████▏     | 33/80 [01:28<02:01,  2.58s/it]
Computing max image from bright frames:  42%|████▎     | 34/80 [01:30<01:56,  2.54s/it]
Computing max image from bright frames:  44%|████▍     | 35/80 [01:33<02:00,  2.68s/it]
Computing max image from bright frames:  45%|████▌     | 36/80 [01:36<02:01,  2.76s/it]
Computing max image from bright frames:  46%|████▋     | 37/80 [01:39<02:01,  2.82s/it]
Computing max image from bright frames:  48%|████▊     | 38/80 [01:42<02:00,  2.87s/it]
Computing max image from bright frames:  49%|████▉     | 39/80 [01:45<01:59,  2.90s/it]
Computing max image from bright frames:  50%|█████     | 40/80 [01:48<01:57,  2.93s/it]
Computing max image from bright frames:  51%|█████▏    | 41/80 [01:51<01:55,  2.96s/it]
Computing max image from bright frames:  52%|█████▎    | 42/80 [01:54<01:52,  2.95s/it]
Computing max image from bright frames:  54%|█████▍    | 43/80 [01:57<01:49,  2.95s/it]
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Computing max image from bright frames:  56%|█████▋    | 45/80 [02:04<01:52,  3.22s/it]
Computing max image from bright frames:  57%|█████▊    | 46/80 [02:08<01:57,  3.46s/it]
Computing max image from bright frames:  59%|█████▉    | 47/80 [02:13<02:06,  3.82s/it]
Computing max image from bright frames:  60%|██████    | 48/80 [02:17<02:10,  4.09s/it]
Computing max image from bright frames:  61%|██████▏   | 49/80 [02:22<02:11,  4.26s/it]
Computing max image from bright frames:  62%|██████▎   | 50/80 [02:26<02:10,  4.33s/it]
Computing max image from bright frames:  64%|██████▍   | 51/80 [02:30<02:02,  4.23s/it]
Computing max image from bright frames:  65%|██████▌   | 52/80 [02:31<01:25,  3.04s/it]
Computing max image from bright frames:  66%|██████▋   | 53/80 [02:31<00:59,  2.20s/it]
Computing max image from bright frames:  68%|██████▊   | 54/80 [02:31<00:41,  1.61s/it]
Computing max image from bright frames:  69%|██████▉   | 55/80 [02:35<00:57,  2.31s/it]
Computing max image from bright frames:  70%|███████   | 56/80 [02:39<01:06,  2.79s/it]
Computing max image from bright frames:  71%|███████▏  | 57/80 [02:44<01:16,  3.34s/it]
Computing max image from bright frames:  72%|███████▎  | 58/80 [02:48<01:22,  3.74s/it]
Computing max image from bright frames:  74%|███████▍  | 59/80 [02:53<01:24,  4.03s/it]
Computing max image from bright frames:  75%|███████▌  | 60/80 [02:58<01:24,  4.22s/it]
Computing max image from bright frames:  76%|███████▋  | 61/80 [03:02<01:22,  4.35s/it]
Computing max image from bright frames:  78%|███████▊  | 62/80 [03:07<01:20,  4.46s/it]
Computing max image from bright frames:  79%|███████▉  | 63/80 [03:12<01:16,  4.51s/it]
Computing max image from bright frames:  80%|████████  | 64/80 [03:17<01:16,  4.77s/it]
Computing max image from bright frames:  81%|████████▏ | 65/80 [03:23<01:16,  5.07s/it]
Computing max image from bright frames:  82%|████████▎ | 66/80 [03:29<01:14,  5.29s/it]
Computing max image from bright frames:  84%|████████▍ | 67/80 [03:34<01:10,  5.45s/it]
Computing max image from bright frames:  85%|████████▌ | 68/80 [03:39<01:03,  5.26s/it]
Computing max image from bright frames:  86%|████████▋ | 69/80 [03:44<00:56,  5.11s/it]
Computing max image from bright frames:  88%|████████▊ | 70/80 [03:44<00:36,  3.67s/it]
Computing max image from bright frames:  89%|████████▉ | 71/80 [03:49<00:35,  3.95s/it]
Computing max image from bright frames:  90%|█████████ | 72/80 [03:53<00:33,  4.14s/it]
Computing max image from bright frames:  91%|█████████▏| 73/80 [03:58<00:29,  4.28s/it]
Computing max image from bright frames:  92%|█████████▎| 74/80 [04:03<00:26,  4.46s/it]
Computing max image from bright frames:  94%|█████████▍| 75/80 [04:07<00:21,  4.28s/it]
Computing max image from bright frames:  95%|█████████▌| 76/80 [04:10<00:15,  3.90s/it]
Computing max image from bright frames:  96%|█████████▋| 77/80 [04:13<00:10,  3.60s/it]
Computing max image from bright frames:  98%|█████████▊| 78/80 [04:16<00:06,  3.38s/it]
Computing max image from bright frames:  99%|█████████▉| 79/80 [04:19<00:03,  3.23s/it]
Computing max image from bright frames: 100%|██████████| 80/80 [04:21<00:00,  3.16s/it]
                                                                                       
[✅] Casing detection complete: cx=859.0, cy=990.0

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


  0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   1%|          | 1/100 [00:00<00:36,  2.70it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:36,  2.70it/s]  
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 321.212} (0.000):   2%|▏         | 2/100 [00:00<00:36,  2.70it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 321.212} (0.000):   3%|▎         | 3/100 [00:00<00:35,  2.70it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   4%|▍         | 4/100 [00:00<00:35,  2.70it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 342.424} (0.001):   5%|▌         | 5/100 [00:00<00:35,  2.70it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 349.495} (0.001):   6%|▌         | 6/100 [00:00<00:34,  2.70it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 349.495} (0.001):   7%|▋         | 7/100 [00:00<00:05, 17.18it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.002 | Best: {'fx': 363.636} (0.002):   7%|▋         | 7/100 [00:00<00:05, 17.18it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.002 | Best: {'fx': 370.707} (0.002):   8%|▊         | 8/100 [00:00<00:05, 17.18it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 370.707} (0.002):   9%|▉         | 9/100 [00:00<00:05, 17.18it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 370.707} (0.002):  10%|█         | 10/100 [00:00<00:04, 19.77it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 370.707} (0.002):  10%|█         | 10/100 [00:00<00:04, 19.77it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.002 | Best: {'fx': 377.778} (0.002):  11%|█         | 11/100 [00:00<00:04, 19.77it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 391.919} (0.004):  12%|█▏        | 12/100 [00:00<00:04, 19.77it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 391.919} (0.004):  13%|█▎        | 13/100 [00:00<00:03, 22.51it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 398.99} (0.004):  13%|█▎        | 13/100 [00:00<00:03, 22.51it/s] 
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.003 | Best: {'fx': 398.99} (0.004):  14%|█▍        | 14/100 [00:00<00:03, 22.51it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 406.061} (0.004):  15%|█▌        | 15/100 [00:00<00:03, 22.51it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.005 | Best: {'fx': 413.131} (0.005):  16%|█▌        | 16/100 [00:00<00:03, 22.51it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.005 | Best: {'fx': 420.202} (0.005):  17%|█▋        | 17/100 [00:00<00:03, 22.51it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.005 | Best: {'fx': 420.202} (0.005):  18%|█▊        | 18/100 [00:00<00:02, 30.13it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.006 | Best: {'fx': 427.273} (0.006):  18%|█▊        | 18/100 [00:00<00:02, 30.13it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.007 | Best: {'fx': 434.343} (0.007):  19%|█▉        | 19/100 [00:00<00:02, 30.13it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.008 | Best: {'fx': 441.414} (0.008):  20%|██        | 20/100 [00:00<00:02, 30.13it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.011 | Best: {'fx': 455.556} (0.011):  21%|██        | 21/100 [00:01<00:02, 30.13it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.011 | Best: {'fx': 455.556} (0.011):  22%|██▏       | 22/100 [00:01<00:02, 26.06it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.010 | Best: {'fx': 455.556} (0.011):  22%|██▏       | 22/100 [00:01<00:02, 26.06it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.014 | Best: {'fx': 462.626} (0.014):  23%|██▎       | 23/100 [00:01<00:02, 26.06it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.025 | Best: {'fx': 483.838} (0.025):  24%|██▍       | 24/100 [00:01<00:02, 26.06it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.017 | Best: {'fx': 483.838} (0.025):  25%|██▌       | 25/100 [00:01<00:02, 26.06it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.017 | Best: {'fx': 483.838} (0.025):  26%|██▌       | 26/100 [00:01<00:02, 27.97it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 483.838} (0.025):  26%|██▌       | 26/100 [00:01<00:02, 27.97it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.043 | Best: {'fx': 505.051} (0.043):  27%|██▋       | 27/100 [00:01<00:02, 27.97it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.037 | Best: {'fx': 505.051} (0.043):  28%|██▊       | 28/100 [00:01<00:02, 27.97it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.029 | Best: {'fx': 505.051} (0.043):  29%|██▉       | 29/100 [00:01<00:02, 27.97it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.052 | Best: {'fx': 512.121} (0.052):  30%|███       | 30/100 [00:01<00:02, 27.97it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.052 | Best: {'fx': 512.121} (0.052):  31%|███       | 31/100 [00:01<00:02, 24.33it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.062 | Best: {'fx': 519.192} (0.062):  31%|███       | 31/100 [00:01<00:02, 24.33it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.073 | Best: {'fx': 526.263} (0.073):  32%|███▏      | 32/100 [00:01<00:02, 24.33it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.074 | Best: {'fx': 533.333} (0.074):  33%|███▎      | 33/100 [00:01<00:02, 24.33it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.074 | Best: {'fx': 533.333} (0.074):  34%|███▍      | 34/100 [00:01<00:03, 19.17it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.062 | Best: {'fx': 533.333} (0.074):  34%|███▍      | 34/100 [00:01<00:03, 19.17it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.050 | Best: {'fx': 533.333} (0.074):  35%|███▌      | 35/100 [00:01<00:03, 19.17it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.056 | Best: {'fx': 533.333} (0.074):  36%|███▌      | 36/100 [00:01<00:03, 19.17it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.045 | Best: {'fx': 533.333} (0.074):  37%|███▋      | 37/100 [00:01<00:03, 19.17it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.045 | Best: {'fx': 533.333} (0.074):  38%|███▊      | 38/100 [00:01<00:02, 20.85it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.038 | Best: {'fx': 533.333} (0.074):  38%|███▊      | 38/100 [00:01<00:02, 20.85it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.036 | Best: {'fx': 533.333} (0.074):  39%|███▉      | 39/100 [00:01<00:02, 20.85it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.031 | Best: {'fx': 533.333} (0.074):  40%|████      | 40/100 [00:01<00:02, 20.85it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.041 | Best: {'fx': 533.333} (0.074):  41%|████      | 41/100 [00:01<00:02, 20.85it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.041 | Best: {'fx': 533.333} (0.074):  42%|████▏     | 42/100 [00:01<00:02, 22.05it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.030 | Best: {'fx': 533.333} (0.074):  42%|████▏     | 42/100 [00:01<00:02, 22.05it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.034 | Best: {'fx': 533.333} (0.074):  43%|████▎     | 43/100 [00:01<00:02, 22.05it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.032 | Best: {'fx': 533.333} (0.074):  44%|████▍     | 44/100 [00:01<00:02, 22.05it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.028 | Best: {'fx': 533.333} (0.074):  45%|████▌     | 45/100 [00:02<00:02, 22.05it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.028 | Best: {'fx': 533.333} (0.074):  46%|████▌     | 46/100 [00:02<00:02, 22.05it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.028 | Best: {'fx': 533.333} (0.074):  47%|████▋     | 47/100 [00:02<00:02, 23.80it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.027 | Best: {'fx': 533.333} (0.074):  47%|████▋     | 47/100 [00:02<00:02, 23.80it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.025 | Best: {'fx': 533.333} (0.074):  48%|████▊     | 48/100 [00:02<00:02, 23.80it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.025 | Best: {'fx': 533.333} (0.074):  49%|████▉     | 49/100 [00:02<00:02, 23.80it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.023 | Best: {'fx': 533.333} (0.074):  50%|█████     | 50/100 [00:02<00:02, 23.80it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.023 | Best: {'fx': 533.333} (0.074):  51%|█████     | 51/100 [00:02<00:01, 26.51it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.026 | Best: {'fx': 533.333} (0.074):  51%|█████     | 51/100 [00:02<00:01, 26.51it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.024 | Best: {'fx': 533.333} (0.074):  52%|█████▏    | 52/100 [00:02<00:01, 26.51it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.024 | Best: {'fx': 533.333} (0.074):  53%|█████▎    | 53/100 [00:02<00:01, 26.51it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.023 | Best: {'fx': 533.333} (0.074):  54%|█████▍    | 54/100 [00:02<00:01, 26.51it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.074):  55%|█████▌    | 55/100 [00:02<00:01, 26.51it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.074):  56%|█████▌    | 56/100 [00:02<00:01, 29.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.074):  56%|█████▌    | 56/100 [00:02<00:01, 29.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.074):  57%|█████▋    | 57/100 [00:02<00:01, 29.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.074):  58%|█████▊    | 58/100 [00:02<00:01, 29.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.074):  59%|█████▉    | 59/100 [00:02<00:01, 29.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.074):  60%|██████    | 60/100 [00:02<00:01, 29.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.074):  61%|██████    | 61/100 [00:02<00:01, 29.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.074):  62%|██████▏   | 62/100 [00:02<00:01, 29.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.074):  63%|██████▎   | 63/100 [00:02<00:01, 29.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.074):  64%|██████▍   | 64/100 [00:02<00:01, 29.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.074):  65%|██████▌   | 65/100 [00:02<00:01, 29.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.074):  66%|██████▌   | 66/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.074):  66%|██████▌   | 66/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.023 | Best: {'fx': 533.333} (0.074):  67%|██████▋   | 67/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.074):  68%|██████▊   | 68/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.074):  69%|██████▉   | 69/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.074):  70%|███████   | 70/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.074):  71%|███████   | 71/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.074):  72%|███████▏  | 72/100 [00:02<00:00, 45.03it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.074):  72%|███████▏  | 72/100 [00:02<00:00, 45.03it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.074):  73%|███████▎  | 73/100 [00:02<00:00, 45.03it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.074):  74%|███████▍  | 74/100 [00:02<00:00, 45.03it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.074):  75%|███████▌  | 75/100 [00:02<00:00, 45.03it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.074):  76%|███████▌  | 76/100 [00:02<00:00, 45.03it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.074):  77%|███████▋  | 77/100 [00:02<00:00, 45.08it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.074):  77%|███████▋  | 77/100 [00:02<00:00, 45.08it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  78%|███████▊  | 78/100 [00:02<00:00, 45.08it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  79%|███████▉  | 79/100 [00:02<00:00, 45.08it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  80%|████████  | 80/100 [00:02<00:00, 45.08it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  81%|████████  | 81/100 [00:02<00:00, 45.08it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  82%|████████▏ | 82/100 [00:02<00:00, 43.77it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  82%|████████▏ | 82/100 [00:02<00:00, 43.77it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  83%|████████▎ | 83/100 [00:02<00:00, 43.77it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  84%|████████▍ | 84/100 [00:02<00:00, 43.77it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  85%|████████▌ | 85/100 [00:02<00:00, 43.77it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  86%|████████▌ | 86/100 [00:03<00:00, 43.77it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  87%|████████▋ | 87/100 [00:03<00:00, 31.72it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  87%|████████▋ | 87/100 [00:03<00:00, 31.72it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  88%|████████▊ | 88/100 [00:03<00:00, 31.72it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  89%|████████▉ | 89/100 [00:03<00:00, 31.72it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  90%|█████████ | 90/100 [00:03<00:00, 31.72it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  91%|█████████ | 91/100 [00:03<00:00, 31.34it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  91%|█████████ | 91/100 [00:03<00:00, 31.34it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.017 | Best: {'fx': 533.333} (0.074):  92%|█████████▏| 92/100 [00:03<00:00, 31.34it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  93%|█████████▎| 93/100 [00:03<00:00, 31.34it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.017 | Best: {'fx': 533.333} (0.074):  94%|█████████▍| 94/100 [00:03<00:00, 31.34it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.017 | Best: {'fx': 533.333} (0.074):  95%|█████████▌| 95/100 [00:03<00:00, 31.34it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.017 | Best: {'fx': 533.333} (0.074):  96%|█████████▌| 96/100 [00:03<00:00, 31.49it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.074):  96%|█████████▌| 96/100 [00:03<00:00, 31.49it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.017 | Best: {'fx': 533.333} (0.074):  97%|█████████▋| 97/100 [00:03<00:00, 31.49it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.017 | Best: {'fx': 533.333} (0.074):  98%|█████████▊| 98/100 [00:03<00:00, 31.49it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.017 | Best: {'fx': 533.333} (0.074):  99%|█████████▉| 99/100 [00:03<00:00, 31.49it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.017 | Best: {'fx': 533.333} (0.074): 100%|██████████| 100/100 [00:03<00:00, 28.44it/s]
                                                                                                                                        

  0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.047 | Best: {'fx': 508.333} (0.047):   0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.047 | Best: {'fx': 508.333} (0.047):   2%|▏         | 1/50 [00:00<00:29,  1.69it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.049 | Best: {'fx': 509.354} (0.049):   2%|▏         | 1/50 [00:00<00:29,  1.69it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.050 | Best: {'fx': 510.374} (0.050):   4%|▍         | 2/50 [00:00<00:28,  1.69it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.053 | Best: {'fx': 512.415} (0.053):   6%|▌         | 3/50 [00:00<00:27,  1.69it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.051 | Best: {'fx': 512.415} (0.053):   8%|▊         | 4/50 [00:00<00:27,  1.69it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.051 | Best: {'fx': 512.415} (0.053):  10%|█         | 5/50 [00:00<00:05,  8.67it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.054 | Best: {'fx': 513.435} (0.054):  10%|█         | 5/50 [00:00<00:05,  8.67it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.055 | Best: {'fx': 514.456} (0.055):  12%|█▏        | 6/50 [00:00<00:05,  8.67it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.059 | Best: {'fx': 517.517} (0.059):  14%|█▍        | 7/50 [00:00<00:04,  8.67it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.059 | Best: {'fx': 517.517} (0.059):  16%|█▌        | 8/50 [00:00<00:03, 11.63it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.062 | Best: {'fx': 518.537} (0.062):  16%|█▌        | 8/50 [00:00<00:03, 11.63it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.057 | Best: {'fx': 518.537} (0.062):  18%|█▊        | 9/50 [00:00<00:03, 11.63it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.058 | Best: {'fx': 518.537} (0.062):  20%|██        | 10/50 [00:01<00:03, 11.63it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.058 | Best: {'fx': 518.537} (0.062):  22%|██▏       | 11/50 [00:01<00:02, 14.04it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.065 | Best: {'fx': 521.599} (0.065):  22%|██▏       | 11/50 [00:01<00:02, 14.04it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.063 | Best: {'fx': 521.599} (0.065):  24%|██▍       | 12/50 [00:01<00:02, 14.04it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.069 | Best: {'fx': 523.639} (0.069):  26%|██▌       | 13/50 [00:01<00:02, 14.04it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.069 | Best: {'fx': 523.639} (0.069):  28%|██▊       | 14/50 [00:01<00:02, 17.34it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.070 | Best: {'fx': 524.66} (0.070):  28%|██▊       | 14/50 [00:01<00:02, 17.34it/s] 
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.064 | Best: {'fx': 524.66} (0.070):  30%|███       | 15/50 [00:01<00:02, 17.34it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.074 | Best: {'fx': 526.701} (0.074):  32%|███▏      | 16/50 [00:01<00:01, 17.34it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.067 | Best: {'fx': 526.701} (0.074):  34%|███▍      | 17/50 [00:01<00:01, 17.34it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.067 | Best: {'fx': 526.701} (0.074):  36%|███▌      | 18/50 [00:01<00:01, 21.37it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.074 | Best: {'fx': 526.701} (0.074):  36%|███▌      | 18/50 [00:01<00:01, 21.37it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.074 | Best: {'fx': 526.701} (0.074):  38%|███▊      | 19/50 [00:01<00:01, 21.37it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.075 | Best: {'fx': 530.782} (0.075):  40%|████      | 20/50 [00:01<00:01, 21.37it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.074 | Best: {'fx': 530.782} (0.075):  42%|████▏     | 21/50 [00:01<00:01, 21.37it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.074 | Best: {'fx': 530.782} (0.075):  44%|████▍     | 22/50 [00:01<00:01, 19.92it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.075 | Best: {'fx': 530.782} (0.075):  44%|████▍     | 22/50 [00:01<00:01, 19.92it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.069 | Best: {'fx': 530.782} (0.075):  46%|████▌     | 23/50 [00:01<00:01, 19.92it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.075 | Best: {'fx': 530.782} (0.075):  48%|████▊     | 24/50 [00:01<00:01, 19.92it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.063 | Best: {'fx': 530.782} (0.075):  50%|█████     | 25/50 [00:01<00:01, 19.92it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.071 | Best: {'fx': 530.782} (0.075):  52%|█████▏    | 26/50 [00:01<00:01, 19.92it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.062 | Best: {'fx': 530.782} (0.075):  54%|█████▍    | 27/50 [00:01<00:01, 19.92it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.059 | Best: {'fx': 530.782} (0.075):  56%|█████▌    | 28/50 [00:01<00:01, 19.92it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.061 | Best: {'fx': 530.782} (0.075):  58%|█████▊    | 29/50 [00:01<00:01, 19.92it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.061 | Best: {'fx': 530.782} (0.075):  60%|██████    | 30/50 [00:01<00:01, 19.92it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.074 | Best: {'fx': 530.782} (0.075):  62%|██████▏   | 31/50 [00:01<00:00, 19.92it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.074 | Best: {'fx': 530.782} (0.075):  64%|██████▍   | 32/50 [00:01<00:00, 36.36it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.060 | Best: {'fx': 530.782} (0.075):  64%|██████▍   | 32/50 [00:01<00:00, 36.36it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.067 | Best: {'fx': 530.782} (0.075):  66%|██████▌   | 33/50 [00:01<00:00, 36.36it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.055 | Best: {'fx': 530.782} (0.075):  68%|██████▊   | 34/50 [00:01<00:00, 36.36it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.064 | Best: {'fx': 530.782} (0.075):  70%|███████   | 35/50 [00:01<00:00, 36.36it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.058 | Best: {'fx': 530.782} (0.075):  72%|███████▏  | 36/50 [00:01<00:00, 36.36it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.058 | Best: {'fx': 530.782} (0.075):  74%|███████▍  | 37/50 [00:01<00:00, 38.78it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.069 | Best: {'fx': 530.782} (0.075):  74%|███████▍  | 37/50 [00:01<00:00, 38.78it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.057 | Best: {'fx': 530.782} (0.075):  76%|███████▌  | 38/50 [00:01<00:00, 38.78it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.053 | Best: {'fx': 530.782} (0.075):  78%|███████▊  | 39/50 [00:01<00:00, 38.78it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.055 | Best: {'fx': 530.782} (0.075):  80%|████████  | 40/50 [00:01<00:00, 38.78it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.056 | Best: {'fx': 530.782} (0.075):  82%|████████▏ | 41/50 [00:01<00:00, 38.78it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.066 | Best: {'fx': 530.782} (0.075):  84%|████████▍ | 42/50 [00:01<00:00, 38.78it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.054 | Best: {'fx': 530.782} (0.075):  86%|████████▌ | 43/50 [00:01<00:00, 38.78it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.051 | Best: {'fx': 530.782} (0.075):  88%|████████▊ | 44/50 [00:01<00:00, 38.78it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.051 | Best: {'fx': 530.782} (0.075):  90%|█████████ | 45/50 [00:01<00:00, 38.78it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.051 | Best: {'fx': 530.782} (0.075):  92%|█████████▏| 46/50 [00:01<00:00, 48.21it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.050 | Best: {'fx': 530.782} (0.075):  92%|█████████▏| 46/50 [00:01<00:00, 48.21it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.048 | Best: {'fx': 530.782} (0.075):  94%|█████████▍| 47/50 [00:01<00:00, 48.21it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.049 | Best: {'fx': 530.782} (0.075):  96%|█████████▌| 48/50 [00:01<00:00, 48.21it/s]
Brute | Start: {'fx': 533.333} (0.074) | Current: 0.047 | Best: {'fx': 530.782} (0.075):  98%|█████████▊| 49/50 [00:01<00:00, 48.21it/s]
                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 530.7823129251701
    px: 859.0
    py: 990.0
    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 3 incomplete frames): 77 frames will be used for optimization
  Rigs: 2000R(2000mm):20/20, 1500(1500mm):20/20, 2000L(2000mm):18/20, 1000(1000mm):19/20
  Total: 77/80 frames used for optimization

Initial score: 59.9686: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 59.9686, picklable_objective(x0) = 59.8584

Best score: 59.8584: : 0iter [00:02, ?iter/s] 
Best score: 59.8584: : 1iter [00:02,  2.14s/iter]
Best score: 59.8584: : 1iter [00:02,  2.14s/iter]
Best score: 59.8584: : 2iter [00:02,  2.14s/iter]
Best score: 59.8584: : 3iter [00:02,  1.62iter/s]
Best score: 59.8584: : 3iter [00:02,  1.62iter/s]
Best score: 59.8584: : 4iter [00:02,  1.62iter/s]
Best score: 59.8584: : 5iter [00:02,  2.91iter/s]
Best score: 59.8584: : 5iter [00:02,  2.91iter/s]
Best score: 59.8584: : 6iter [00:02,  2.91iter/s]
Best score: 59.8584: : 7iter [00:02,  4.27iter/s]
Best score: 59.8584: : 7iter [00:02,  4.27iter/s]
Best score: 59.8584: : 8iter [00:02,  4.27iter/s]
Best score: 59.8584: : 9iter [00:02,  5.62iter/s]
Best score: 59.8584: : 9iter [00:02,  5.62iter/s]
Best score: 59.8584: : 10iter [00:02,  5.62iter/s]
Best score: 59.8584: : 11iter [00:02,  6.79iter/s]
Best score: 59.8584: : 11iter [00:03,  6.79iter/s]
Best score: 59.8584: : 12iter [00:03,  6.79iter/s]
Best score: 59.8584: : 13iter [00:03,  7.89iter/s]
Best score: 59.8584: : 13iter [00:03,  7.89iter/s]
Best score: 59.8584: : 14iter [00:03,  7.89iter/s]
Best score: 59.8584: : 15iter [00:03,  8.82iter/s]
Best score: 59.8584: : 15iter [00:03,  8.82iter/s]
Best score: 59.8584: : 16iter [00:03,  8.82iter/s]
Best score: 59.8584: : 17iter [00:03,  9.56iter/s]
Best score: 59.8584: : 17iter [00:03,  9.56iter/s]
Best score: 59.8584: : 18iter [00:03,  9.56iter/s]
Best score: 59.8584: : 19iter [00:03, 10.12iter/s]
Best score: 59.8584: : 19iter [00:03, 10.12iter/s]
Best score: 59.8584: : 20iter [00:03, 10.12iter/s]
Best score: 59.8584: : 21iter [00:03, 10.40iter/s]
Best score: 59.8584: : 21iter [00:03, 10.40iter/s]
Best score: 59.8584: : 22iter [00:04, 10.40iter/s]
Best score: 59.8584: : 23iter [00:04, 10.78iter/s]
Best score: 59.8584: : 23iter [00:04, 10.78iter/s]
Best score: 59.8584: : 24iter [00:04, 10.78iter/s]
Best score: 59.8584: : 25iter [00:04, 11.06iter/s]
Best score: 59.8584: : 25iter [00:04, 11.06iter/s]
Best score: 59.8584: : 26iter [00:04, 11.06iter/s]
Best score: 59.8584: : 27iter [00:04, 11.29iter/s]
Best score: 59.8584: : 27iter [00:04, 11.29iter/s]
Best score: 59.8584: : 28iter [00:04, 11.29iter/s]
Best score: 59.8584: : 29iter [00:04, 11.43iter/s]
Best score: 59.8584: : 29iter [00:04, 11.43iter/s]
Best score: 59.8584: : 30iter [00:04, 11.43iter/s]
Best score: 59.8584: : 31iter [00:04, 11.38iter/s]
Best score: 59.8584: : 31iter [00:04, 11.38iter/s]
Best score: 59.8584: : 32iter [00:04, 11.38iter/s]
Best score: 59.8584: : 33iter [00:04, 11.51iter/s]
Best score: 59.8584: : 33iter [00:04, 11.51iter/s]
Best score: 59.8584: : 34iter [00:05, 11.51iter/s]
Best score: 59.8584: : 35iter [00:05, 11.57iter/s]
Best score: 59.8584: : 35iter [00:05, 11.57iter/s]
Best score: 59.8584: : 36iter [00:05, 11.57iter/s]
Best score: 59.8584: : 37iter [00:05, 11.64iter/s]
Best score: 59.8584: : 37iter [00:05, 11.64iter/s]
Best score: 59.8584: : 38iter [00:05, 11.64iter/s]
Best score: 59.8584: : 39iter [00:05, 11.67iter/s]
Best score: 59.8584: : 39iter [00:05, 11.67iter/s]
Best score: 59.8584: : 40iter [00:05, 11.67iter/s]
Best score: 59.8584: : 41iter [00:05, 11.52iter/s]
Best score: 59.8584: : 41iter [00:05, 11.52iter/s]
Best score: 59.8584: : 42iter [00:05, 11.52iter/s]
Best score: 59.8584: : 43iter [00:05, 11.59iter/s]
Best score: 59.8584: : 43iter [00:05, 11.59iter/s]
Best score: 59.8584: : 44iter [00:05, 11.59iter/s]
Best score: 59.8584: : 45iter [00:05, 11.71iter/s]
Best score: 59.8584: : 45iter [00:05, 11.71iter/s]
Best score: 59.8584: : 46iter [00:06, 11.71iter/s]
Best score: 59.8584: : 47iter [00:06, 11.79iter/s]
Best score: 59.8584: : 47iter [00:06, 11.79iter/s]
Best score: 59.8584: : 48iter [00:06, 11.79iter/s]
Best score: 59.8584: : 49iter [00:06, 11.83iter/s]
[ITER 50] Best: 59.8584
[PARAMS] Current best parameters:
  fx: 530.7823
  fy: 530.7823
  px: 859.0000
  py: 990.0000
  k1: 0.00000000
  k2: -0.00000000
  k3: 0.00000000
  k4: 0.00000000
  p1: 0.00000000
  p2: 0.00000000
  p3: 0.00000000
  p4: 0.00000000
  s1: 0.0000
  s2: 0.0000
  s3: 0.0000
  s4: 0.0000
  tilt_x: 0.0000
  tilt_y: 0.0000
  scale: 3.0000
  rotation: 0.0000

Best score: 59.8584: : 49iter [00:06, 11.83iter/s]
Best score: 59.8584: : 50iter [00:06, 11.83iter/s]
Best score: 59.8584: : 51iter [00:06, 11.70iter/s]
Best score: 59.8584: : 51iter [00:06, 11.70iter/s]
Best score: 59.8584: : 52iter [00:06, 11.70iter/s]
Best score: 59.8584: : 53iter [00:06, 11.76iter/s]
Best score: 59.8584: : 53iter [00:06, 11.76iter/s]
Best score: 59.8584: : 54iter [00:06, 11.76iter/s]
Best score: 59.8584: : 55iter [00:06, 11.81iter/s]
Best score: 59.8584: : 55iter [00:06, 11.81iter/s]
Best score: 59.8584: : 56iter [00:06, 11.81iter/s]
Best score: 59.8584: : 57iter [00:06, 11.85iter/s]
Best score: 59.8584: : 57iter [00:07, 11.85iter/s]
Best score: 59.8584: : 58iter [00:07, 11.85iter/s]
Best score: 59.8584: : 59iter [00:07, 11.84iter/s]
Best score: 59.8584: : 59iter [00:07, 11.84iter/s]
Best score: 59.8584: : 60iter [00:07, 11.84iter/s]
Best score: 59.8584: : 61iter [00:07, 11.74iter/s]
Best score: 59.8584: : 61iter [00:07, 11.74iter/s]
Best score: 59.8584: : 62iter [00:07, 11.74iter/s]
Best score: 59.8584: : 63iter [00:07, 11.79iter/s]
Best score: 59.8584: : 63iter [00:07, 11.79iter/s]
Best score: 59.8584: : 64iter [00:07, 11.79iter/s]
Best score: 59.8584: : 65iter [00:07, 11.80iter/s]
Best score: 59.8584: : 65iter [00:07, 11.80iter/s]
Best score: 59.8584: : 66iter [00:07, 11.80iter/s]
Best score: 59.8584: : 67iter [00:07, 11.81iter/s]
Best score: 59.8584: : 67iter [00:07, 11.81iter/s]
Best score: 59.8584: : 68iter [00:07, 11.81iter/s]
Best score: 59.8584: : 69iter [00:07, 11.80iter/s]
Best score: 59.8584: : 69iter [00:08, 11.80iter/s]
Best score: 59.8584: : 70iter [00:08, 11.80iter/s]
Best score: 59.8584: : 71iter [00:08, 11.67iter/s]
Best score: 59.8584: : 71iter [00:08, 11.67iter/s]
Best score: 59.8584: : 72iter [00:08, 11.67iter/s]
Best score: 59.8584: : 73iter [00:08, 11.75iter/s]
Best score: 59.8584: : 73iter [00:08, 11.75iter/s]
Best score: 59.8584: : 74iter [00:08, 11.75iter/s]
Best score: 59.8584: : 75iter [00:08, 11.82iter/s]
Best score: 59.8584: : 75iter [00:08, 11.82iter/s]
Best score: 59.8584: : 76iter [00:08, 11.82iter/s]
Best score: 59.8584: : 77iter [00:08, 11.87iter/s]
Best score: 59.8584: : 77iter [00:08, 11.87iter/s]
Best score: 59.8584: : 78iter [00:08, 11.87iter/s]
Best score: 59.8584: : 79iter [00:08, 11.86iter/s]
Best score: 48.8110: : 79iter [00:08, 11.86iter/s]
Best score: 48.8110: : 80iter [00:08, 11.86iter/s]
Best score: 48.8110: : 81iter [00:08, 11.66iter/s]
Best score: 48.8110: : 81iter [00:09, 11.66iter/s]
Best score: 48.8110: : 82iter [00:09, 11.66iter/s]
Best score: 48.8110: : 83iter [00:09, 11.71iter/s]
Best score: 48.8110: : 83iter [00:09, 11.71iter/s]
Best score: 48.8110: : 84iter [00:09, 11.71iter/s]
Best score: 48.8110: : 85iter [00:09, 11.78iter/s]
Best score: 48.8110: : 85iter [00:09, 11.78iter/s]
Best score: 48.8110: : 86iter [00:09, 11.78iter/s]
Best score: 48.8110: : 87iter [00:09, 11.87iter/s]
Best score: 48.8110: : 87iter [00:09, 11.87iter/s]
Best score: 48.8110: : 88iter [00:09, 11.87iter/s]
Best score: 48.8110: : 89iter [00:09, 11.85iter/s]
Best score: 48.8110: : 89iter [00:09, 11.85iter/s]
Best score: 48.8110: : 90iter [00:09, 11.85iter/s]
Best score: 48.8110: : 91iter [00:09, 11.69iter/s]
Best score: 48.8110: : 91iter [00:09, 11.69iter/s]
Best score: 48.8110: : 92iter [00:09, 11.69iter/s]
Best score: 48.8110: : 93iter [00:09, 11.75iter/s]
Best score: 48.8110: : 93iter [00:10, 11.75iter/s]
Best score: 48.8110: : 94iter [00:10, 11.75iter/s]
Best score: 48.8110: : 95iter [00:10, 11.85iter/s]
Best score: 48.8110: : 95iter [00:10, 11.85iter/s]
Best score: 48.8110: : 96iter [00:10, 11.85iter/s]
Best score: 48.8110: : 97iter [00:10, 11.89iter/s]
Best score: 48.8110: : 97iter [00:10, 11.89iter/s]
Best score: 48.8110: : 98iter [00:10, 11.89iter/s]
Best score: 48.8110: : 99iter [00:10, 11.91iter/s]
[ITER 100] Best: 20.3364
[PARAMS] Current best parameters:
  fx: 523.9620
  fy: 524.9405
  px: 856.3080
  py: 998.9129
  k1: -0.01513780
  k2: -0.04004945
  k3: 0.05543309
  k4: -0.01622015
  p1: 0.00151590
  p2: 0.02193322
  p3: -0.00104039
  p4: 0.00127983
  s1: -0.0306
  s2: 0.0113
  s3: 0.0256
  s4: -0.0190
  tilt_x: -0.0299
  tilt_y: 0.0073
  scale: 3.2108
  rotation: -0.6232

Best score: 20.3364: : 99iter [00:10, 11.91iter/s]
Best score: 20.3364: : 100iter [00:10, 11.91iter/s]
Best score: 20.3364: : 101iter [00:10, 10.11iter/s]
Best score: 20.3364: : 101iter [00:10, 10.11iter/s]
Best score: 20.3364: : 102iter [00:10, 10.11iter/s]
Best score: 20.3364: : 103iter [00:10, 10.56iter/s]
Best score: 20.3364: : 103iter [00:11, 10.56iter/s]
Best score: 20.3364: : 104iter [00:11, 10.56iter/s]
Best score: 20.3364: : 105iter [00:11, 10.88iter/s]
Best score: 20.3364: : 105iter [00:11, 10.88iter/s]
Best score: 20.3364: : 106iter [00:11, 10.88iter/s]
Best score: 20.3364: : 107iter [00:11, 11.12iter/s]
Best score: 20.3364: : 107iter [00:11, 11.12iter/s]
Best score: 20.3364: : 108iter [00:11, 11.12iter/s]
Best score: 20.3364: : 109iter [00:11, 11.33iter/s]
Best score: 20.3364: : 109iter [00:11, 11.33iter/s]
Best score: 20.3364: : 110iter [00:11, 11.33iter/s]
Best score: 20.3364: : 111iter [00:11, 11.28iter/s]
Best score: 20.3364: : 111iter [00:11, 11.28iter/s]
Best score: 20.3364: : 112iter [00:11, 11.28iter/s]
Best score: 20.3364: : 113iter [00:11, 11.45iter/s]
Best score: 20.3364: : 113iter [00:11, 11.45iter/s]
Best score: 20.3364: : 114iter [00:11, 11.45iter/s]
Best score: 20.3364: : 115iter [00:11, 11.53iter/s]
Best score: 20.3364: : 115iter [00:12, 11.53iter/s]
Best score: 20.3364: : 116iter [00:12, 11.53iter/s]
Best score: 20.3364: : 117iter [00:12, 11.65iter/s]
Best score: 20.3364: : 117iter [00:12, 11.65iter/s]
Best score: 20.3364: : 118iter [00:12, 11.65iter/s]
Best score: 20.3364: : 119iter [00:12, 11.68iter/s]
Best score: 20.3364: : 119iter [00:12, 11.68iter/s]
Best score: 20.3364: : 120iter [00:12, 11.68iter/s]
Best score: 20.3364: : 121iter [00:12, 11.50iter/s]
Best score: 20.3364: : 121iter [00:12, 11.50iter/s]
Best score: 20.3364: : 122iter [00:12, 11.50iter/s]
Best score: 20.3364: : 123iter [00:12, 11.65iter/s]
Best score: 20.3364: : 123iter [00:12, 11.65iter/s]
Best score: 20.3364: : 124iter [00:12, 11.65iter/s]
Best score: 20.3364: : 125iter [00:12, 11.75iter/s]
Best score: 20.3364: : 125iter [00:12, 11.75iter/s]
Best score: 20.3364: : 126iter [00:12, 11.75iter/s]
Best score: 20.3364: : 127iter [00:12, 11.73iter/s]
Best score: 20.3364: : 127iter [00:13, 11.73iter/s]
Best score: 20.3364: : 128iter [00:13, 11.73iter/s]
Best score: 20.3364: : 129iter [00:13, 11.73iter/s]
Best score: 20.3364: : 129iter [00:13, 11.73iter/s]
Best score: 20.3364: : 130iter [00:13, 11.73iter/s]
Best score: 20.3364: : 131iter [00:13, 11.54iter/s]
Best score: 20.3364: : 131iter [00:13, 11.54iter/s]
Best score: 20.3364: : 132iter [00:13, 11.54iter/s]
Best score: 20.3364: : 133iter [00:13, 11.64iter/s]
Best score: 20.3364: : 133iter [00:13, 11.64iter/s]
Best score: 20.3364: : 134iter [00:13, 11.64iter/s]
Best score: 20.3364: : 135iter [00:13, 11.70iter/s]
Best score: 20.3364: : 135iter [00:13, 11.70iter/s]
Best score: 20.3364: : 136iter [00:13, 11.70iter/s]
Best score: 20.3364: : 137iter [00:13, 11.79iter/s]
Best score: 20.3364: : 137iter [00:13, 11.79iter/s]
Best score: 20.3364: : 138iter [00:13, 11.79iter/s]
Best score: 20.3364: : 139iter [00:13, 11.79iter/s]
Best score: 20.3364: : 139iter [00:14, 11.79iter/s]
Best score: 20.3364: : 140iter [00:14, 11.79iter/s]
Best score: 20.3364: : 141iter [00:14, 11.63iter/s]
Best score: 20.3364: : 141iter [00:14, 11.63iter/s]
Best score: 20.3364: : 142iter [00:14, 11.63iter/s]
Best score: 20.3364: : 143iter [00:14, 11.68iter/s]
Best score: 20.3364: : 143iter [00:14, 11.68iter/s]
Best score: 20.3364: : 144iter [00:14, 11.68iter/s]
Best score: 20.3364: : 145iter [00:14, 11.78iter/s]
Best score: 20.3364: : 145iter [00:14, 11.78iter/s]
Best score: 20.3364: : 146iter [00:14, 11.78iter/s]
Best score: 20.3364: : 147iter [00:14, 11.86iter/s]
Best score: 20.3364: : 147iter [00:14, 11.86iter/s]
Best score: 20.3364: : 148iter [00:14, 11.86iter/s]
Best score: 20.3364: : 149iter [00:14, 11.93iter/s]
[ITER 150] Best: 13.1911
[PARAMS] Current best parameters:
  fx: 552.0721
  fy: 550.7582
  px: 857.3082
  py: 993.6947
  k1: 0.01463884
  k2: -0.05999443
  k3: 0.04697455
  k4: -0.01225322
  p1: 0.00506995
  p2: 0.01601627
  p3: -0.01175467
  p4: -0.01212876
  s1: -0.0225
  s2: 0.0374
  s3: 0.0111
  s4: -0.0141
  tilt_x: -0.0348
  tilt_y: -0.0003
  scale: 2.9223
  rotation: -0.5560

Best score: 13.1911: : 149iter [00:14, 11.93iter/s]
Best score: 13.1911: : 150iter [00:15, 11.93iter/s]
Best score: 13.1911: : 151iter [00:15,  7.74iter/s]
Best score: 13.1911: : 151iter [00:15,  7.74iter/s]
Best score: 13.1911: : 152iter [00:15,  7.74iter/s]
Best score: 13.1911: : 153iter [00:15,  8.65iter/s]
Best score: 13.1911: : 153iter [00:15,  8.65iter/s]
Best score: 13.1911: : 154iter [00:15,  8.65iter/s]
Best score: 13.1911: : 155iter [00:15,  9.46iter/s]
Best score: 13.1911: : 155iter [00:15,  9.46iter/s]
Best score: 13.1911: : 156iter [00:15,  9.46iter/s]
Best score: 13.1911: : 157iter [00:15, 10.14iter/s]
Best score: 13.1911: : 157iter [00:15, 10.14iter/s]
Best score: 13.1911: : 158iter [00:15, 10.14iter/s]
Best score: 13.1911: : 159iter [00:15, 10.67iter/s]
Best score: 13.0052: : 159iter [00:16, 10.67iter/s]
Best score: 13.0052: : 160iter [00:16, 10.67iter/s]
Best score: 13.0052: : 161iter [00:16, 10.89iter/s]
Best score: 13.0052: : 161iter [00:16, 10.89iter/s]
Best score: 13.0052: : 162iter [00:16, 10.89iter/s]
Best score: 13.0052: : 163iter [00:16,  8.63iter/s]
Best score: 13.0052: : 163iter [00:16,  8.63iter/s]
Best score: 13.0052: : 164iter [00:16,  8.63iter/s]
Best score: 13.0052: : 165iter [00:16,  9.46iter/s]
Best score: 13.0052: : 165iter [00:16,  9.46iter/s]
Best score: 13.0052: : 166iter [00:16,  9.46iter/s]
Best score: 13.0052: : 167iter [00:16, 10.10iter/s]
Best score: 13.0052: : 167iter [00:16, 10.10iter/s]
Best score: 13.0052: : 168iter [00:16, 10.10iter/s]
Best score: 13.0052: : 169iter [00:16, 10.60iter/s]
Best score: 8.3383: : 169iter [00:17, 10.60iter/s] 
Best score: 8.3383: : 170iter [00:17, 10.60iter/s]
Best score: 8.3383: : 171iter [00:17, 10.85iter/s]
Best score: 8.3383: : 171iter [00:17, 10.85iter/s]
Best score: 8.3383: : 172iter [00:17, 10.85iter/s]
Best score: 8.3383: : 173iter [00:17, 11.21iter/s]
Best score: 8.3383: : 173iter [00:17, 11.21iter/s]
Best score: 8.3383: : 174iter [00:17, 11.21iter/s]
Best score: 8.3383: : 175iter [00:17, 11.45iter/s]
Best score: 8.3383: : 175iter [00:17, 11.45iter/s]
Best score: 8.3383: : 176iter [00:17, 11.45iter/s]
Best score: 8.3383: : 177iter [00:17, 11.64iter/s]
Best score: 8.3383: : 177iter [00:17, 11.64iter/s]
Best score: 8.3383: : 178iter [00:17, 11.64iter/s]
Best score: 8.3383: : 179iter [00:17, 11.76iter/s]
Best score: 8.3383: : 179iter [00:17, 11.76iter/s]
Best score: 8.3383: : 180iter [00:18, 11.76iter/s]
Best score: 8.3383: : 181iter [00:18, 11.63iter/s]
Best score: 8.3383: : 181iter [00:18, 11.63iter/s]
Best score: 8.3383: : 182iter [00:18, 11.63iter/s]
Best score: 8.3383: : 183iter [00:18, 11.73iter/s]
Best score: 8.3383: : 183iter [00:18, 11.73iter/s]
Best score: 8.3383: : 184iter [00:18, 11.73iter/s]
Best score: 8.3383: : 185iter [00:18, 11.81iter/s]
Best score: 8.3383: : 185iter [00:18, 11.81iter/s]
Best score: 8.3383: : 186iter [00:18, 11.81iter/s]
Best score: 8.3383: : 187iter [00:18, 11.86iter/s]
Best score: 8.3383: : 187iter [00:18, 11.86iter/s]
Best score: 8.3383: : 188iter [00:18, 11.86iter/s]
Best score: 8.3383: : 189iter [00:18, 11.87iter/s]
Best score: 7.7677: : 189iter [00:18, 11.87iter/s]
Best score: 7.7677: : 190iter [00:18, 11.87iter/s]
Best score: 7.7677: : 191iter [00:18, 11.77iter/s]
Best score: 7.7677: : 191iter [00:18, 11.77iter/s]
Best score: 7.7677: : 192iter [00:19, 11.77iter/s]
Best score: 7.7677: : 193iter [00:19, 11.88iter/s]
Best score: 7.7677: : 193iter [00:19, 11.88iter/s]
Best score: 7.7677: : 194iter [00:19, 11.88iter/s]
Best score: 7.7677: : 195iter [00:19, 11.91iter/s]
Best score: 7.7677: : 195iter [00:19, 11.91iter/s]
Best score: 7.7677: : 196iter [00:19, 11.91iter/s]
Best score: 7.7677: : 197iter [00:19, 11.98iter/s]
Best score: 7.7677: : 197iter [00:19, 11.98iter/s]
Best score: 7.7677: : 198iter [00:19, 11.98iter/s]
Best score: 7.7677: : 199iter [00:19, 12.00iter/s]
[ITER 200] Best: 4.0464
[PARAMS] Current best parameters:
  fx: 533.3443
  fy: 535.4205
  px: 852.9057
  py: 990.7911
  k1: -0.01184978
  k2: -0.03293767
  k3: 0.05082542
  k4: -0.01775467
  p1: -0.00435311
  p2: -0.00402240
  p3: 0.02461677
  p4: -0.00746027
  s1: -0.0317
  s2: 0.0138
  s3: -0.0058
  s4: -0.0155
  tilt_x: -0.0542
  tilt_y: -0.0038
  scale: 3.0592
  rotation: -0.3064

Best score: 4.0464: : 199iter [00:19, 12.00iter/s]
Best score: 4.0464: : 200iter [00:19, 12.00iter/s]
Best score: 4.0464: : 201iter [00:19,  7.72iter/s]
Best score: 4.0464: : 201iter [00:20,  7.72iter/s]
Best score: 4.0464: : 202iter [00:20,  7.72iter/s]
Best score: 4.0464: : 203iter [00:20,  8.66iter/s]
Best score: 4.0464: : 203iter [00:20,  8.66iter/s]
Best score: 4.0464: : 204iter [00:20,  8.66iter/s]
Best score: 4.0464: : 205iter [00:20,  9.46iter/s]
Best score: 4.0464: : 205iter [00:20,  9.46iter/s]
Best score: 4.0464: : 206iter [00:20,  9.46iter/s]
Best score: 4.0464: : 207iter [00:20, 10.13iter/s]
Best score: 4.0464: : 207iter [00:20, 10.13iter/s]
Best score: 4.0464: : 208iter [00:20, 10.13iter/s]
Best score: 4.0464: : 209iter [00:20, 10.67iter/s]
Best score: 3.1376: : 209iter [00:20, 10.67iter/s]
Best score: 3.1376: : 210iter [00:20, 10.67iter/s]
Best score: 3.1376: : 211iter [00:20, 10.84iter/s]
Best score: 3.1376: : 211iter [00:20, 10.84iter/s]
Best score: 3.1376: : 212iter [00:20, 10.84iter/s]
Best score: 3.1376: : 213iter [00:20, 11.13iter/s]
Best score: 3.1376: : 213iter [00:21, 11.13iter/s]
Best score: 3.1376: : 214iter [00:21, 11.13iter/s]
Best score: 3.1376: : 215iter [00:21, 11.43iter/s]
Best score: 3.1376: : 215iter [00:21, 11.43iter/s]
Best score: 3.1376: : 216iter [00:21, 11.43iter/s]
Best score: 3.1376: : 217iter [00:21, 11.64iter/s]
Best score: 3.1376: : 217iter [00:21, 11.64iter/s]
Best score: 3.1376: : 218iter [00:21, 11.64iter/s]
Best score: 3.1376: : 219iter [00:21, 11.78iter/s]
Best score: 3.1376: : 219iter [00:21, 11.78iter/s]
Best score: 3.1376: : 220iter [00:21, 11.78iter/s]
Best score: 3.1376: : 221iter [00:21, 11.70iter/s]
Best score: 3.1376: : 221iter [00:21, 11.70iter/s]
Best score: 3.1376: : 222iter [00:21, 11.70iter/s]
Best score: 3.1376: : 223iter [00:21, 11.85iter/s]
Best score: 3.1376: : 223iter [00:21, 11.85iter/s]
Best score: 3.1376: : 224iter [00:21, 11.85iter/s]
Best score: 3.1376: : 225iter [00:21, 11.94iter/s]
Best score: 3.1376: : 225iter [00:22, 11.94iter/s]
Best score: 3.1376: : 226iter [00:22, 11.94iter/s]
Best score: 3.1376: : 227iter [00:22, 11.96iter/s]
Best score: 3.1376: : 227iter [00:22, 11.96iter/s]
Best score: 3.1376: : 228iter [00:22, 11.96iter/s]
Best score: 3.1376: : 229iter [00:22, 11.97iter/s]
Best score: 1.7456: : 229iter [00:22, 11.97iter/s]
Best score: 1.7456: : 230iter [00:22, 11.97iter/s]
Best score: 1.7456: : 231iter [00:22, 11.84iter/s]
Best score: 1.7456: : 231iter [00:22, 11.84iter/s]
Best score: 1.7456: : 232iter [00:22, 11.84iter/s]
Best score: 1.7456: : 233iter [00:22, 11.91iter/s]
Best score: 1.7456: : 233iter [00:22, 11.91iter/s]
Best score: 1.7456: : 234iter [00:22, 11.91iter/s]
Best score: 1.7456: : 235iter [00:22, 11.99iter/s]
Best score: 1.7456: : 235iter [00:22, 11.99iter/s]
Best score: 1.7456: : 236iter [00:22, 11.99iter/s]
Best score: 1.7456: : 237iter [00:22, 12.04iter/s]
Best score: 1.7456: : 237iter [00:23, 12.04iter/s]
Best score: 1.7456: : 238iter [00:23, 12.04iter/s]
Best score: 1.7456: : 239iter [00:23, 12.09iter/s]
Best score: 1.4810: : 239iter [00:23, 12.09iter/s]
Best score: 1.4810: : 240iter [00:23, 12.09iter/s]
Best score: 1.4810: : 241iter [00:23, 11.88iter/s]
Best score: 1.4810: : 241iter [00:23, 11.88iter/s]
Best score: 1.4810: : 242iter [00:23, 11.88iter/s]
Best score: 1.4810: : 243iter [00:23, 11.92iter/s]
Best score: 1.4810: : 243iter [00:23, 11.92iter/s]
Best score: 1.4810: : 244iter [00:23, 11.92iter/s]
Best score: 1.4810: : 245iter [00:23, 12.00iter/s]
Best score: 1.4810: : 245iter [00:23, 12.00iter/s]
Best score: 1.4810: : 246iter [00:23, 12.00iter/s]
Best score: 1.4810: : 247iter [00:23, 12.04iter/s]
Best score: 1.4810: : 247iter [00:23, 12.04iter/s]
Best score: 1.4810: : 248iter [00:23, 12.04iter/s]
Best score: 1.4810: : 249iter [00:23, 12.07iter/s]
[ITER 250] Best: 1.4810
[PARAMS] Current best parameters:
  fx: 550.0538
  fy: 551.9150
  px: 860.2025
  py: 987.5285
  k1: -0.00472681
  k2: -0.04283945
  k3: 0.04244854
  k4: -0.01321989
  p1: -0.01690708
  p2: 0.02016696
  p3: -0.01074522
  p4: 0.00909471
  s1: 0.0051
  s2: -0.0189
  s3: -0.0026
  s4: 0.0009
  tilt_x: -0.0366
  tilt_y: -0.0027
  scale: 2.9900
  rotation: -0.3834

Best score: 1.4810: : 249iter [00:24, 12.07iter/s]
Best score: 1.4810: : 250iter [00:24, 12.07iter/s]
Best score: 1.4810: : 251iter [00:24,  7.77iter/s]
Best score: 1.4810: : 251iter [00:24,  7.77iter/s]
Best score: 1.4810: : 252iter [00:24,  7.77iter/s]
Best score: 1.4810: : 253iter [00:24,  8.71iter/s]
Best score: 1.4810: : 253iter [00:24,  8.71iter/s]
Best score: 1.4810: : 254iter [00:24,  8.71iter/s]
Best score: 1.4810: : 255iter [00:24,  9.52iter/s]
Best score: 1.4810: : 255iter [00:24,  9.52iter/s]
Best score: 1.4810: : 256iter [00:24,  9.52iter/s]
Best score: 1.4810: : 257iter [00:24, 10.17iter/s]
Best score: 1.4810: : 257iter [00:25, 10.17iter/s]
Best score: 1.4810: : 258iter [00:25, 10.17iter/s]
Best score: 1.4810: : 259iter [00:25, 10.66iter/s]
Best score: 1.1970: : 259iter [00:25, 10.66iter/s]
Best score: 1.1970: : 260iter [00:25, 10.66iter/s]
Best score: 1.1970: : 261iter [00:25, 10.90iter/s]
Best score: 1.1970: : 261iter [00:25, 10.90iter/s]
Best score: 1.1970: : 262iter [00:25, 10.90iter/s]
Best score: 1.1970: : 263iter [00:25, 11.26iter/s]
Best score: 1.1970: : 263iter [00:25, 11.26iter/s]
Best score: 1.1970: : 264iter [00:25, 11.26iter/s]
Best score: 1.1970: : 265iter [00:25, 11.52iter/s]
Best score: 1.1970: : 265iter [00:25, 11.52iter/s]
Best score: 1.1970: : 266iter [00:25, 11.52iter/s]
Best score: 1.1970: : 267iter [00:25, 11.71iter/s]
Best score: 1.1970: : 267iter [00:25, 11.71iter/s]
Best score: 1.1970: : 268iter [00:25, 11.71iter/s]
Best score: 1.1970: : 269iter [00:25, 11.81iter/s]
Best score: 1.1970: : 269iter [00:26, 11.81iter/s]
Best score: 1.1970: : 270iter [00:26, 11.81iter/s]
Best score: 1.1970: : 271iter [00:26, 11.67iter/s]
Best score: 1.1970: : 271iter [00:26, 11.67iter/s]
Best score: 1.1970: : 272iter [00:26, 11.67iter/s]
Best score: 1.1970: : 273iter [00:26, 11.80iter/s]
Best score: 1.1970: : 273iter [00:26, 11.80iter/s]
Best score: 1.1970: : 274iter [00:26, 11.80iter/s]
Best score: 1.1970: : 275iter [00:26, 11.85iter/s]
Best score: 1.1970: : 275iter [00:26, 11.85iter/s]
Best score: 1.1970: : 276iter [00:26, 11.85iter/s]
Best score: 1.1970: : 277iter [00:26, 11.92iter/s]
Best score: 1.1970: : 277iter [00:26, 11.92iter/s]
Best score: 1.1970: : 278iter [00:26, 11.92iter/s]
Best score: 1.1970: : 279iter [00:26, 11.97iter/s]
Best score: 0.9007: : 279iter [00:26, 11.97iter/s]
Best score: 0.9007: : 280iter [00:26, 11.97iter/s]
Best score: 0.9007: : 281iter [00:26, 11.81iter/s]
Best score: 0.9007: : 281iter [00:27, 11.81iter/s]
Best score: 0.9007: : 282iter [00:27, 11.81iter/s]
Best score: 0.9007: : 283iter [00:27, 11.92iter/s]
Best score: 0.9007: : 283iter [00:27, 11.92iter/s]
Best score: 0.9007: : 284iter [00:27, 11.92iter/s]
Best score: 0.9007: : 285iter [00:27, 11.98iter/s]
Best score: 0.9007: : 285iter [00:27, 11.98iter/s]
Best score: 0.9007: : 286iter [00:27, 11.98iter/s]
Best score: 0.9007: : 287iter [00:27, 12.02iter/s]
Best score: 0.9007: : 287iter [00:27, 12.02iter/s]
Best score: 0.9007: : 288iter [00:27, 12.02iter/s]
Best score: 0.9007: : 289iter [00:27, 12.05iter/s]
Best score: 0.9007: : 289iter [00:27, 12.05iter/s]
Best score: 0.9007: : 290iter [00:27, 12.05iter/s]
Best score: 0.9007: : 291iter [00:27, 11.83iter/s]
Best score: 0.9007: : 291iter [00:27, 11.83iter/s]
Best score: 0.9007: : 292iter [00:27, 11.83iter/s]
Best score: 0.9007: : 293iter [00:27, 11.91iter/s]
Best score: 0.9007: : 293iter [00:28, 11.91iter/s]
Best score: 0.9007: : 294iter [00:28, 11.91iter/s]
Best score: 0.9007: : 295iter [00:28, 11.98iter/s]
Best score: 0.9007: : 295iter [00:28, 11.98iter/s]
Best score: 0.9007: : 296iter [00:28, 11.98iter/s]
Best score: 0.9007: : 297iter [00:28, 12.03iter/s]
Best score: 0.9007: : 297iter [00:28, 12.03iter/s]
Best score: 0.9007: : 298iter [00:28, 12.03iter/s]
Best score: 0.9007: : 299iter [00:28, 12.06iter/s]
[ITER 300] Best: 0.9007
[PARAMS] Current best parameters:
  fx: 559.2514
  fy: 559.5062
  px: 851.3561
  py: 994.8993
  k1: 0.01641530
  k2: -0.08636804
  k3: 0.06234996
  k4: -0.01540556
  p1: 0.00111067
  p2: 0.01036885
  p3: 0.00361755
  p4: -0.00363668
  s1: -0.0266
  s2: 0.0069
  s3: -0.0203
  s4: 0.0138
  tilt_x: -0.0406
  tilt_y: 0.0153
  scale: 2.9731
  rotation: -0.3482

Best score: 0.9007: : 299iter [00:28, 12.06iter/s]
[Periodic outlier @ iter 200] Removing 1500 frame 5 (score=15.79, threshold=8.20)
  Remaining frames: 76

Best score: 0.9007: : 300iter [00:29, 12.06iter/s]
Best score: 0.9007: : 301iter [00:29,  6.70iter/s]
Best score: 0.9007: : 301iter [00:29,  6.70iter/s]
Best score: 0.9007: : 302iter [00:29,  6.70iter/s]
Best score: 0.9007: : 303iter [00:29,  7.72iter/s]
Best score: 0.9007: : 303iter [00:29,  7.72iter/s]
Best score: 0.9007: : 304iter [00:29,  7.72iter/s]
Best score: 0.9007: : 305iter [00:29,  8.63iter/s]
Best score: 0.9007: : 305iter [00:29,  8.63iter/s]
Best score: 0.9007: : 306iter [00:29,  8.63iter/s]
Best score: 0.9007: : 307iter [00:29,  9.40iter/s]
Best score: 0.9007: : 307iter [00:29,  9.40iter/s]
Best score: 0.9007: : 308iter [00:29,  9.40iter/s]
Best score: 0.9007: : 309iter [00:29, 10.05iter/s]
Best score: 0.7472: : 309iter [00:29, 10.05iter/s]
Best score: 0.7472: : 310iter [00:29, 10.05iter/s]
Best score: 0.7472: : 311iter [00:29, 10.43iter/s]
Best score: 0.7472: : 311iter [00:29, 10.43iter/s]
Best score: 0.7472: : 312iter [00:30, 10.43iter/s]
Best score: 0.7472: : 313iter [00:30, 10.88iter/s]
Best score: 0.7472: : 313iter [00:30, 10.88iter/s]
Best score: 0.7472: : 314iter [00:30, 10.88iter/s]
Best score: 0.7472: : 315iter [00:30, 11.23iter/s]
Best score: 0.7472: : 315iter [00:30, 11.23iter/s]
Best score: 0.7472: : 316iter [00:30, 11.23iter/s]
Best score: 0.7472: : 317iter [00:30, 11.43iter/s]
Best score: 0.7472: : 317iter [00:30, 11.43iter/s]
Best score: 0.7472: : 318iter [00:30, 11.43iter/s]
Best score: 0.7472: : 319iter [00:30, 11.65iter/s]
Best score: 0.7472: : 319iter [00:30, 11.65iter/s]
Best score: 0.7472: : 320iter [00:30, 11.65iter/s]
Best score: 0.7472: : 321iter [00:30, 11.60iter/s]
Best score: 0.7472: : 321iter [00:30, 11.60iter/s]
Best score: 0.7472: : 322iter [00:30, 11.60iter/s]
Best score: 0.7472: : 323iter [00:30, 11.67iter/s]
Best score: 0.7472: : 323iter [00:30, 11.67iter/s]
Best score: 0.7472: : 324iter [00:31, 11.67iter/s]
Best score: 0.7472: : 325iter [00:31, 11.75iter/s]
Best score: 0.7472: : 325iter [00:31, 11.75iter/s]
Best score: 0.7472: : 326iter [00:31, 11.75iter/s]
Best score: 0.7472: : 327iter [00:31, 11.81iter/s]
Best score: 0.7472: : 327iter [00:31, 11.81iter/s]
Best score: 0.7472: : 328iter [00:31, 11.81iter/s]
Best score: 0.7472: : 329iter [00:31, 11.92iter/s]
Best score: 0.7472: : 329iter [00:31, 11.92iter/s]
Best score: 0.7472: : 330iter [00:31, 11.92iter/s]
Best score: 0.7472: : 331iter [00:31, 11.76iter/s]
Best score: 0.7472: : 331iter [00:31, 11.76iter/s]
Best score: 0.7472: : 332iter [00:31, 11.76iter/s]
Best score: 0.7472: : 333iter [00:31, 11.85iter/s]
Best score: 0.7472: : 333iter [00:31, 11.85iter/s]
Best score: 0.7472: : 334iter [00:31, 11.85iter/s]
Best score: 0.7472: : 335iter [00:31, 11.89iter/s]
Best score: 0.7472: : 335iter [00:32, 11.89iter/s]
Best score: 0.7472: : 336iter [00:32, 11.89iter/s]
Best score: 0.7472: : 337iter [00:32, 11.97iter/s]
Best score: 0.7472: : 337iter [00:32, 11.97iter/s]
Best score: 0.7472: : 338iter [00:32, 11.97iter/s]
Best score: 0.7472: : 339iter [00:32, 11.98iter/s]
Best score: 0.7472: : 339iter [00:32, 11.98iter/s]
Best score: 0.7472: : 340iter [00:32, 11.98iter/s]
Best score: 0.7472: : 341iter [00:32, 11.84iter/s]
Best score: 0.7472: : 341iter [00:32, 11.84iter/s]
Best score: 0.7472: : 342iter [00:32, 11.84iter/s]
Best score: 0.7472: : 343iter [00:32, 11.92iter/s]
Best score: 0.7472: : 343iter [00:32, 11.92iter/s]
Best score: 0.7472: : 344iter [00:32, 11.92iter/s]
Best score: 0.7472: : 345iter [00:32, 11.99iter/s]
Best score: 0.7472: : 345iter [00:32, 11.99iter/s]
Best score: 0.7472: : 346iter [00:32, 11.99iter/s]
Best score: 0.7472: : 347iter [00:32, 12.06iter/s]
Best score: 0.7472: : 347iter [00:33, 12.06iter/s]
Best score: 0.7472: : 348iter [00:33, 12.06iter/s]
Best score: 0.7472: : 349iter [00:33, 12.12iter/s]
[ITER 350] Best: 0.7472
[PARAMS] Current best parameters:
  fx: 559.2514
  fy: 559.5062
  px: 851.3561
  py: 994.8993
  k1: 0.01641530
  k2: -0.08636804
  k3: 0.06234996
  k4: -0.01540556
  p1: 0.00111067
  p2: 0.01036885
  p3: 0.00361755
  p4: -0.00363668
  s1: -0.0266
  s2: 0.0069
  s3: -0.0203
  s4: 0.0138
  tilt_x: -0.0406
  tilt_y: 0.0153
  scale: 2.9731
  rotation: -0.3482

Best score: 0.7472: : 349iter [00:33, 12.12iter/s]
[Periodic outlier @ iter 250] Removing 2000L frame 8 (score=7.62, threshold=7.46)
  Remaining frames: 75

Best score: 0.7472: : 350iter [00:33, 12.12iter/s]
Best score: 0.7472: : 351iter [00:33,  6.76iter/s]
Best score: 0.7472: : 351iter [00:33,  6.76iter/s]
Best score: 0.7472: : 352iter [00:33,  6.76iter/s]
Best score: 0.7472: : 353iter [00:33,  7.79iter/s]
Best score: 0.7472: : 353iter [00:33,  7.79iter/s]
Best score: 0.7472: : 354iter [00:34,  7.79iter/s]
Best score: 0.7472: : 355iter [00:34,  8.72iter/s]
Best score: 0.7472: : 355iter [00:34,  8.72iter/s]
Best score: 0.7472: : 356iter [00:34,  8.72iter/s]
Best score: 0.7472: : 357iter [00:34,  9.51iter/s]
Best score: 0.7472: : 357iter [00:34,  9.51iter/s]
Best score: 0.7472: : 358iter [00:34,  9.51iter/s]
Best score: 0.7472: : 359iter [00:34, 10.17iter/s]
Best score: 0.6448: : 359iter [00:34, 10.17iter/s]
Best score: 0.6448: : 360iter [00:34, 10.17iter/s]
Best score: 0.6448: : 361iter [00:34, 10.52iter/s]
Best score: 0.6448: : 361iter [00:34, 10.52iter/s]
Best score: 0.6448: : 362iter [00:34, 10.52iter/s]
Best score: 0.6448: : 363iter [00:34, 11.01iter/s]
Best score: 0.6448: : 363iter [00:34, 11.01iter/s]
Best score: 0.6448: : 364iter [00:34, 11.01iter/s]
Best score: 0.6448: : 365iter [00:34, 11.37iter/s]
Best score: 0.6448: : 365iter [00:34, 11.37iter/s]
Best score: 0.6448: : 366iter [00:35, 11.37iter/s]
Best score: 0.6448: : 367iter [00:35, 11.59iter/s]
Best score: 0.6448: : 367iter [00:35, 11.59iter/s]
Best score: 0.6448: : 368iter [00:35, 11.59iter/s]
Best score: 0.6448: : 369iter [00:35, 11.77iter/s]
Best score: 0.6448: : 369iter [00:35, 11.77iter/s]
Best score: 0.6448: : 370iter [00:35, 11.77iter/s]
Best score: 0.6448: : 371iter [00:35, 11.72iter/s]
Best score: 0.6448: : 371iter [00:35, 11.72iter/s]
Best score: 0.6448: : 372iter [00:35, 11.72iter/s]
Best score: 0.6448: : 373iter [00:35, 11.85iter/s]
Best score: 0.6448: : 373iter [00:35, 11.85iter/s]
Best score: 0.6448: : 374iter [00:35, 11.85iter/s]
Best score: 0.6448: : 375iter [00:35, 11.85iter/s]
Best score: 0.6448: : 375iter [00:35, 11.85iter/s]
Best score: 0.6448: : 376iter [00:35, 11.85iter/s]
Best score: 0.6448: : 377iter [00:35, 11.96iter/s]
Best score: 0.6448: : 377iter [00:35, 11.96iter/s]
Best score: 0.6448: : 378iter [00:36, 11.96iter/s]
Best score: 0.6448: : 379iter [00:36, 12.07iter/s]
Best score: 0.6448: : 379iter [00:36, 12.07iter/s]
Best score: 0.6448: : 380iter [00:36, 12.07iter/s]
Best score: 0.6448: : 381iter [00:36, 11.86iter/s]
Best score: 0.6448: : 381iter [00:36, 11.86iter/s]
Best score: 0.6448: : 382iter [00:36, 11.86iter/s]
Best score: 0.6448: : 383iter [00:36, 11.95iter/s]
Best score: 0.6448: : 383iter [00:36, 11.95iter/s]
Best score: 0.6448: : 384iter [00:36, 11.95iter/s]
Best score: 0.6448: : 385iter [00:36, 12.03iter/s]
Best score: 0.6448: : 385iter [00:36, 12.03iter/s]
Best score: 0.6448: : 386iter [00:36, 12.03iter/s]
Best score: 0.6448: : 387iter [00:36, 12.08iter/s]
Best score: 0.6448: : 387iter [00:36, 12.08iter/s]
Best score: 0.6448: : 388iter [00:36, 12.08iter/s]
Best score: 0.6448: : 389iter [00:36, 12.18iter/s]
Best score: 0.6448: : 389iter [00:36, 12.18iter/s]
Best score: 0.6448: : 390iter [00:37, 12.18iter/s]
Best score: 0.6448: : 391iter [00:37, 11.97iter/s]
Best score: 0.6448: : 391iter [00:37, 11.97iter/s]
Best score: 0.6448: : 392iter [00:37, 11.97iter/s]
Best score: 0.6448: : 393iter [00:37, 12.05iter/s]
Best score: 0.6448: : 393iter [00:37, 12.05iter/s]
Best score: 0.6448: : 394iter [00:37, 12.05iter/s]
Best score: 0.6448: : 395iter [00:37, 12.15iter/s]
Best score: 0.6448: : 395iter [00:37, 12.15iter/s]
Best score: 0.6448: : 396iter [00:37, 12.15iter/s]
Best score: 0.6448: : 397iter [00:37, 12.18iter/s]
Best score: 0.6448: : 397iter [00:37, 12.18iter/s]
Best score: 0.6448: : 398iter [00:37, 12.18iter/s]
Best score: 0.6448: : 399iter [00:37, 12.25iter/s]
[ITER 400] Best: 0.6448
[PARAMS] Current best parameters:
  fx: 559.2514
  fy: 559.5062
  px: 851.3561
  py: 994.8993
  k1: 0.01641530
  k2: -0.08636804
  k3: 0.06234996
  k4: -0.01540556
  p1: 0.00111067
  p2: 0.01036885
  p3: 0.00361755
  p4: -0.00363668
  s1: -0.0266
  s2: 0.0069
  s3: -0.0203
  s4: 0.0138
  tilt_x: -0.0406
  tilt_y: 0.0153
  scale: 2.9731
  rotation: -0.3482

Best score: 0.6448: : 399iter [00:37, 12.25iter/s]
Best score: 0.6448: : 400iter [00:38, 12.25iter/s]
Best score: 0.6448: : 401iter [00:38,  7.86iter/s]
Best score: 0.6448: : 401iter [00:38,  7.86iter/s]
Best score: 0.6448: : 402iter [00:38,  7.86iter/s]
Best score: 0.6448: : 403iter [00:38,  8.83iter/s]
Best score: 0.6448: : 403iter [00:38,  8.83iter/s]
Best score: 0.6448: : 404iter [00:38,  8.83iter/s]
Best score: 0.6448: : 405iter [00:38,  9.65iter/s]
Best score: 0.6448: : 405iter [00:38,  9.65iter/s]
Best score: 0.6448: : 406iter [00:38,  9.65iter/s]
Best score: 0.6448: : 407iter [00:38, 10.31iter/s]
Best score: 0.6448: : 407iter [00:38, 10.31iter/s]
Best score: 0.6448: : 408iter [00:38, 10.31iter/s]
Best score: 0.6448: : 409iter [00:38, 10.85iter/s]
Best score: 0.6448: : 409iter [00:38, 10.85iter/s]
Best score: 0.6448: : 410iter [00:38, 10.85iter/s]
Best score: 0.6448: : 411iter [00:38, 11.03iter/s]
Best score: 0.6448: : 411iter [00:39, 11.03iter/s]
Best score: 0.6448: : 412iter [00:39, 11.03iter/s]
Best score: 0.6448: : 413iter [00:39, 11.40iter/s]
Best score: 0.6448: : 413iter [00:39, 11.40iter/s]
Best score: 0.6448: : 414iter [00:39, 11.40iter/s]
Best score: 0.6448: : 415iter [00:39, 11.70iter/s]
Best score: 0.6448: : 415iter [00:39, 11.70iter/s]
Best score: 0.6448: : 416iter [00:39, 11.70iter/s]
Best score: 0.6448: : 417iter [00:39, 11.83iter/s]
Best score: 0.6448: : 417iter [00:39, 11.83iter/s]
Best score: 0.6448: : 418iter [00:39, 11.83iter/s]
Best score: 0.6448: : 419iter [00:39, 11.04iter/s]
Best score: 0.6448: : 419iter [00:39, 11.04iter/s]
Best score: 0.6448: : 420iter [00:39, 11.04iter/s]
Best score: 0.6448: : 421iter [00:39, 11.19iter/s]
Best score: 0.6448: : 421iter [00:39, 11.19iter/s]
Best score: 0.6448: : 422iter [00:39, 11.19iter/s]
Best score: 0.6448: : 423iter [00:39, 11.49iter/s]
Best score: 0.6448: : 423iter [00:40, 11.49iter/s]
Best score: 0.6448: : 424iter [00:40, 11.49iter/s]
Best score: 0.6448: : 425iter [00:40, 11.74iter/s]
Best score: 0.6448: : 425iter [00:40, 11.74iter/s]
Best score: 0.6448: : 426iter [00:40, 11.74iter/s]
Best score: 0.6448: : 427iter [00:40, 11.92iter/s]
Best score: 0.6448: : 427iter [00:40, 11.92iter/s]
Best score: 0.6448: : 428iter [00:40, 11.92iter/s]
Best score: 0.6448: : 429iter [00:40, 12.02iter/s]
Best score: 0.6448: : 429iter [00:40, 12.02iter/s]
Best score: 0.6448: : 430iter [00:40, 12.02iter/s]
Best score: 0.6448: : 431iter [00:40, 11.87iter/s]
Best score: 0.6448: : 431iter [00:40, 11.87iter/s]
Best score: 0.6448: : 432iter [00:40, 11.87iter/s]
Best score: 0.6448: : 433iter [00:40, 11.99iter/s]
Best score: 0.6448: : 433iter [00:40, 11.99iter/s]
Best score: 0.6448: : 434iter [00:40, 11.99iter/s]
Best score: 0.6448: : 435iter [00:40, 12.04iter/s]
Best score: 0.6448: : 435iter [00:41, 12.04iter/s]
Best score: 0.6448: : 436iter [00:41, 12.04iter/s]
Best score: 0.6448: : 437iter [00:41, 12.15iter/s]
Best score: 0.6448: : 437iter [00:41, 12.15iter/s]
Best score: 0.6448: : 438iter [00:41, 12.15iter/s]
Best score: 0.6448: : 439iter [00:41, 12.25iter/s]
Best score: 0.6448: : 439iter [00:41, 12.25iter/s]
Best score: 0.6448: : 440iter [00:41, 12.25iter/s]
Best score: 0.6448: : 441iter [00:41, 12.07iter/s]
Best score: 0.6448: : 441iter [00:41, 12.07iter/s]
Best score: 0.6448: : 442iter [00:41, 12.07iter/s]
Best score: 0.6448: : 443iter [00:41, 12.17iter/s]
Best score: 0.6448: : 443iter [00:41, 12.17iter/s]
Best score: 0.6448: : 444iter [00:41, 12.17iter/s]
Best score: 0.6448: : 445iter [00:41, 12.27iter/s]
Best score: 0.6448: : 445iter [00:41, 12.27iter/s]
Best score: 0.6448: : 446iter [00:41, 12.27iter/s]
Best score: 0.6448: : 447iter [00:41, 12.27iter/s]
Best score: 0.6448: : 447iter [00:42, 12.27iter/s]
Best score: 0.6448: : 448iter [00:42, 12.27iter/s]
Best score: 0.6448: : 449iter [00:42, 12.32iter/s]
Best score: 0.6448: : 449iter [00:42, 12.32iter/s]
[ITER 450] Best: 0.6448
[PARAMS] Current best parameters:
  fx: 559.2514
  fy: 559.5062
  px: 851.3561
  py: 994.8993
  k1: 0.01641530
  k2: -0.08636804
  k3: 0.06234996
  k4: -0.01540556
  p1: 0.00111067
  p2: 0.01036885
  p3: 0.00361755
  p4: -0.00363668
  s1: -0.0266
  s2: 0.0069
  s3: -0.0203
  s4: 0.0138
  tilt_x: -0.0406
  tilt_y: 0.0153
  scale: 2.9731
  rotation: -0.3482

Best score: 0.6448: : 450iter [00:42, 12.32iter/s]
Best score: 0.6448: : 451iter [00:42,  7.86iter/s]
Best score: 0.6448: : 451iter [00:42,  7.86iter/s]
Best score: 0.6448: : 452iter [00:42,  7.86iter/s]
Best score: 0.6448: : 453iter [00:42,  8.84iter/s]
Best score: 0.6448: : 453iter [00:42,  8.84iter/s]
Best score: 0.6448: : 454iter [00:42,  8.84iter/s]
Best score: 0.6448: : 455iter [00:42,  9.62iter/s]
Best score: 0.6448: : 455iter [00:42,  9.62iter/s]
Best score: 0.6448: : 456iter [00:43,  9.62iter/s]
Best score: 0.6448: : 457iter [00:43, 10.26iter/s]
Best score: 0.6448: : 457iter [00:43, 10.26iter/s]
Best score: 0.6448: : 458iter [00:43, 10.26iter/s]
Best score: 0.6448: : 459iter [00:43, 10.73iter/s]
Best score: 0.6448: : 459iter [00:43, 10.73iter/s]
Best score: 0.6448: : 460iter [00:43, 10.73iter/s]
Best score: 0.6448: : 461iter [00:43, 10.96iter/s]
Best score: 0.6448: : 461iter [00:43, 10.96iter/s]
Best score: 0.6448: : 462iter [00:43, 10.96iter/s]
Best score: 0.6448: : 463iter [00:43, 11.31iter/s]
Best score: 0.6448: : 463iter [00:43, 11.31iter/s]
Best score: 0.6448: : 464iter [00:43, 11.31iter/s]
Best score: 0.6448: : 465iter [00:43, 11.55iter/s]
Best score: 0.6448: : 465iter [00:43, 11.55iter/s]
Best score: 0.6448: : 466iter [00:43, 11.55iter/s]
Best score: 0.6448: : 467iter [00:43, 11.73iter/s]
Best score: 0.6448: : 467iter [00:43, 11.73iter/s]
Best score: 0.6448: : 468iter [00:44, 11.73iter/s]
Best score: 0.6448: : 469iter [00:44, 11.90iter/s]
Best score: 0.6448: : 469iter [00:44, 11.90iter/s]
Best score: 0.6448: : 470iter [00:44, 11.90iter/s]
Best score: 0.6448: : 471iter [00:44, 11.83iter/s]
Best score: 0.6448: : 471iter [00:44, 11.83iter/s]
Best score: 0.6448: : 472iter [00:44, 11.83iter/s]
Best score: 0.6448: : 473iter [00:44, 12.01iter/s]
Best score: 0.6448: : 473iter [00:44, 12.01iter/s]
Best score: 0.6448: : 474iter [00:44, 12.01iter/s]
Best score: 0.6448: : 475iter [00:44, 12.14iter/s]
Best score: 0.6448: : 475iter [00:44, 12.14iter/s]
Best score: 0.6448: : 476iter [00:44, 12.14iter/s]
Best score: 0.6448: : 477iter [00:44, 12.21iter/s]
Best score: 0.6448: : 477iter [00:44, 12.21iter/s]
Best score: 0.6448: : 478iter [00:44, 12.21iter/s]
Best score: 0.6448: : 479iter [00:44, 12.18iter/s]
Best score: 0.6448: : 479iter [00:44, 12.18iter/s]
Best score: 0.6448: : 480iter [00:45, 12.18iter/s]
Best score: 0.6448: : 481iter [00:45, 11.94iter/s]
Best score: 0.6448: : 481iter [00:45, 11.94iter/s]
Best score: 0.6448: : 482iter [00:45, 11.94iter/s]
Best score: 0.6448: : 483iter [00:45, 12.01iter/s]
Best score: 0.6448: : 483iter [00:45, 12.01iter/s]
Best score: 0.6448: : 484iter [00:45, 12.01iter/s]
Best score: 0.6448: : 485iter [00:45, 12.07iter/s]
Best score: 0.6448: : 485iter [00:45, 12.07iter/s]
Best score: 0.6448: : 486iter [00:45, 12.07iter/s]
Best score: 0.6448: : 487iter [00:45, 11.53iter/s]
Best score: 0.6448: : 487iter [00:45, 11.53iter/s]
Best score: 0.6448: : 488iter [00:45, 11.53iter/s]
Best score: 0.6448: : 489iter [00:45, 11.70iter/s]
Best score: 0.6448: : 489iter [00:45, 11.70iter/s]
Best score: 0.6448: : 490iter [00:45, 11.70iter/s]
Best score: 0.6448: : 491iter [00:45, 11.06iter/s]
Best score: 0.6448: : 491iter [00:46, 11.06iter/s]
Best score: 0.6448: : 492iter [00:46, 11.06iter/s]
Best score: 0.6448: : 493iter [00:46, 11.34iter/s]
Best score: 0.6448: : 493iter [00:46, 11.34iter/s]
Best score: 0.6448: : 494iter [00:46, 11.34iter/s]
Best score: 0.6448: : 495iter [00:46, 11.56iter/s]
Best score: 0.6448: : 495iter [00:46, 11.56iter/s]
Best score: 0.6448: : 496iter [00:46, 11.56iter/s]
Best score: 0.6448: : 497iter [00:46, 11.80iter/s]
Best score: 0.6448: : 497iter [00:46, 11.80iter/s]
Best score: 0.6448: : 498iter [00:46, 11.80iter/s]
Best score: 0.6448: : 499iter [00:46, 11.85iter/s]
[ITER 500] Best: 0.6448
[PARAMS] Current best parameters:
  fx: 559.2514
  fy: 559.5062
  px: 851.3561
  py: 994.8993
  k1: 0.01641530
  k2: -0.08636804
  k3: 0.06234996
  k4: -0.01540556
  p1: 0.00111067
  p2: 0.01036885
  p3: 0.00361755
  p4: -0.00363668
  s1: -0.0266
  s2: 0.0069
  s3: -0.0203
  s4: 0.0138
  tilt_x: -0.0406
  tilt_y: 0.0153
  scale: 2.9731
  rotation: -0.3482

Best score: 0.6448: : 499iter [00:46, 11.85iter/s]
Best score: 0.6448: : 500iter [00:47, 11.85iter/s]
Best score: 0.6448: : 501iter [00:47,  7.58iter/s]
Best score: 0.6448: : 501iter [00:47,  7.58iter/s]
Best score: 0.6448: : 502iter [00:47,  7.58iter/s]
Best score: 0.6448: : 503iter [00:47,  8.51iter/s]
Best score: 0.6448: : 503iter [00:47,  8.51iter/s]
Best score: 0.6448: : 504iter [00:47,  8.51iter/s]
Best score: 0.6448: : 505iter [00:47,  9.33iter/s]
Best score: 0.6448: : 505iter [00:47,  9.33iter/s]
Best score: 0.6448: : 506iter [00:47,  9.33iter/s]
Best score: 0.6448: : 507iter [00:47, 10.03iter/s]
Best score: 0.6448: : 507iter [00:47, 10.03iter/s]
Best score: 0.6448: : 508iter [00:47, 10.03iter/s]
Best score: 0.6448: : 509iter [00:47, 10.60iter/s]
Best score: 0.5587: : 509iter [00:47, 10.60iter/s]
Best score: 0.5587: : 510iter [00:47, 10.60iter/s]
Best score: 0.5587: : 511iter [00:47, 10.89iter/s]
Best score: 0.5587: : 511iter [00:48, 10.89iter/s]
Best score: 0.5587: : 512iter [00:48, 10.89iter/s]
Best score: 0.5587: : 513iter [00:48, 11.29iter/s]
Best score: 0.5587: : 513iter [00:48, 11.29iter/s]
Best score: 0.5587: : 514iter [00:48, 11.29iter/s]
Best score: 0.5587: : 515iter [00:48, 11.52iter/s]
Best score: 0.5587: : 515iter [00:48, 11.52iter/s]
Best score: 0.5587: : 516iter [00:48, 11.52iter/s]
Best score: 0.5587: : 517iter [00:48, 11.74iter/s]
Best score: 0.5587: : 517iter [00:48, 11.74iter/s]
Best score: 0.5587: : 518iter [00:48, 11.74iter/s]
Best score: 0.5587: : 519iter [00:48, 11.89iter/s]
Best score: 0.5446: : 519iter [00:48, 11.89iter/s]
Best score: 0.5446: : 520iter [00:48, 11.89iter/s]
Best score: 0.5446: : 521iter [00:48, 11.74iter/s]
Best score: 0.5446: : 521iter [00:48, 11.74iter/s]
Best score: 0.5446: : 522iter [00:48, 11.74iter/s]
Best score: 0.5446: : 523iter [00:48, 11.89iter/s]
Best score: 0.5446: : 523iter [00:48, 11.89iter/s]
Best score: 0.5446: : 524iter [00:49, 11.89iter/s]
Best score: 0.5446: : 525iter [00:49, 12.03iter/s]
Best score: 0.5446: : 525iter [00:49, 12.03iter/s]
Best score: 0.5446: : 526iter [00:49, 12.03iter/s]
Best score: 0.5446: : 527iter [00:49, 12.12iter/s]
Best score: 0.5446: : 527iter [00:49, 12.12iter/s]
Best score: 0.5446: : 528iter [00:49, 12.12iter/s]
Best score: 0.5446: : 529iter [00:49, 12.11iter/s]
Best score: 0.5446: : 529iter [00:49, 12.11iter/s]
Best score: 0.5446: : 530iter [00:49, 12.11iter/s]
Best score: 0.5446: : 531iter [00:49, 11.95iter/s]
Best score: 0.5446: : 531iter [00:49, 11.95iter/s]
Best score: 0.5446: : 532iter [00:49, 11.95iter/s]
Best score: 0.5446: : 533iter [00:49, 12.07iter/s]
Best score: 0.5446: : 533iter [00:49, 12.07iter/s]
Best score: 0.5446: : 534iter [00:49, 12.07iter/s]
Best score: 0.5446: : 535iter [00:49, 12.11iter/s]
Best score: 0.5446: : 535iter [00:49, 12.11iter/s]
Best score: 0.5446: : 536iter [00:50, 12.11iter/s]
Best score: 0.5446: : 537iter [00:50, 12.14iter/s]
Best score: 0.5446: : 537iter [00:50, 12.14iter/s]
Best score: 0.5446: : 538iter [00:50, 12.14iter/s]
Best score: 0.5446: : 539iter [00:50, 12.16iter/s]
Best score: 0.5446: : 539iter [00:50, 12.16iter/s]
Best score: 0.5446: : 540iter [00:50, 12.16iter/s]
Best score: 0.5446: : 541iter [00:50, 11.97iter/s]
Best score: 0.5446: : 541iter [00:50, 11.97iter/s]
Best score: 0.5446: : 542iter [00:50, 11.97iter/s]
Best score: 0.5446: : 543iter [00:50, 12.03iter/s]
Best score: 0.5446: : 543iter [00:50, 12.03iter/s]
Best score: 0.5446: : 544iter [00:50, 12.03iter/s]
Best score: 0.5446: : 545iter [00:50, 12.07iter/s]
Best score: 0.5446: : 545iter [00:50, 12.07iter/s]
Best score: 0.5446: : 546iter [00:50, 12.07iter/s]
Best score: 0.5446: : 547iter [00:50, 12.08iter/s]
Best score: 0.5446: : 547iter [00:50, 12.08iter/s]
Best score: 0.5446: : 548iter [00:51, 12.08iter/s]
Best score: 0.5446: : 549iter [00:51, 12.10iter/s]
[ITER 550] Best: 0.4954
[PARAMS] Current best parameters:
  fx: 556.9707
  fy: 557.5281
  px: 851.7061
  py: 998.2095
  k1: 0.01699755
  k2: -0.08542066
  k3: 0.06196409
  k4: -0.01526110
  p1: 0.00461200
  p2: 0.01786126
  p3: 0.00568467
  p4: -0.00856867
  s1: -0.0247
  s2: 0.0059
  s3: -0.0186
  s4: 0.0168
  tilt_x: -0.0332
  tilt_y: 0.0349
  scale: 2.9766
  rotation: -0.4343

Best score: 0.4954: : 549iter [00:51, 12.10iter/s]
Best score: 0.4954: : 550iter [00:51, 12.10iter/s]
Best score: 0.4954: : 551iter [00:51,  7.82iter/s]
Best score: 0.4954: : 551iter [00:51,  7.82iter/s]
Best score: 0.4954: : 552iter [00:51,  7.82iter/s]
Best score: 0.4954: : 553iter [00:51,  8.76iter/s]
Best score: 0.4954: : 553iter [00:51,  8.76iter/s]
Best score: 0.4954: : 554iter [00:51,  8.76iter/s]
Best score: 0.4954: : 555iter [00:51,  9.57iter/s]
Best score: 0.4954: : 555iter [00:51,  9.57iter/s]
Best score: 0.4954: : 556iter [00:52,  9.57iter/s]
Best score: 0.4954: : 557iter [00:52, 10.20iter/s]
Best score: 0.4954: : 557iter [00:52, 10.20iter/s]
Best score: 0.4954: : 558iter [00:52, 10.20iter/s]
Best score: 0.4954: : 559iter [00:52, 10.72iter/s]
Best score: 0.3811: : 559iter [00:52, 10.72iter/s]
Best score: 0.3811: : 560iter [00:52, 10.72iter/s]
Best score: 0.3811: : 561iter [00:52, 10.94iter/s]
Best score: 0.3811: : 561iter [00:52, 10.94iter/s]
Best score: 0.3811: : 562iter [00:52, 10.94iter/s]
Best score: 0.3811: : 563iter [00:52, 11.28iter/s]
Best score: 0.3811: : 563iter [00:52, 11.28iter/s]
Best score: 0.3811: : 564iter [00:52, 11.28iter/s]
Best score: 0.3811: : 565iter [00:52, 11.50iter/s]
Best score: 0.3811: : 565iter [00:52, 11.50iter/s]
Best score: 0.3811: : 566iter [00:52, 11.50iter/s]
Best score: 0.3811: : 567iter [00:52, 11.65iter/s]
Best score: 0.3811: : 567iter [00:52, 11.65iter/s]
Best score: 0.3811: : 568iter [00:53, 11.65iter/s]
Best score: 0.3811: : 569iter [00:53, 11.80iter/s]
Best score: 0.3811: : 569iter [00:53, 11.80iter/s]
Best score: 0.3811: : 570iter [00:53, 11.80iter/s]
Best score: 0.3811: : 571iter [00:53, 11.77iter/s]
Best score: 0.3811: : 571iter [00:53, 11.77iter/s]
Best score: 0.3811: : 572iter [00:53, 11.77iter/s]
Best score: 0.3811: : 573iter [00:53, 11.86iter/s]
Best score: 0.3811: : 573iter [00:53, 11.86iter/s]
Best score: 0.3811: : 574iter [00:53, 11.86iter/s]
Best score: 0.3811: : 575iter [00:53, 11.97iter/s]
Best score: 0.3811: : 575iter [00:53, 11.97iter/s]
Best score: 0.3811: : 576iter [00:53, 11.97iter/s]
Best score: 0.3811: : 577iter [00:53, 12.07iter/s]
Best score: 0.3811: : 577iter [00:53, 12.07iter/s]
Best score: 0.3811: : 578iter [00:53, 12.07iter/s]
Best score: 0.3811: : 579iter [00:53, 12.07iter/s]
Best score: 0.3811: : 579iter [00:53, 12.07iter/s]
Best score: 0.3811: : 580iter [00:54, 12.07iter/s]
Best score: 0.3811: : 581iter [00:54, 11.91iter/s]
Best score: 0.3811: : 581iter [00:54, 11.91iter/s]
Best score: 0.3811: : 582iter [00:54, 11.91iter/s]
Best score: 0.3811: : 583iter [00:54, 11.99iter/s]
Best score: 0.3811: : 583iter [00:54, 11.99iter/s]
Best score: 0.3811: : 584iter [00:54, 11.99iter/s]
Best score: 0.3811: : 585iter [00:54, 12.05iter/s]
Best score: 0.3811: : 585iter [00:54, 12.05iter/s]
Best score: 0.3811: : 586iter [00:54, 12.05iter/s]
Best score: 0.3811: : 587iter [00:54, 12.07iter/s]
Best score: 0.3811: : 587iter [00:54, 12.07iter/s]
Best score: 0.3811: : 588iter [00:54, 12.07iter/s]
Best score: 0.3811: : 589iter [00:54, 12.07iter/s]
Best score: 0.3811: : 589iter [00:54, 12.07iter/s]
Best score: 0.3811: : 590iter [00:54, 12.07iter/s]
Best score: 0.3811: : 591iter [00:54, 11.93iter/s]
Best score: 0.3811: : 591iter [00:54, 11.93iter/s]
Best score: 0.3811: : 592iter [00:55, 11.93iter/s]
Best score: 0.3811: : 593iter [00:55, 11.99iter/s]
Best score: 0.3811: : 593iter [00:55, 11.99iter/s]
Best score: 0.3811: : 594iter [00:55, 11.99iter/s]
Best score: 0.3811: : 595iter [00:55, 12.06iter/s]
Best score: 0.3811: : 595iter [00:55, 12.06iter/s]
Best score: 0.3811: : 596iter [00:55, 12.06iter/s]
Best score: 0.3811: : 597iter [00:55, 12.10iter/s]
Best score: 0.3811: : 597iter [00:55, 12.10iter/s]
Best score: 0.3811: : 598iter [00:55, 12.10iter/s]
Best score: 0.3811: : 599iter [00:55, 12.15iter/s]
[ITER 600] Best: 0.3664
[PARAMS] Current best parameters:
  fx: 559.5151
  fy: 559.6381
  px: 849.8961
  py: 996.8665
  k1: 0.01696656
  k2: -0.08560681
  k3: 0.06006460
  k4: -0.01436018
  p1: 0.00426311
  p2: 0.01017818
  p3: 0.00796893
  p4: -0.00913345
  s1: -0.0249
  s2: 0.0090
  s3: -0.0208
  s4: 0.0155
  tilt_x: -0.0362
  tilt_y: 0.0267
  scale: 2.9720
  rotation: -0.3926

Best score: 0.3664: : 599iter [00:55, 12.15iter/s]
[Periodic outlier @ iter 500] Removing 2000L frame 16 (score=3.46, threshold=2.55)
  Remaining frames: 74

Best score: 0.3664: : 600iter [00:56, 12.15iter/s]
Best score: 0.3664: : 601iter [00:56,  6.75iter/s]
Best score: 0.3664: : 601iter [00:56,  6.75iter/s]
Best score: 0.3664: : 602iter [00:56,  6.75iter/s]
Best score: 0.3664: : 603iter [00:56,  7.79iter/s]
Best score: 0.3664: : 603iter [00:56,  7.79iter/s]
Best score: 0.3664: : 604iter [00:56,  7.79iter/s]
Best score: 0.3664: : 605iter [00:56,  8.73iter/s]
Best score: 0.3664: : 605iter [00:56,  8.73iter/s]
Best score: 0.3664: : 606iter [00:56,  8.73iter/s]
Best score: 0.3664: : 607iter [00:56,  9.53iter/s]
Best score: 0.3664: : 607iter [00:56,  9.53iter/s]
Best score: 0.3664: : 608iter [00:56,  9.53iter/s]
Best score: 0.3664: : 609iter [00:56, 10.18iter/s]
Best score: 0.3271: : 609iter [00:56, 10.18iter/s]
Best score: 0.3271: : 610iter [00:56, 10.18iter/s]
Best score: 0.3271: : 611iter [00:56, 10.52iter/s]
Best score: 0.3271: : 611iter [00:57, 10.52iter/s]
Best score: 0.3271: : 612iter [00:57, 10.52iter/s]
Best score: 0.3271: : 613iter [00:57, 10.99iter/s]
Best score: 0.3271: : 613iter [00:57, 10.99iter/s]
Best score: 0.3271: : 614iter [00:57, 10.99iter/s]
Best score: 0.3271: : 615iter [00:57, 11.31iter/s]
Best score: 0.3271: : 615iter [00:57, 11.31iter/s]
Best score: 0.3271: : 616iter [00:57, 11.31iter/s]
Best score: 0.3271: : 617iter [00:57, 11.51iter/s]
Best score: 0.3271: : 617iter [00:57, 11.51iter/s]
Best score: 0.3271: : 618iter [00:57, 11.51iter/s]
Best score: 0.3271: : 619iter [00:57, 11.71iter/s]
Best score: 0.3271: : 619iter [00:57, 11.71iter/s]
Best score: 0.3271: : 620iter [00:57, 11.71iter/s]
Best score: 0.3271: : 621iter [00:57, 11.64iter/s]
Best score: 0.3271: : 621iter [00:57, 11.64iter/s]
Best score: 0.3271: : 622iter [00:57, 11.64iter/s]
Best score: 0.3271: : 623iter [00:57, 11.78iter/s]
Best score: 0.3271: : 623iter [00:58, 11.78iter/s]
Best score: 0.3271: : 624iter [00:58, 11.78iter/s]
Best score: 0.3271: : 625iter [00:58, 11.85iter/s]
Best score: 0.3271: : 625iter [00:58, 11.85iter/s]
Best score: 0.3271: : 626iter [00:58, 11.85iter/s]
Best score: 0.3271: : 627iter [00:58, 11.89iter/s]
Best score: 0.3271: : 627iter [00:58, 11.89iter/s]
Best score: 0.3271: : 628iter [00:58, 11.89iter/s]
Best score: 0.3271: : 629iter [00:58, 11.94iter/s]
Best score: 0.3271: : 629iter [00:58, 11.94iter/s]
Best score: 0.3271: : 630iter [00:58, 11.94iter/s]
Best score: 0.3271: : 631iter [00:58, 11.80iter/s]
Best score: 0.3271: : 631iter [00:58, 11.80iter/s]
Best score: 0.3271: : 632iter [00:58, 11.80iter/s]
Best score: 0.3271: : 633iter [00:58, 11.88iter/s]
Best score: 0.3271: : 633iter [00:58, 11.88iter/s]
Best score: 0.3271: : 634iter [00:58, 11.88iter/s]
Best score: 0.3271: : 635iter [00:58, 11.93iter/s]
Best score: 0.3271: : 635iter [00:59, 11.93iter/s]
Best score: 0.3271: : 636iter [00:59, 11.93iter/s]
Best score: 0.3271: : 637iter [00:59, 12.00iter/s]
Best score: 0.3271: : 637iter [00:59, 12.00iter/s]
Best score: 0.3271: : 638iter [00:59, 12.00iter/s]
Best score: 0.3271: : 639iter [00:59, 12.04iter/s]
Best score: 0.3271: : 639iter [00:59, 12.04iter/s]
Best score: 0.3271: : 640iter [00:59, 12.04iter/s]
Best score: 0.3271: : 641iter [00:59, 11.85iter/s]
Best score: 0.3271: : 641iter [00:59, 11.85iter/s]
Best score: 0.3271: : 642iter [00:59, 11.85iter/s]
Best score: 0.3271: : 643iter [00:59, 11.93iter/s]
Best score: 0.3271: : 643iter [00:59, 11.93iter/s]
Best score: 0.3271: : 644iter [00:59, 11.93iter/s]
Best score: 0.3271: : 645iter [00:59, 11.98iter/s]
Best score: 0.3271: : 645iter [00:59, 11.98iter/s]
Best score: 0.3271: : 646iter [00:59, 11.98iter/s]
Best score: 0.3271: : 647iter [00:59, 12.01iter/s]
Best score: 0.3271: : 647iter [01:00, 12.01iter/s]
Best score: 0.3271: : 648iter [01:00, 12.01iter/s]
Best score: 0.3271: : 649iter [01:00, 12.04iter/s]
[ITER 650] Best: 0.3271
[PARAMS] Current best parameters:
  fx: 559.5151
  fy: 559.6381
  px: 849.8961
  py: 996.8665
  k1: 0.01696656
  k2: -0.08560681
  k3: 0.06006460
  k4: -0.01436018
  p1: 0.00426311
  p2: 0.01017818
  p3: 0.00796893
  p4: -0.00913345
  s1: -0.0249
  s2: 0.0090
  s3: -0.0208
  s4: 0.0155
  tilt_x: -0.0362
  tilt_y: 0.0267
  scale: 2.9720
  rotation: -0.3926

Best score: 0.3271: : 649iter [01:00, 12.04iter/s]
Best score: 0.3271: : 650iter [01:00, 12.04iter/s]
Best score: 0.3271: : 651iter [01:00,  7.82iter/s]
Best score: 0.3271: : 651iter [01:00,  7.82iter/s]
Best score: 0.3271: : 652iter [01:00,  7.82iter/s]
Best score: 0.3271: : 653iter [01:00,  8.79iter/s]
Best score: 0.3271: : 653iter [01:00,  8.79iter/s]
Best score: 0.3271: : 654iter [01:00,  8.79iter/s]
Best score: 0.3271: : 655iter [01:00,  9.57iter/s]
Best score: 0.3271: : 655iter [01:00,  9.57iter/s]
Best score: 0.3271: : 656iter [01:01,  9.57iter/s]
Best score: 0.3271: : 657iter [01:01, 10.22iter/s]
Best score: 0.3271: : 657iter [01:01, 10.22iter/s]
Best score: 0.3271: : 658iter [01:01, 10.22iter/s]
Best score: 0.3271: : 659iter [01:01, 10.73iter/s]
Best score: 0.3271: : 659iter [01:01, 10.73iter/s]
Best score: 0.3271: : 660iter [01:01, 10.73iter/s]
Best score: 0.3271: : 661iter [01:01, 10.96iter/s]
Best score: 0.3271: : 661iter [01:01, 10.96iter/s]
Best score: 0.3271: : 662iter [01:01, 10.96iter/s]
Best score: 0.3271: : 663iter [01:01, 11.28iter/s]
Best score: 0.3271: : 663iter [01:01, 11.28iter/s]
Best score: 0.3271: : 664iter [01:01, 11.28iter/s]
Best score: 0.3271: : 665iter [01:01, 11.53iter/s]
Best score: 0.3271: : 665iter [01:01, 11.53iter/s]
Best score: 0.3271: : 666iter [01:01, 11.53iter/s]
Best score: 0.3271: : 667iter [01:01, 11.72iter/s]
Best score: 0.3271: : 667iter [01:01, 11.72iter/s]
Best score: 0.3271: : 668iter [01:02, 11.72iter/s]
Best score: 0.3271: : 669iter [01:02, 11.85iter/s]
Best score: 0.3271: : 669iter [01:02, 11.85iter/s]
Best score: 0.3271: : 670iter [01:02, 11.85iter/s]
Best score: 0.3271: : 671iter [01:02, 11.79iter/s]
Best score: 0.3271: : 671iter [01:02, 11.79iter/s]
Best score: 0.3271: : 672iter [01:02, 11.79iter/s]
Best score: 0.3271: : 673iter [01:02, 11.93iter/s]
Best score: 0.3271: : 673iter [01:02, 11.93iter/s]
Best score: 0.3271: : 674iter [01:02, 11.93iter/s]
Best score: 0.3271: : 675iter [01:02,  9.35iter/s]
Best score: 0.3271: : 675iter [01:02,  9.35iter/s]
Best score: 0.3271: : 676iter [01:02,  9.35iter/s]
Best score: 0.3271: : 677iter [01:02, 10.05iter/s]
Best score: 0.3271: : 677iter [01:02, 10.05iter/s]
Best score: 0.3271: : 678iter [01:03, 10.05iter/s]
Best score: 0.3271: : 679iter [01:03, 10.63iter/s]
Best score: 0.3271: : 679iter [01:03, 10.63iter/s]
Best score: 0.3271: : 680iter [01:03, 10.63iter/s]
Best score: 0.3271: : 681iter [01:03, 10.88iter/s]
Best score: 0.3271: : 681iter [01:03, 10.88iter/s]
Best score: 0.3271: : 682iter [01:03, 10.88iter/s]
Best score: 0.3271: : 683iter [01:03, 11.26iter/s]
Best score: 0.3271: : 683iter [01:03, 11.26iter/s]
Best score: 0.3271: : 684iter [01:03, 11.26iter/s]
Best score: 0.3271: : 685iter [01:03, 11.54iter/s]
Best score: 0.3271: : 685iter [01:03, 11.54iter/s]
Best score: 0.3271: : 686iter [01:03, 11.54iter/s]
Best score: 0.3271: : 687iter [01:03, 11.77iter/s]
Best score: 0.3271: : 687iter [01:03, 11.77iter/s]
Best score: 0.3271: : 688iter [01:03, 11.77iter/s]
Best score: 0.3271: : 689iter [01:03, 11.88iter/s]
Best score: 0.3271: : 689iter [01:03, 11.88iter/s]
Best score: 0.3271: : 690iter [01:04, 11.88iter/s]
Best score: 0.3271: : 691iter [01:04, 11.78iter/s]
Best score: 0.3271: : 691iter [01:04, 11.78iter/s]
Best score: 0.3271: : 692iter [01:04, 11.78iter/s]
Best score: 0.3271: : 693iter [01:04, 11.85iter/s]
Best score: 0.3271: : 693iter [01:04, 11.85iter/s]
Best score: 0.3271: : 694iter [01:04, 11.85iter/s]
Best score: 0.3271: : 695iter [01:04, 11.93iter/s]
Best score: 0.3271: : 695iter [01:04, 11.93iter/s]
Best score: 0.3271: : 696iter [01:04, 11.93iter/s]
Best score: 0.3271: : 697iter [01:04, 12.01iter/s]
Best score: 0.3271: : 697iter [01:04, 12.01iter/s]
Best score: 0.3271: : 698iter [01:04, 12.01iter/s]
Best score: 0.3271: : 699iter [01:04, 12.07iter/s]
[ITER 700] Best: 0.3271
[PARAMS] Current best parameters:
  fx: 559.5151
  fy: 559.6381
  px: 849.8961
  py: 996.8665
  k1: 0.01696656
  k2: -0.08560681
  k3: 0.06006460
  k4: -0.01436018
  p1: 0.00426311
  p2: 0.01017818
  p3: 0.00796893
  p4: -0.00913345
  s1: -0.0249
  s2: 0.0090
  s3: -0.0208
  s4: 0.0155
  tilt_x: -0.0362
  tilt_y: 0.0267
  scale: 2.9720
  rotation: -0.3926

Best score: 0.3271: : 699iter [01:04, 12.07iter/s]
Best score: 0.3271: : 700iter [01:05, 12.07iter/s]
Best score: 0.3271: : 701iter [01:05,  7.68iter/s]
Best score: 0.3271: : 701iter [01:05,  7.68iter/s]
Best score: 0.3271: : 702iter [01:05,  7.68iter/s]
Best score: 0.3271: : 703iter [01:05,  8.65iter/s]
Best score: 0.3271: : 703iter [01:05,  8.65iter/s]
Best score: 0.3271: : 704iter [01:05,  8.65iter/s]
Best score: 0.3271: : 705iter [01:05,  9.50iter/s]
Best score: 0.3271: : 705iter [01:05,  9.50iter/s]
Best score: 0.3271: : 706iter [01:05,  9.50iter/s]
Best score: 0.3271: : 707iter [01:05, 10.20iter/s]
Best score: 0.3271: : 707iter [01:05, 10.20iter/s]
Best score: 0.3271: : 708iter [01:05, 10.20iter/s]
Best score: 0.3271: : 709iter [01:05, 10.78iter/s]
Best score: 0.3271: : 709iter [01:05, 10.78iter/s]
Best score: 0.3271: : 710iter [01:06, 10.78iter/s]
Best score: 0.3271: : 711iter [01:06, 11.02iter/s]
Best score: 0.3271: : 711iter [01:06, 11.02iter/s]
Best score: 0.3271: : 712iter [01:06, 11.02iter/s]
Best score: 0.3271: : 713iter [01:06, 11.40iter/s]
Best score: 0.3271: : 713iter [01:06, 11.40iter/s]
Best score: 0.3271: : 714iter [01:06, 11.40iter/s]
Best score: 0.3271: : 715iter [01:06, 11.64iter/s]
Best score: 0.3271: : 715iter [01:06, 11.64iter/s]
Best score: 0.3271: : 716iter [01:06, 11.64iter/s]
Best score: 0.3271: : 717iter [01:06, 11.84iter/s]
Best score: 0.3271: : 717iter [01:06, 11.84iter/s]
Best score: 0.3271: : 718iter [01:06, 11.84iter/s]
Best score: 0.3271: : 719iter [01:06, 12.01iter/s]
Best score: 0.3271: : 719iter [01:06, 12.01iter/s]
Best score: 0.3271: : 720iter [01:06, 12.01iter/s]
Best score: 0.3271: : 721iter [01:06, 11.96iter/s]
Best score: 0.3271: : 721iter [01:06, 11.96iter/s]
Best score: 0.3271: : 722iter [01:06, 11.96iter/s]
Best score: 0.3271: : 723iter [01:06, 12.12iter/s]
Best score: 0.3271: : 723iter [01:07, 12.12iter/s]
Best score: 0.3271: : 724iter [01:07, 12.12iter/s]
Best score: 0.3271: : 725iter [01:07, 12.22iter/s]
Best score: 0.3271: : 725iter [01:07, 12.22iter/s]
Best score: 0.3271: : 726iter [01:07, 12.22iter/s]
Best score: 0.3271: : 727iter [01:07, 12.27iter/s]
Best score: 0.3271: : 727iter [01:07, 12.27iter/s]
Best score: 0.3271: : 728iter [01:07, 12.27iter/s]
Best score: 0.3271: : 729iter [01:07, 12.31iter/s]
Best score: 0.3271: : 729iter [01:07, 12.31iter/s]
Best score: 0.3271: : 730iter [01:07, 12.31iter/s]
Best score: 0.3271: : 731iter [01:07, 12.11iter/s]
Best score: 0.3271: : 731iter [01:07, 12.11iter/s]
Best score: 0.3271: : 732iter [01:07, 12.11iter/s]
Best score: 0.3271: : 733iter [01:07, 12.22iter/s]
Best score: 0.3271: : 733iter [01:07, 12.22iter/s]
Best score: 0.3271: : 734iter [01:07, 12.22iter/s]
Best score: 0.3271: : 735iter [01:07, 12.29iter/s]
Best score: 0.3271: : 735iter [01:08, 12.29iter/s]
Best score: 0.3271: : 736iter [01:08, 12.29iter/s]
Best score: 0.3271: : 737iter [01:08, 12.31iter/s]
Best score: 0.3271: : 737iter [01:08, 12.31iter/s]
Best score: 0.3271: : 738iter [01:08, 12.31iter/s]
Best score: 0.3271: : 739iter [01:08, 12.33iter/s]
Best score: 0.3271: : 739iter [01:08, 12.33iter/s]
Best score: 0.3271: : 740iter [01:08, 12.33iter/s]
Best score: 0.3271: : 741iter [01:08, 12.14iter/s]
Best score: 0.3271: : 741iter [01:08, 12.14iter/s]
Best score: 0.3271: : 742iter [01:08, 12.14iter/s]
Best score: 0.3271: : 743iter [01:08, 12.23iter/s]
Best score: 0.3271: : 743iter [01:08, 12.23iter/s]
Best score: 0.3271: : 744iter [01:08, 12.23iter/s]
Best score: 0.3271: : 745iter [01:08, 12.24iter/s]
Best score: 0.3271: : 745iter [01:08, 12.24iter/s]
Best score: 0.3271: : 746iter [01:08, 12.24iter/s]
Best score: 0.3271: : 747iter [01:08, 12.27iter/s]
Best score: 0.3271: : 747iter [01:09, 12.27iter/s]
Best score: 0.3271: : 748iter [01:09, 12.27iter/s]
Best score: 0.3271: : 749iter [01:09, 12.28iter/s]
[ITER 750] Best: 0.3271
[PARAMS] Current best parameters:
  fx: 559.5151
  fy: 559.6381
  px: 849.8961
  py: 996.8665
  k1: 0.01696656
  k2: -0.08560681
  k3: 0.06006460
  k4: -0.01436018
  p1: 0.00426311
  p2: 0.01017818
  p3: 0.00796893
  p4: -0.00913345
  s1: -0.0249
  s2: 0.0090
  s3: -0.0208
  s4: 0.0155
  tilt_x: -0.0362
  tilt_y: 0.0267
  scale: 2.9720
  rotation: -0.3926

Best score: 0.3271: : 749iter [01:09, 12.28iter/s]
Best score: 0.3271: : 750iter [01:09, 12.28iter/s]
Best score: 0.3271: : 751iter [01:09,  7.84iter/s]
Best score: 0.3271: : 751iter [01:09,  7.84iter/s]
Best score: 0.3271: : 752iter [01:09,  7.84iter/s]
Best score: 0.3271: : 753iter [01:09,  8.77iter/s]
Best score: 0.3271: : 753iter [01:09,  8.77iter/s]
Best score: 0.3271: : 754iter [01:09,  8.77iter/s]
Best score: 0.3271: : 755iter [01:09,  9.60iter/s]
Best score: 0.3271: : 755iter [01:09,  9.60iter/s]
Best score: 0.3271: : 756iter [01:10,  9.60iter/s]
Best score: 0.3271: : 757iter [01:10, 10.31iter/s]
Best score: 0.3271: : 757iter [01:10, 10.31iter/s]
Best score: 0.3271: : 758iter [01:10, 10.31iter/s]
Best score: 0.3271: : 759iter [01:10, 10.84iter/s]
Best score: 0.3271: : 759iter [01:10, 10.84iter/s]
Best score: 0.3271: : 760iter [01:10, 10.84iter/s]
Best score: 0.3271: : 761iter [01:10, 11.13iter/s]
Best score: 0.3271: : 761iter [01:10, 11.13iter/s]
Best score: 0.3271: : 762iter [01:10, 11.13iter/s]
Best score: 0.3271: : 763iter [01:10, 11.47iter/s]
Best score: 0.3271: : 763iter [01:10, 11.47iter/s]
Best score: 0.3271: : 764iter [01:10, 11.47iter/s]
Best score: 0.3271: : 765iter [01:10, 11.70iter/s]
Best score: 0.3271: : 765iter [01:10, 11.70iter/s]
Best score: 0.3271: : 766iter [01:10, 11.70iter/s]
Best score: 0.3271: : 767iter [01:10, 11.84iter/s]
Best score: 0.3271: : 767iter [01:10, 11.84iter/s]
Best score: 0.3271: : 768iter [01:11, 11.84iter/s]
Best score: 0.3271: : 769iter [01:11, 12.03iter/s]
Best score: 0.3271: : 769iter [01:11, 12.03iter/s]
Best score: 0.3271: : 770iter [01:11, 12.03iter/s]
Best score: 0.3271: : 771iter [01:11, 11.95iter/s]
Best score: 0.3271: : 771iter [01:11, 11.95iter/s]
Best score: 0.3271: : 772iter [01:11, 11.95iter/s]
Best score: 0.3271: : 773iter [01:11, 12.05iter/s]
Best score: 0.3271: : 773iter [01:11, 12.05iter/s]
Best score: 0.3271: : 774iter [01:11, 12.05iter/s]
Best score: 0.3271: : 775iter [01:11, 12.11iter/s]
Best score: 0.3271: : 775iter [01:11, 12.11iter/s]
Best score: 0.3271: : 776iter [01:11, 12.11iter/s]
Best score: 0.3271: : 777iter [01:11, 12.18iter/s]
Best score: 0.3271: : 777iter [01:11, 12.18iter/s]
Best score: 0.3271: : 778iter [01:11, 12.18iter/s]
Best score: 0.3271: : 779iter [01:11, 12.21iter/s]
Best score: 0.3271: : 779iter [01:11, 12.21iter/s]
Best score: 0.3271: : 780iter [01:12, 12.21iter/s]
Best score: 0.3271: : 781iter [01:12, 12.04iter/s]
Best score: 0.3271: : 781iter [01:12, 12.04iter/s]
Best score: 0.3271: : 782iter [01:12, 12.04iter/s]
Best score: 0.3271: : 783iter [01:12, 12.09iter/s]
Best score: 0.3271: : 783iter [01:12, 12.09iter/s]
Best score: 0.3271: : 784iter [01:12, 12.09iter/s]
Best score: 0.3271: : 785iter [01:12, 12.12iter/s]
Best score: 0.3271: : 785iter [01:12, 12.12iter/s]
Best score: 0.3271: : 786iter [01:12, 12.12iter/s]
Best score: 0.3271: : 787iter [01:12, 12.18iter/s]
Best score: 0.3271: : 787iter [01:12, 12.18iter/s]
Best score: 0.3271: : 788iter [01:12, 12.18iter/s]
Best score: 0.3271: : 789iter [01:12, 12.21iter/s]
Best score: 0.3271: : 789iter [01:12, 12.21iter/s]
Best score: 0.3271: : 790iter [01:12, 12.21iter/s]
Best score: 0.3271: : 791iter [01:12, 12.04iter/s]
Best score: 0.3271: : 791iter [01:12, 12.04iter/s]
Best score: 0.3271: : 792iter [01:13, 12.04iter/s]
Best score: 0.3271: : 793iter [01:13, 12.18iter/s]
Best score: 0.3271: : 793iter [01:13, 12.18iter/s]
Best score: 0.3271: : 794iter [01:13, 12.18iter/s]
Best score: 0.3271: : 795iter [01:13, 12.24iter/s]
Best score: 0.3271: : 795iter [01:13, 12.24iter/s]
Best score: 0.3271: : 796iter [01:13, 12.24iter/s]
Best score: 0.3271: : 797iter [01:13, 12.27iter/s]
Best score: 0.3271: : 797iter [01:13, 12.27iter/s]
Best score: 0.3271: : 798iter [01:13, 12.27iter/s]
Best score: 0.3271: : 799iter [01:13, 12.31iter/s]
[ITER 800] Best: 0.3271
[PARAMS] Current best parameters:
  fx: 559.5151
  fy: 559.6381
  px: 849.8961
  py: 996.8665
  k1: 0.01696656
  k2: -0.08560681
  k3: 0.06006460
  k4: -0.01436018
  p1: 0.00426311
  p2: 0.01017818
  p3: 0.00796893
  p4: -0.00913345
  s1: -0.0249
  s2: 0.0090
  s3: -0.0208
  s4: 0.0155
  tilt_x: -0.0362
  tilt_y: 0.0267
  scale: 2.9720
  rotation: -0.3926

Best score: 0.3271: : 799iter [01:13, 12.31iter/s]
Best score: 0.3271: : 800iter [01:13, 12.31iter/s]
Best score: 0.3271: : 801iter [01:13,  7.91iter/s]
Best score: 0.3271: : 801iter [01:14,  7.91iter/s]
Best score: 0.3271: : 802iter [01:14,  7.91iter/s]
Best score: 0.3271: : 803iter [01:14,  8.89iter/s]
Best score: 0.3271: : 803iter [01:14,  8.89iter/s]
Best score: 0.3271: : 804iter [01:14,  8.89iter/s]
Best score: 0.3271: : 805iter [01:14,  9.71iter/s]
Best score: 0.3271: : 805iter [01:14,  9.71iter/s]
Best score: 0.3271: : 806iter [01:14,  9.71iter/s]
Best score: 0.3271: : 807iter [01:14, 10.40iter/s]
Best score: 0.3271: : 807iter [01:14, 10.40iter/s]
Best score: 0.3271: : 808iter [01:14, 10.40iter/s]
Best score: 0.3271: : 809iter [01:14, 10.89iter/s]
Best score: 0.3271: : 809iter [01:14, 10.89iter/s]
Best score: 0.3271: : 810iter [01:14, 10.89iter/s]
Best score: 0.3271: : 811iter [01:14, 11.14iter/s]
Best score: 0.3271: : 811iter [01:14, 11.14iter/s]
Best score: 0.3271: : 812iter [01:14, 11.14iter/s]
Best score: 0.3271: : 813iter [01:14, 11.52iter/s]
Best score: 0.3271: : 813iter [01:15, 11.52iter/s]
Best score: 0.3271: : 814iter [01:15, 11.52iter/s]
Best score: 0.3271: : 815iter [01:15, 11.78iter/s]
Best score: 0.3271: : 815iter [01:15, 11.78iter/s]
Best score: 0.3271: : 816iter [01:15, 11.78iter/s]
Best score: 0.3271: : 817iter [01:15, 11.90iter/s]
Best score: 0.3271: : 817iter [01:15, 11.90iter/s]
Best score: 0.3271: : 818iter [01:15, 11.90iter/s]
Best score: 0.3271: : 819iter [01:15, 12.01iter/s]
Best score: 0.3219: : 819iter [01:15, 12.01iter/s]
Best score: 0.3219: : 820iter [01:15, 12.01iter/s]
Best score: 0.3219: : 821iter [01:15, 11.92iter/s]
Best score: 0.3219: : 821iter [01:15, 11.92iter/s]
Best score: 0.3219: : 822iter [01:15, 11.92iter/s]
Best score: 0.3219: : 823iter [01:15, 12.04iter/s]
Best score: 0.3219: : 823iter [01:15, 12.04iter/s]
Best score: 0.3219: : 824iter [01:15, 12.04iter/s]
Best score: 0.3219: : 825iter [01:15, 12.11iter/s]
Best score: 0.3219: : 825iter [01:16, 12.11iter/s]
Best score: 0.3219: : 826iter [01:16, 12.11iter/s]
Best score: 0.3219: : 827iter [01:16, 12.17iter/s]
Best score: 0.3219: : 827iter [01:16, 12.17iter/s]
Best score: 0.3219: : 828iter [01:16, 12.17iter/s]
Best score: 0.3219: : 829iter [01:16, 12.21iter/s]
Best score: 0.3219: : 829iter [01:16, 12.21iter/s]
Best score: 0.3219: : 830iter [01:16, 12.21iter/s]
Best score: 0.3219: : 831iter [01:16, 12.08iter/s]
Best score: 0.3219: : 831iter [01:16, 12.08iter/s]
Best score: 0.3219: : 832iter [01:16, 12.08iter/s]
Best score: 0.3219: : 833iter [01:16, 12.18iter/s]
Best score: 0.3219: : 833iter [01:16, 12.18iter/s]
Best score: 0.3219: : 834iter [01:16, 12.18iter/s]
Best score: 0.3219: : 835iter [01:16, 12.21iter/s]
Best score: 0.3219: : 835iter [01:16, 12.21iter/s]
Best score: 0.3219: : 836iter [01:16, 12.21iter/s]
Best score: 0.3219: : 837iter [01:16, 12.22iter/s]
Best score: 0.3219: : 837iter [01:16, 12.22iter/s]
Best score: 0.3219: : 838iter [01:17, 12.22iter/s]
Best score: 0.3219: : 839iter [01:17, 12.29iter/s]
Best score: 0.3219: : 839iter [01:17, 12.29iter/s]
Best score: 0.3219: : 840iter [01:17, 12.29iter/s]
Best score: 0.3219: : 841iter [01:17, 12.15iter/s]
Best score: 0.3219: : 841iter [01:17, 12.15iter/s]
Best score: 0.3219: : 842iter [01:17, 12.15iter/s]
Best score: 0.3219: : 843iter [01:17, 12.24iter/s]
Best score: 0.3219: : 843iter [01:17, 12.24iter/s]
Best score: 0.3219: : 844iter [01:17, 12.24iter/s]
Best score: 0.3219: : 845iter [01:17, 12.33iter/s]
Best score: 0.3219: : 845iter [01:17, 12.33iter/s]
Best score: 0.3219: : 846iter [01:17, 12.33iter/s]
Best score: 0.3219: : 847iter [01:17, 12.33iter/s]
Best score: 0.3219: : 847iter [01:17, 12.33iter/s]
Best score: 0.3219: : 848iter [01:17, 12.33iter/s]
Best score: 0.3219: : 849iter [01:17, 12.33iter/s]
[ITER 850] Best: 0.3212
[PARAMS] Current best parameters:
  fx: 560.7475
  fy: 560.5464
  px: 850.4201
  py: 997.2144
  k1: 0.01784759
  k2: -0.08786020
  k3: 0.06026580
  k4: -0.01399755
  p1: 0.00129519
  p2: 0.00735277
  p3: 0.00801481
  p4: -0.01030774
  s1: -0.0227
  s2: 0.0106
  s3: -0.0156
  s4: 0.0138
  tilt_x: -0.0271
  tilt_y: 0.0185
  scale: 2.9687
  rotation: -0.3938

Best score: 0.3212: : 849iter [01:17, 12.33iter/s]
Best score: 0.3212: : 850iter [01:18, 12.33iter/s]
Best score: 0.3212: : 851iter [01:18,  7.79iter/s]
Best score: 0.3212: : 851iter [01:18,  7.79iter/s]
Best score: 0.3212: : 852iter [01:18,  7.79iter/s]
Best score: 0.3212: : 853iter [01:18,  8.75iter/s]
Best score: 0.3212: : 853iter [01:18,  8.75iter/s]
Best score: 0.3212: : 854iter [01:18,  8.75iter/s]
Best score: 0.3212: : 855iter [01:18,  9.58iter/s]
Best score: 0.3212: : 855iter [01:18,  9.58iter/s]
Best score: 0.3212: : 856iter [01:18,  9.58iter/s]
Best score: 0.3212: : 857iter [01:18, 10.28iter/s]
Best score: 0.3212: : 857iter [01:18, 10.28iter/s]
Best score: 0.3212: : 858iter [01:19, 10.28iter/s]
Best score: 0.3212: : 859iter [01:19, 10.81iter/s]
Best score: 0.3067: : 859iter [01:19, 10.81iter/s]
Best score: 0.3067: : 860iter [01:19, 10.81iter/s]
Best score: 0.3067: : 861iter [01:19, 11.04iter/s]
Best score: 0.3067: : 861iter [01:19, 11.04iter/s]
Best score: 0.3067: : 862iter [01:19, 11.04iter/s]
Best score: 0.3067: : 863iter [01:19, 11.33iter/s]
Best score: 0.3067: : 863iter [01:19, 11.33iter/s]
Best score: 0.3067: : 864iter [01:19, 11.33iter/s]
Best score: 0.3067: : 865iter [01:19, 10.51iter/s]
Best score: 0.3067: : 865iter [01:19, 10.51iter/s]
Best score: 0.3067: : 866iter [01:19, 10.51iter/s]
Best score: 0.3067: : 867iter [01:19,  9.94iter/s]
Best score: 0.3067: : 867iter [01:19,  9.94iter/s]
Best score: 0.3067: : 868iter [01:20,  9.94iter/s]
Best score: 0.3067: : 869iter [01:20,  9.66iter/s]
Best score: 0.2949: : 869iter [01:20,  9.66iter/s]
Best score: 0.2949: : 870iter [01:20,  9.35iter/s]
Best score: 0.2949: : 870iter [01:20,  9.35iter/s]
Best score: 0.2949: : 871iter [01:20,  9.33iter/s]
Best score: 0.2949: : 871iter [01:20,  9.33iter/s]
Best score: 0.2949: : 872iter [01:20,  9.29iter/s]
Best score: 0.2949: : 872iter [01:20,  9.29iter/s]
Best score: 0.2949: : 873iter [01:20,  9.27iter/s]
Best score: 0.2949: : 873iter [01:20,  9.27iter/s]
Best score: 0.2949: : 874iter [01:20,  9.21iter/s]
Best score: 0.2949: : 874iter [01:20,  9.21iter/s]
Best score: 0.2949: : 875iter [01:20,  9.19iter/s]
Best score: 0.2949: : 875iter [01:20,  9.19iter/s]
Best score: 0.2949: : 876iter [01:20,  9.26iter/s]
Best score: 0.2949: : 876iter [01:20,  9.26iter/s]
Best score: 0.2949: : 877iter [01:20,  9.12iter/s]
Best score: 0.2949: : 877iter [01:21,  9.12iter/s]
Best score: 0.2949: : 878iter [01:21,  9.09iter/s]
Best score: 0.2949: : 878iter [01:21,  9.09iter/s]
Best score: 0.2949: : 879iter [01:21,  9.12iter/s]
Best score: 0.2773: : 879iter [01:21,  9.12iter/s]
Best score: 0.2773: : 880iter [01:21,  8.77iter/s]
Best score: 0.2773: : 880iter [01:21,  8.77iter/s]
Best score: 0.2773: : 881iter [01:21,  8.94iter/s]
Best score: 0.2773: : 881iter [01:21,  8.94iter/s]
Best score: 0.2773: : 882iter [01:21,  9.04iter/s]
Best score: 0.2773: : 882iter [01:21,  9.04iter/s]
Best score: 0.2773: : 883iter [01:21,  9.07iter/s]
Best score: 0.2773: : 883iter [01:21,  9.07iter/s]
Best score: 0.2773: : 884iter [01:21,  9.23iter/s]
Best score: 0.2773: : 884iter [01:21,  9.23iter/s]
Best score: 0.2773: : 885iter [01:21,  9.29iter/s]
Best score: 0.2773: : 885iter [01:21,  9.29iter/s]
Best score: 0.2773: : 886iter [01:21,  9.26iter/s]
Best score: 0.2773: : 886iter [01:22,  9.26iter/s]
Best score: 0.2773: : 887iter [01:22,  9.23iter/s]
Best score: 0.2773: : 887iter [01:22,  9.23iter/s]
Best score: 0.2773: : 888iter [01:22,  9.30iter/s]
Best score: 0.2773: : 888iter [01:22,  9.30iter/s]
Best score: 0.2773: : 889iter [01:22,  9.27iter/s]
Best score: 0.2765: : 889iter [01:22,  9.27iter/s]
Best score: 0.2765: : 890iter [01:22,  8.93iter/s]
Best score: 0.2765: : 890iter [01:22,  8.93iter/s]
Best score: 0.2765: : 891iter [01:22,  9.03iter/s]
Best score: 0.2765: : 891iter [01:22,  9.03iter/s]
Best score: 0.2765: : 892iter [01:22,  9.09iter/s]
Best score: 0.2765: : 892iter [01:22,  9.09iter/s]
Best score: 0.2765: : 893iter [01:22,  9.13iter/s]
Best score: 0.2765: : 893iter [01:22,  9.13iter/s]
Best score: 0.2765: : 894iter [01:22,  8.95iter/s]
Best score: 0.2765: : 894iter [01:22,  8.95iter/s]
Best score: 0.2765: : 895iter [01:22,  8.89iter/s]
Best score: 0.2765: : 895iter [01:23,  8.89iter/s]
Best score: 0.2765: : 896iter [01:23,  9.02iter/s]
Best score: 0.2765: : 896iter [01:23,  9.02iter/s]
Best score: 0.2765: : 897iter [01:23,  8.98iter/s]
Best score: 0.2765: : 897iter [01:23,  8.98iter/s]
Best score: 0.2765: : 898iter [01:23,  8.96iter/s]
Best score: 0.2765: : 898iter [01:23,  8.96iter/s]
Best score: 0.2765: : 899iter [01:23,  8.99iter/s]
[ITER 900] Best: 0.2745
[PARAMS] Current best parameters:
  fx: 559.9563
  fy: 559.9267
  px: 851.8679
  py: 993.9529
  k1: 0.01493441
  k2: -0.09180605
  k3: 0.06962809
  k4: -0.01760253
  p1: -0.00900649
  p2: 0.00562068
  p3: 0.01425830
  p4: -0.01172743
  s1: -0.0252
  s2: 0.0118
  s3: -0.0112
  s4: 0.0122
  tilt_x: -0.0237
  tilt_y: 0.0088
  scale: 2.9768
  rotation: -0.3827

Best score: 0.2745: : 899iter [01:23,  8.99iter/s]
Best score: 0.2745: : 900iter [01:23,  8.78iter/s]
Best score: 0.2745: : 900iter [01:23,  8.78iter/s]
Best score: 0.2745: : 901iter [01:23,  5.00iter/s]
Best score: 0.2745: : 901iter [01:23,  5.00iter/s]
Best score: 0.2745: : 902iter [01:23,  5.83iter/s]
Best score: 0.2745: : 902iter [01:24,  5.83iter/s]
Best score: 0.2745: : 903iter [01:24,  6.55iter/s]
Best score: 0.2745: : 903iter [01:24,  6.55iter/s]
Best score: 0.2745: : 904iter [01:24,  7.19iter/s]
Best score: 0.2745: : 904iter [01:24,  7.19iter/s]
Best score: 0.2745: : 905iter [01:24,  7.62iter/s]
Best score: 0.2745: : 905iter [01:24,  7.62iter/s]
Best score: 0.2745: : 906iter [01:24,  8.04iter/s]
Best score: 0.2745: : 906iter [01:24,  8.04iter/s]
Best score: 0.2745: : 907iter [01:24,  8.36iter/s]
Best score: 0.2745: : 907iter [01:24,  8.36iter/s]
Best score: 0.2745: : 908iter [01:24,  8.64iter/s]
Best score: 0.2745: : 908iter [01:24,  8.64iter/s]
Best score: 0.2745: : 909iter [01:24,  8.77iter/s]
Best score: 0.2728: : 909iter [01:24,  8.77iter/s]
Best score: 0.2728: : 910iter [01:24,  8.61iter/s]
Best score: 0.2728: : 910iter [01:24,  8.61iter/s]
Best score: 0.2728: : 911iter [01:24,  8.86iter/s]
Best score: 0.2728: : 911iter [01:25,  8.86iter/s]
Best score: 0.2728: : 912iter [01:25,  9.02iter/s]
Best score: 0.2728: : 912iter [01:25,  9.02iter/s]
Best score: 0.2728: : 913iter [01:25,  9.06iter/s]
Best score: 0.2728: : 913iter [01:25,  9.06iter/s]
Best score: 0.2728: : 914iter [01:25,  9.08iter/s]
Best score: 0.2728: : 914iter [01:25,  9.08iter/s]
Best score: 0.2728: : 915iter [01:25,  9.22iter/s]
Best score: 0.2728: : 915iter [01:25,  9.22iter/s]
Best score: 0.2728: : 916iter [01:25,  9.10iter/s]
Best score: 0.2728: : 916iter [01:25,  9.10iter/s]
Best score: 0.2728: : 917iter [01:25,  9.12iter/s]
Best score: 0.2728: : 917iter [01:25,  9.12iter/s]
Best score: 0.2728: : 918iter [01:25,  9.10iter/s]
Best score: 0.2728: : 918iter [01:25,  9.10iter/s]
Best score: 0.2728: : 919iter [01:25,  9.03iter/s]
Best score: 0.2728: : 919iter [01:25,  9.03iter/s]
Best score: 0.2728: : 920iter [01:25,  8.81iter/s]
Best score: 0.2728: : 920iter [01:26,  8.81iter/s]
Best score: 0.2728: : 921iter [01:26,  8.84iter/s]
Best score: 0.2728: : 921iter [01:26,  8.84iter/s]
Best score: 0.2728: : 922iter [01:26,  8.83iter/s]
Best score: 0.2728: : 922iter [01:26,  8.83iter/s]
Best score: 0.2728: : 923iter [01:26,  8.85iter/s]
Best score: 0.2728: : 923iter [01:26,  8.85iter/s]
Best score: 0.2728: : 924iter [01:26,  8.99iter/s]
Best score: 0.2728: : 924iter [01:26,  8.99iter/s]
Best score: 0.2728: : 925iter [01:26,  8.97iter/s]
Best score: 0.2728: : 925iter [01:26,  8.97iter/s]
Best score: 0.2728: : 926iter [01:26,  9.00iter/s]
Best score: 0.2728: : 926iter [01:26,  9.00iter/s]
Best score: 0.2728: : 927iter [01:26,  9.00iter/s]
Best score: 0.2728: : 927iter [01:26,  9.00iter/s]
Best score: 0.2728: : 928iter [01:26,  9.05iter/s]
Best score: 0.2728: : 928iter [01:26,  9.05iter/s]
Best score: 0.2728: : 929iter [01:26,  9.03iter/s]
Best score: 0.2608: : 929iter [01:27,  9.03iter/s]
Best score: 0.2608: : 930iter [01:27,  8.87iter/s]
Best score: 0.2608: : 930iter [01:27,  8.87iter/s]
Best score: 0.2608: : 931iter [01:27,  8.95iter/s]
Best score: 0.2608: : 931iter [01:27,  8.95iter/s]
Best score: 0.2608: : 932iter [01:27,  9.04iter/s]
Best score: 0.2608: : 932iter [01:27,  9.04iter/s]
Best score: 0.2608: : 933iter [01:27,  9.05iter/s]
Best score: 0.2608: : 933iter [01:27,  9.05iter/s]
Best score: 0.2608: : 934iter [01:27,  9.07iter/s]
Best score: 0.2608: : 934iter [01:27,  9.07iter/s]
Best score: 0.2608: : 935iter [01:27,  9.12iter/s]
Best score: 0.2608: : 935iter [01:27,  9.12iter/s]
Best score: 0.2608: : 936iter [01:27,  9.21iter/s]
Best score: 0.2608: : 936iter [01:27,  9.21iter/s]
Best score: 0.2608: : 937iter [01:27,  9.16iter/s]
Best score: 0.2608: : 937iter [01:27,  9.16iter/s]
Best score: 0.2608: : 938iter [01:27,  9.02iter/s]
Best score: 0.2608: : 938iter [01:28,  9.02iter/s]
Best score: 0.2608: : 939iter [01:28,  8.98iter/s]
Best score: 0.2577: : 939iter [01:28,  8.98iter/s]
Best score: 0.2577: : 940iter [01:28,  8.87iter/s]
Best score: 0.2577: : 940iter [01:28,  8.87iter/s]
Best score: 0.2577: : 941iter [01:28,  8.97iter/s]
Best score: 0.2577: : 941iter [01:28,  8.97iter/s]
Best score: 0.2577: : 942iter [01:28,  8.96iter/s]
Best score: 0.2577: : 942iter [01:28,  8.96iter/s]
Best score: 0.2577: : 943iter [01:28,  8.94iter/s]
Best score: 0.2577: : 943iter [01:28,  8.94iter/s]
Best score: 0.2577: : 944iter [01:28,  8.80iter/s]
Best score: 0.2577: : 944iter [01:28,  8.80iter/s]
Best score: 0.2577: : 945iter [01:28,  8.94iter/s]
Best score: 0.2577: : 945iter [01:28,  8.94iter/s]
Best score: 0.2577: : 946iter [01:28,  9.03iter/s]
Best score: 0.2577: : 946iter [01:28,  9.03iter/s]
Best score: 0.2577: : 947iter [01:28,  9.04iter/s]
Best score: 0.2577: : 947iter [01:29,  9.04iter/s]
Best score: 0.2577: : 948iter [01:29,  9.07iter/s]
Best score: 0.2577: : 948iter [01:29,  9.07iter/s]
Best score: 0.2577: : 949iter [01:29,  8.98iter/s]
Best score: 0.2577: : 949iter [01:29,  8.98iter/s]
Best score: 0.2577: : 950iter [01:29,  8.73iter/s]
[ITER 950] Best: 0.2577
[PARAMS] Current best parameters:
  fx: 555.7817
  fy: 556.0163
  px: 853.8992
  py: 992.6628
  k1: 0.02150454
  k2: -0.09097594
  k3: 0.06566168
  k4: -0.01618217
  p1: -0.01315150
  p2: 0.00662798
  p3: 0.01690836
  p4: -0.00687672
  s1: -0.0268
  s2: 0.0077
  s3: -0.0136
  s4: 0.0093
  tilt_x: -0.0216
  tilt_y: 0.0007
  scale: 2.9719
  rotation: -0.4144

Best score: 0.2577: : 950iter [01:29,  8.73iter/s]
Best score: 0.2577: : 951iter [01:29,  4.92iter/s]
Best score: 0.2577: : 951iter [01:29,  4.92iter/s]
Best score: 0.2577: : 952iter [01:29,  5.68iter/s]
Best score: 0.2577: : 952iter [01:29,  5.68iter/s]
Best score: 0.2577: : 953iter [01:29,  6.39iter/s]
Best score: 0.2577: : 953iter [01:30,  6.39iter/s]
Best score: 0.2577: : 954iter [01:30,  6.98iter/s]
Best score: 0.2577: : 954iter [01:30,  6.98iter/s]
Best score: 0.2577: : 955iter [01:30,  7.48iter/s]
Best score: 0.2577: : 955iter [01:30,  7.48iter/s]
Best score: 0.2577: : 956iter [01:30,  7.90iter/s]
Best score: 0.2577: : 956iter [01:30,  7.90iter/s]
Best score: 0.2577: : 957iter [01:30,  8.27iter/s]
Best score: 0.2577: : 957iter [01:30,  8.27iter/s]
Best score: 0.2577: : 958iter [01:30,  8.55iter/s]
Best score: 0.2577: : 958iter [01:30,  8.55iter/s]
Best score: 0.2577: : 959iter [01:30,  8.69iter/s]
Best score: 0.2577: : 959iter [01:30,  8.69iter/s]
Best score: 0.2577: : 960iter [01:30,  8.57iter/s]
Best score: 0.2577: : 960iter [01:30,  8.57iter/s]
Best score: 0.2577: : 961iter [01:30,  8.67iter/s]
Best score: 0.2577: : 961iter [01:30,  8.67iter/s]
Best score: 0.2577: : 962iter [01:30,  8.79iter/s]
Best score: 0.2577: : 962iter [01:31,  8.79iter/s]
Best score: 0.2577: : 963iter [01:31,  8.84iter/s]
Best score: 0.2577: : 963iter [01:31,  8.84iter/s]
Best score: 0.2577: : 964iter [01:31,  8.98iter/s]
Best score: 0.2577: : 964iter [01:31,  8.98iter/s]
Best score: 0.2577: : 965iter [01:31,  9.00iter/s]
Best score: 0.2577: : 965iter [01:31,  9.00iter/s]
Best score: 0.2577: : 966iter [01:31,  9.02iter/s]
Best score: 0.2577: : 966iter [01:31,  9.02iter/s]
Best score: 0.2577: : 967iter [01:31,  9.00iter/s]
Best score: 0.2577: : 967iter [01:31,  9.00iter/s]
Best score: 0.2577: : 968iter [01:31,  9.05iter/s]
Best score: 0.2577: : 968iter [01:31,  9.05iter/s]
Best score: 0.2577: : 969iter [01:31,  9.11iter/s]
Best score: 0.2577: : 969iter [01:31,  9.11iter/s]
Best score: 0.2577: : 970iter [01:31,  8.83iter/s]
Best score: 0.2577: : 970iter [01:31,  8.83iter/s]
Best score: 0.2577: : 971iter [01:31,  8.89iter/s]
Best score: 0.2577: : 971iter [01:32,  8.89iter/s]
Best score: 0.2577: : 972iter [01:32,  8.89iter/s]
Best score: 0.2577: : 972iter [01:32,  8.89iter/s]
Best score: 0.2577: : 973iter [01:32,  9.01iter/s]
Best score: 0.2577: : 973iter [01:32,  9.01iter/s]
Best score: 0.2577: : 974iter [01:32,  9.11iter/s]
Best score: 0.2577: : 974iter [01:32,  9.11iter/s]
Best score: 0.2577: : 975iter [01:32,  9.06iter/s]
Best score: 0.2577: : 975iter [01:32,  9.06iter/s]
Best score: 0.2577: : 976iter [01:32,  9.09iter/s]
Best score: 0.2577: : 976iter [01:32,  9.09iter/s]
Best score: 0.2577: : 977iter [01:32,  9.09iter/s]
Best score: 0.2577: : 977iter [01:32,  9.09iter/s]
Best score: 0.2577: : 978iter [01:32,  9.11iter/s]
Best score: 0.2577: : 978iter [01:32,  9.11iter/s]
Best score: 0.2577: : 979iter [01:32,  9.08iter/s]
Best score: 0.2569: : 979iter [01:32,  9.08iter/s]
Best score: 0.2569: : 980iter [01:32,  8.85iter/s]
Best score: 0.2569: : 980iter [01:33,  8.85iter/s]
Best score: 0.2569: : 981iter [01:33,  8.96iter/s]
Best score: 0.2569: : 981iter [01:33,  8.96iter/s]
Best score: 0.2569: : 982iter [01:33,  9.11iter/s]
Best score: 0.2569: : 982iter [01:33,  9.11iter/s]
Best score: 0.2569: : 983iter [01:33,  9.12iter/s]
Best score: 0.2569: : 983iter [01:33,  9.12iter/s]
Best score: 0.2569: : 984iter [01:33,  9.02iter/s]
Best score: 0.2569: : 984iter [01:33,  9.02iter/s]
Best score: 0.2569: : 985iter [01:33,  9.10iter/s]
Best score: 0.2569: : 985iter [01:33,  9.10iter/s]
Best score: 0.2569: : 986iter [01:33,  9.12iter/s]
Best score: 0.2569: : 986iter [01:33,  9.12iter/s]
Best score: 0.2569: : 987iter [01:33,  9.20iter/s]
Best score: 0.2569: : 987iter [01:33,  9.20iter/s]
Best score: 0.2569: : 988iter [01:33,  9.16iter/s]
Best score: 0.2569: : 988iter [01:33,  9.16iter/s]
Best score: 0.2569: : 989iter [01:33,  9.18iter/s]
Best score: 0.2543: : 989iter [01:34,  9.18iter/s]
Best score: 0.2543: : 990iter [01:34,  8.90iter/s]
Best score: 0.2543: : 990iter [01:34,  8.90iter/s]
Best score: 0.2543: : 991iter [01:34,  9.03iter/s]
Best score: 0.2543: : 991iter [01:34,  9.03iter/s]
Best score: 0.2543: : 992iter [01:34,  9.15iter/s]
Best score: 0.2543: : 992iter [01:34,  9.15iter/s]
Best score: 0.2543: : 993iter [01:34,  9.07iter/s]
Best score: 0.2543: : 993iter [01:34,  9.07iter/s]
Best score: 0.2543: : 994iter [01:34,  9.11iter/s]
Best score: 0.2543: : 994iter [01:34,  9.11iter/s]
Best score: 0.2543: : 995iter [01:34,  9.13iter/s]
Best score: 0.2543: : 995iter [01:34,  9.13iter/s]
Best score: 0.2543: : 996iter [01:34,  9.15iter/s]
Best score: 0.2543: : 996iter [01:34,  9.15iter/s]
Best score: 0.2543: : 997iter [01:34,  9.16iter/s]
Best score: 0.2543: : 997iter [01:34,  9.16iter/s]
Best score: 0.2543: : 998iter [01:34,  9.28iter/s]
Best score: 0.2543: : 998iter [01:34,  9.28iter/s]
Best score: 0.2543: : 999iter [01:34,  9.30iter/s]
[ITER 1000] Best: 0.2514
[PARAMS] Current best parameters:
  fx: 554.9921
  fy: 554.9295
  px: 854.5089
  py: 992.6194
  k1: 0.02154204
  k2: -0.09032094
  k3: 0.06603549
  k4: -0.01650099
  p1: -0.01807093
  p2: 0.00579825
  p3: 0.01715913
  p4: -0.00680680
  s1: -0.0260
  s2: 0.0079
  s3: -0.0081
  s4: 0.0090
  tilt_x: -0.0124
  tilt_y: -0.0043
  scale: 2.9716
  rotation: -0.4241

Best score: 0.2514: : 999iter [01:35,  9.30iter/s]
Best score: 0.2514: : 1000iter [01:35,  9.11iter/s]
Best score: 0.2514: : 1000iter [01:35,  9.11iter/s]
Best score: 0.2514: : 1001iter [01:35,  5.10iter/s]
Best score: 0.2514: : 1001iter [01:35,  5.10iter/s]
Best score: 0.2514: : 1002iter [01:35,  5.74iter/s]
Best score: 0.2514: : 1002iter [01:35,  5.74iter/s]
Best score: 0.2514: : 1003iter [01:35,  6.44iter/s]
Best score: 0.2514: : 1003iter [01:35,  6.44iter/s]
Best score: 0.2514: : 1004iter [01:35,  7.03iter/s]
Best score: 0.2514: : 1004iter [01:35,  7.03iter/s]
Best score: 0.2514: : 1005iter [01:35,  7.55iter/s]
Best score: 0.2514: : 1005iter [01:36,  7.55iter/s]
Best score: 0.2514: : 1006iter [01:36,  7.96iter/s]
Best score: 0.2514: : 1006iter [01:36,  7.96iter/s]
Best score: 0.2514: : 1007iter [01:36,  8.28iter/s]
Best score: 0.2514: : 1007iter [01:36,  8.28iter/s]
Best score: 0.2514: : 1008iter [01:36,  8.55iter/s]
Best score: 0.2514: : 1008iter [01:36,  8.55iter/s]
Best score: 0.2514: : 1009iter [01:36,  8.73iter/s]
Best score: 0.2514: : 1009iter [01:36,  8.73iter/s]
Best score: 0.2514: : 1010iter [01:36,  8.59iter/s]
Best score: 0.2514: : 1010iter [01:36,  8.59iter/s]
Best score: 0.2514: : 1011iter [01:36,  8.77iter/s]
Best score: 0.2514: : 1011iter [01:36,  8.77iter/s]
Best score: 0.2514: : 1012iter [01:36,  8.81iter/s]
Best score: 0.2514: : 1012iter [01:36,  8.81iter/s]
Best score: 0.2514: : 1013iter [01:36,  8.88iter/s]
Best score: 0.2514: : 1013iter [01:36,  8.88iter/s]
Best score: 0.2514: : 1014iter [01:36,  8.96iter/s]
Best score: 0.2514: : 1014iter [01:37,  8.96iter/s]
Best score: 0.2514: : 1015iter [01:37,  8.98iter/s]
Best score: 0.2514: : 1015iter [01:37,  8.98iter/s]
Best score: 0.2514: : 1016iter [01:37,  9.01iter/s]
Best score: 0.2514: : 1016iter [01:37,  9.01iter/s]
Best score: 0.2514: : 1017iter [01:37,  9.06iter/s]
Best score: 0.2514: : 1017iter [01:37,  9.06iter/s]
Best score: 0.2514: : 1018iter [01:37,  9.02iter/s]
Best score: 0.2514: : 1018iter [01:37,  9.02iter/s]
Best score: 0.2514: : 1019iter [01:37,  9.10iter/s]
Best score: 0.2514: : 1019iter [01:37,  9.10iter/s]
Best score: 0.2514: : 1020iter [01:37,  8.86iter/s]
Best score: 0.2514: : 1020iter [01:37,  8.86iter/s]
Best score: 0.2514: : 1021iter [01:37,  8.98iter/s]
Best score: 0.2514: : 1021iter [01:37,  8.98iter/s]
Best score: 0.2514: : 1022iter [01:37,  8.96iter/s]
Best score: 0.2514: : 1022iter [01:37,  8.96iter/s]
Best score: 0.2514: : 1023iter [01:37,  8.96iter/s]
Best score: 0.2514: : 1023iter [01:38,  8.96iter/s]
Best score: 0.2514: : 1024iter [01:38,  8.99iter/s]
Best score: 0.2514: : 1024iter [01:38,  8.99iter/s]
Best score: 0.2514: : 1025iter [01:38,  9.01iter/s]
Best score: 0.2514: : 1025iter [01:38,  9.01iter/s]
Best score: 0.2514: : 1026iter [01:38,  8.98iter/s]
Best score: 0.2514: : 1026iter [01:38,  8.98iter/s]
Best score: 0.2514: : 1027iter [01:38,  8.98iter/s]
Best score: 0.2514: : 1027iter [01:38,  8.98iter/s]
Best score: 0.2514: : 1028iter [01:38,  8.99iter/s]
Best score: 0.2514: : 1028iter [01:38,  8.99iter/s]
Best score: 0.2514: : 1029iter [01:38,  9.11iter/s]
Best score: 0.2510: : 1029iter [01:38,  9.11iter/s]
Best score: 0.2510: : 1030iter [01:38,  8.84iter/s]
Best score: 0.2510: : 1030iter [01:38,  8.84iter/s]
Best score: 0.2510: : 1031iter [01:38,  8.85iter/s]
Best score: 0.2510: : 1031iter [01:38,  8.85iter/s]
Best score: 0.2510: : 1032iter [01:38,  8.94iter/s]
Best score: 0.2510: : 1032iter [01:39,  8.94iter/s]
Best score: 0.2510: : 1033iter [01:39,  9.00iter/s]
Best score: 0.2510: : 1033iter [01:39,  9.00iter/s]
Best score: 0.2510: : 1034iter [01:39,  9.05iter/s]
Best score: 0.2510: : 1034iter [01:39,  9.05iter/s]
Best score: 0.2510: : 1035iter [01:39,  9.07iter/s]
Best score: 0.2510: : 1035iter [01:39,  9.07iter/s]
Best score: 0.2510: : 1036iter [01:39,  9.12iter/s]
Best score: 0.2510: : 1036iter [01:39,  9.12iter/s]
Best score: 0.2510: : 1037iter [01:39,  9.17iter/s]
Best score: 0.2510: : 1037iter [01:39,  9.17iter/s]
Best score: 0.2510: : 1038iter [01:39,  9.08iter/s]
Best score: 0.2510: : 1038iter [01:39,  9.08iter/s]
Best score: 0.2510: : 1039iter [01:39,  9.00iter/s]
Best score: 0.2502: : 1039iter [01:39,  9.00iter/s]
Best score: 0.2502: : 1040iter [01:39,  8.80iter/s]
Best score: 0.2502: : 1040iter [01:39,  8.80iter/s]
Best score: 0.2502: : 1041iter [01:39,  8.93iter/s]
Best score: 0.2502: : 1041iter [01:40,  8.93iter/s]
Best score: 0.2502: : 1042iter [01:40,  8.96iter/s]
Best score: 0.2502: : 1042iter [01:40,  8.96iter/s]
Best score: 0.2502: : 1043iter [01:40,  8.85iter/s]
Best score: 0.2502: : 1043iter [01:40,  8.85iter/s]
Best score: 0.2502: : 1044iter [01:40,  9.03iter/s]
Best score: 0.2502: : 1044iter [01:40,  9.03iter/s]
Best score: 0.2502: : 1045iter [01:40,  8.95iter/s]
Best score: 0.2502: : 1045iter [01:40,  8.95iter/s]
Best score: 0.2502: : 1046iter [01:40,  9.07iter/s]
Best score: 0.2502: : 1046iter [01:40,  9.07iter/s]
Best score: 0.2502: : 1047iter [01:40,  9.12iter/s]
Best score: 0.2502: : 1047iter [01:40,  9.12iter/s]
Best score: 0.2502: : 1048iter [01:40,  9.14iter/s]
Best score: 0.2502: : 1048iter [01:40,  9.14iter/s]
Best score: 0.2502: : 1049iter [01:40,  9.16iter/s]
Best score: 0.2496: : 1049iter [01:40,  9.16iter/s]
Best score: 0.2496: : 1050iter [01:40,  8.86iter/s]
[ITER 1050] Best: 0.2496
[PARAMS] Current best parameters:
  fx: 554.7333
  fy: 554.7615
  px: 854.3753
  py: 992.7512
  k1: 0.02224935
  k2: -0.09057453
  k3: 0.06547427
  k4: -0.01617544
  p1: -0.01536256
  p2: 0.00631487
  p3: 0.01761521
  p4: -0.00881472
  s1: -0.0273
  s2: 0.0101
  s3: -0.0111
  s4: 0.0115
  tilt_x: -0.0173
  tilt_y: -0.0028
  scale: 2.9725
  rotation: -0.4202

Best score: 0.2496: : 1050iter [01:41,  8.86iter/s]
Best score: 0.2496: : 1051iter [01:41,  4.92iter/s]
Best score: 0.2496: : 1051iter [01:41,  4.92iter/s]
Best score: 0.2496: : 1052iter [01:41,  5.70iter/s]
Best score: 0.2496: : 1052iter [01:41,  5.70iter/s]
Best score: 0.2496: : 1053iter [01:41,  6.39iter/s]
Best score: 0.2496: : 1053iter [01:41,  6.39iter/s]
Best score: 0.2496: : 1054iter [01:41,  6.97iter/s]
Best score: 0.2496: : 1054iter [01:41,  6.97iter/s]
Best score: 0.2496: : 1055iter [01:41,  7.47iter/s]
Best score: 0.2496: : 1055iter [01:41,  7.47iter/s]
Best score: 0.2496: : 1056iter [01:41,  7.91iter/s]
Best score: 0.2496: : 1056iter [01:42,  7.91iter/s]
Best score: 0.2496: : 1057iter [01:42,  8.22iter/s]
Best score: 0.2496: : 1057iter [01:42,  8.22iter/s]
Best score: 0.2496: : 1058iter [01:42,  8.53iter/s]
Best score: 0.2496: : 1058iter [01:42,  8.53iter/s]
Best score: 0.2496: : 1059iter [01:42,  8.72iter/s]
Best score: 0.2496: : 1059iter [01:42,  8.72iter/s]
Best score: 0.2496: : 1060iter [01:42,  8.58iter/s]
Best score: 0.2496: : 1060iter [01:42,  8.58iter/s]
Best score: 0.2496: : 1061iter [01:42,  8.79iter/s]
Best score: 0.2496: : 1061iter [01:42,  8.79iter/s]
Best score: 0.2496: : 1062iter [01:42,  8.83iter/s]
Best score: 0.2496: : 1062iter [01:42,  8.83iter/s]
Best score: 0.2496: : 1063iter [01:42,  8.88iter/s]
Best score: 0.2496: : 1063iter [01:42,  8.88iter/s]
Best score: 0.2496: : 1064iter [01:42,  8.97iter/s]
Best score: 0.2496: : 1064iter [01:42,  8.97iter/s]
Best score: 0.2496: : 1065iter [01:42,  9.00iter/s]
Best score: 0.2496: : 1065iter [01:43,  9.00iter/s]
Best score: 0.2496: : 1066iter [01:43,  8.99iter/s]
Best score: 0.2496: : 1066iter [01:43,  8.99iter/s]
Best score: 0.2496: : 1067iter [01:43,  9.09iter/s]
Best score: 0.2496: : 1067iter [01:43,  9.09iter/s]
Best score: 0.2496: : 1068iter [01:43,  9.05iter/s]
Best score: 0.2496: : 1068iter [01:43,  9.05iter/s]
Best score: 0.2496: : 1069iter [01:43,  9.08iter/s]
Best score: 0.2489: : 1069iter [01:43,  9.08iter/s]
Best score: 0.2489: : 1070iter [01:43,  8.91iter/s]
Best score: 0.2489: : 1070iter [01:43,  8.91iter/s]
Best score: 0.2489: : 1071iter [01:43,  8.92iter/s]
Best score: 0.2489: : 1071iter [01:43,  8.92iter/s]
Best score: 0.2489: : 1072iter [01:43,  9.02iter/s]
Best score: 0.2489: : 1072iter [01:43,  9.02iter/s]
Best score: 0.2489: : 1073iter [01:43,  9.11iter/s]
Best score: 0.2489: : 1073iter [01:43,  9.11iter/s]
Best score: 0.2489: : 1074iter [01:43,  9.05iter/s]
Best score: 0.2489: : 1074iter [01:44,  9.05iter/s]
Best score: 0.2489: : 1075iter [01:44,  9.17iter/s]
Best score: 0.2489: : 1075iter [01:44,  9.17iter/s]
Best score: 0.2489: : 1076iter [01:44,  9.06iter/s]
Best score: 0.2489: : 1076iter [01:44,  9.06iter/s]
Best score: 0.2489: : 1077iter [01:44,  9.15iter/s]
Best score: 0.2489: : 1077iter [01:44,  9.15iter/s]
Best score: 0.2489: : 1078iter [01:44,  9.26iter/s]
Best score: 0.2489: : 1078iter [01:44,  9.26iter/s]
Best score: 0.2489: : 1079iter [01:44,  9.23iter/s]
Best score: 0.2482: : 1079iter [01:44,  9.23iter/s]
Best score: 0.2482: : 1080iter [01:44,  9.01iter/s]
Best score: 0.2482: : 1080iter [01:44,  9.01iter/s]
Best score: 0.2482: : 1081iter [01:44,  9.04iter/s]
Best score: 0.2482: : 1081iter [01:44,  9.04iter/s]
Best score: 0.2482: : 1082iter [01:44,  9.04iter/s]
Best score: 0.2482: : 1082iter [01:44,  9.04iter/s]
Best score: 0.2482: : 1083iter [01:44,  8.96iter/s]
Best score: 0.2482: : 1083iter [01:45,  8.96iter/s]
Best score: 0.2482: : 1084iter [01:45,  9.03iter/s]
Best score: 0.2482: : 1084iter [01:45,  9.03iter/s]
Best score: 0.2482: : 1085iter [01:45,  8.98iter/s]
Best score: 0.2482: : 1085iter [01:45,  8.98iter/s]
Best score: 0.2482: : 1086iter [01:45,  8.96iter/s]
Best score: 0.2482: : 1086iter [01:45,  8.96iter/s]
Best score: 0.2482: : 1087iter [01:45,  8.94iter/s]
Best score: 0.2482: : 1087iter [01:45,  8.94iter/s]
Best score: 0.2482: : 1088iter [01:45,  8.97iter/s]
Best score: 0.2482: : 1088iter [01:45,  8.97iter/s]
Best score: 0.2482: : 1089iter [01:45,  8.98iter/s]
Best score: 0.2478: : 1089iter [01:45,  8.98iter/s]
Best score: 0.2478: : 1090iter [01:45,  8.67iter/s]
Best score: 0.2478: : 1090iter [01:45,  8.67iter/s]
Best score: 0.2478: : 1091iter [01:45,  8.73iter/s]
Best score: 0.2478: : 1091iter [01:45,  8.73iter/s]
Best score: 0.2478: : 1092iter [01:45,  8.80iter/s]
Best score: 0.2478: : 1092iter [01:46,  8.80iter/s]
Best score: 0.2478: : 1093iter [01:46,  8.86iter/s]
Best score: 0.2478: : 1093iter [01:46,  8.86iter/s]
Best score: 0.2478: : 1094iter [01:46,  8.94iter/s]
Best score: 0.2478: : 1094iter [01:46,  8.94iter/s]
Best score: 0.2478: : 1095iter [01:46,  8.91iter/s]
Best score: 0.2478: : 1095iter [01:46,  8.91iter/s]
Best score: 0.2478: : 1096iter [01:46,  8.95iter/s]
Best score: 0.2478: : 1096iter [01:46,  8.95iter/s]
Best score: 0.2478: : 1097iter [01:46,  8.92iter/s]
Best score: 0.2478: : 1097iter [01:46,  8.92iter/s]
Best score: 0.2478: : 1098iter [01:46,  8.95iter/s]
Best score: 0.2478: : 1098iter [01:46,  8.95iter/s]
Best score: 0.2478: : 1099iter [01:46,  9.06iter/s]
[ITER 1100] Best: 0.2477
[PARAMS] Current best parameters:
  fx: 554.2792
  fy: 554.2723
  px: 855.1306
  py: 992.4696
  k1: 0.02243945
  k2: -0.08979682
  k3: 0.06484047
  k4: -0.01601958
  p1: -0.01602628
  p2: 0.00726351
  p3: 0.01698885
  p4: -0.00731729
  s1: -0.0264
  s2: 0.0081
  s3: -0.0091
  s4: 0.0089
  tilt_x: -0.0172
  tilt_y: -0.0044
  scale: 2.9719
  rotation: -0.4278

Best score: 0.2477: : 1099iter [01:46,  9.06iter/s]
Best score: 0.2477: : 1100iter [01:46,  8.81iter/s]
Best score: 0.2477: : 1100iter [01:47, 10.27iter/s]

[📈] Running L-BFGS-B polish after 1100 DE iterations...
  Polish improved score: 0.247667 -> 0.245831

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 95,633 → 90,821 within 3500mm ring
  Ring polish did not improve score: 0.245831
  Success: True
  Tangential distortion: p1=-0.016055, p2=0.006776, p3=0.016438, p4=-0.007777
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.2458
[✅] Parameters copied to: /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 554.2792071290653
    fy: 554.2722583255504
    px: 855.130571921693
    py: 992.4696176404995
    k1: 0.022682266837942427
    k2: -0.08882970320757973
    k3: 0.06326281677591207
    k4: -0.015463823753437609
    p1: -0.01605479232573092
    p2: 0.006776311689110968
    p3: 0.016437577434872428
    p4: -0.007777478318570331
    scale: 2.9710183498099783
    rotation: -0.42751693132508584
    mmpp: 3.4480081736981374
    nmpp: 3448008.1736981375

[🔄] Converting 1930 frames to PTD, creating debug images for 400 calibration frames...

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   🔄 2000L:  99%|█████████▊| 581/589 [00:03<00:00, 178.02frame/s]/app/slick/utils/distortion_utils.py:114: RuntimeWarning: overflow encountered in square
  r4 = r2**2
/app/slick/utils/distortion_utils.py:172: RuntimeWarning: invalid value encountered in add
  w_p = M[2, 0] * xn + M[2, 1] * yn + M[2, 2]


                                                                  
📁 Rigs:  75%|███████▌  | 3/4 [00:17<00:05,  5.79s/rig]

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📁 Rigs: 100%|██████████| 4/4 [00:20<00:00,  4.63s/rig]
📁 Rigs: 100%|██████████| 4/4 [00:20<00:00,  5.06s/rig]
[✅] Saved PTDs: /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/debug/4_undistorted/output/ptd

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📁 Rigs:  75%|███████▌  | 3/4 [00:03<00:01,  1.00s/rig]

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📁 Rigs: 100%|██████████| 4/4 [00:04<00:00,  1.03s/rig]
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[✅] Saved PTDs: /working/MDCP3D-SL-010_W046(6)_2026-04-09/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.

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📤 Writing LUT: 100%|█████████▉| 3229734/3240000 [00:04<00:00, 665011.68px/s]
📤 Writing LUT: 100%|██████████| 3240000/3240000 [00:04<00:00, 656173.13px/s]
[✅] LUT written to: /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'MDCP3D-SL-010_W046(6)_2026-04-09' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/MDCP3D-SL-010_W046(6)_2026-04-09_unknown.lut

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

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

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

   🔥 2000R:   0%|          | 0/569 [00:00<?, ?frame/s]

   🔥 2000R:   2%|▏         | 9/569 [00:00<00:06, 83.82frame/s]

   🔥 2000R:   3%|▎         | 18/569 [00:00<00:07, 78.02frame/s]

   🔥 2000R:   5%|▍         | 26/569 [00:00<00:07, 77.27frame/s]

   🔥 2000R:   6%|▌         | 34/569 [00:00<00:06, 76.81frame/s]

   🔥 2000R:   7%|▋         | 42/569 [00:00<00:06, 76.84frame/s]

   🔥 2000R:   9%|▉         | 51/569 [00:00<00:06, 78.24frame/s]

   🔥 2000R:  11%|█         | 60/569 [00:00<00:06, 79.60frame/s]

   🔥 2000R:  12%|█▏        | 69/569 [00:00<00:06, 82.47frame/s]

   🔥 2000R:  14%|█▍        | 79/569 [00:00<00:05, 85.65frame/s]

   🔥 2000R:  15%|█▌        | 88/569 [00:01<00:05, 86.42frame/s]

   🔥 2000R:  17%|█▋        | 98/569 [00:01<00:05, 87.98frame/s]

   🔥 2000R:  19%|█▉        | 107/569 [00:01<00:05, 88.20frame/s]

   🔥 2000R:  21%|██        | 117/569 [00:01<00:05, 89.13frame/s]

   🔥 2000R:  22%|██▏       | 127/569 [00:01<00:04, 90.23frame/s]

   🔥 2000R:  24%|██▍       | 137/569 [00:01<00:04, 90.63frame/s]

   🔥 2000R:  26%|██▌       | 147/569 [00:01<00:04, 90.68frame/s]

   🔥 2000R:  28%|██▊       | 157/569 [00:01<00:04, 89.45frame/s]

   🔥 2000R:  29%|██▉       | 166/569 [00:01<00:04, 88.11frame/s]

   🔥 2000R:  31%|███       | 175/569 [00:02<00:04, 87.99frame/s]

   🔥 2000R:  32%|███▏      | 184/569 [00:02<00:04, 87.95frame/s]

   🔥 2000R:  34%|███▍      | 193/569 [00:02<00:04, 87.70frame/s]

   🔥 2000R:  36%|███▌      | 202/569 [00:02<00:04, 87.57frame/s]

   🔥 2000R:  37%|███▋      | 211/569 [00:02<00:04, 86.96frame/s]

   🔥 2000R:  39%|███▊      | 220/569 [00:02<00:03, 87.67frame/s]

   🔥 2000R:  40%|████      | 229/569 [00:02<00:03, 86.56frame/s]

   🔥 2000R:  42%|████▏     | 238/569 [00:02<00:03, 84.28frame/s]

   🔥 2000R:  43%|████▎     | 247/569 [00:02<00:03, 83.32frame/s]

   🔥 2000R:  45%|████▍     | 256/569 [00:03<00:03, 83.12frame/s]

   🔥 2000R:  47%|████▋     | 265/569 [00:03<00:03, 82.86frame/s]

   🔥 2000R:  48%|████▊     | 274/569 [00:03<00:03, 84.52frame/s]

   🔥 2000R:  50%|████▉     | 283/569 [00:03<00:03, 85.88frame/s]

   🔥 2000R:  51%|█████▏    | 292/569 [00:03<00:03, 85.72frame/s]

   🔥 2000R:  53%|█████▎    | 301/569 [00:03<00:03, 84.44frame/s]

   🔥 2000R:  54%|█████▍    | 310/569 [00:03<00:03, 85.42frame/s]

   🔥 2000R:  56%|█████▌    | 319/569 [00:03<00:02, 86.05frame/s]

   🔥 2000R:  58%|█████▊    | 329/569 [00:03<00:02, 88.52frame/s]

   🔥 2000R:  60%|█████▉    | 339/569 [00:03<00:02, 89.76frame/s]

   🔥 2000R:  61%|██████▏   | 349/569 [00:04<00:02, 90.80frame/s]

   🔥 2000R:  63%|██████▎   | 359/569 [00:04<00:02, 90.06frame/s]

   🔥 2000R:  65%|██████▍   | 369/569 [00:04<00:02, 90.37frame/s]

   🔥 2000R:  67%|██████▋   | 379/569 [00:04<00:02, 90.69frame/s]

   🔥 2000R:  68%|██████▊   | 389/569 [00:04<00:01, 90.21frame/s]

   🔥 2000R:  70%|███████   | 399/569 [00:04<00:01, 90.22frame/s]

   🔥 2000R:  72%|███████▏  | 409/569 [00:04<00:01, 90.49frame/s]

   🔥 2000R:  74%|███████▎  | 419/569 [00:04<00:01, 91.95frame/s]

   🔥 2000R:  75%|███████▌  | 429/569 [00:04<00:01, 93.30frame/s]

   🔥 2000R:  77%|███████▋  | 439/569 [00:05<00:01, 93.14frame/s]

   🔥 2000R:  79%|███████▉  | 449/569 [00:05<00:01, 93.33frame/s]

   🔥 2000R:  81%|████████  | 459/569 [00:05<00:01, 93.30frame/s]

   🔥 2000R:  82%|████████▏ | 469/569 [00:05<00:01, 90.87frame/s]

   🔥 2000R:  84%|████████▍ | 479/569 [00:05<00:01, 88.82frame/s]

   🔥 2000R:  86%|████████▌ | 488/569 [00:05<00:00, 88.71frame/s]

   🔥 2000R:  88%|████████▊ | 498/569 [00:05<00:00, 90.36frame/s]

   🔥 2000R:  89%|████████▉ | 508/569 [00:05<00:00, 90.92frame/s]

   🔥 2000R:  91%|█████████ | 518/569 [00:05<00:00, 89.10frame/s]

   🔥 2000R:  93%|█████████▎| 527/569 [00:06<00:00, 85.50frame/s]

   🔥 2000R:  94%|█████████▍| 536/569 [00:06<00:00, 82.11frame/s]

   🔥 2000R:  96%|█████████▌| 545/569 [00:06<00:00, 79.89frame/s]

   🔥 2000R:  97%|█████████▋| 554/569 [00:06<00:00, 79.57frame/s]

   🔥 2000R:  99%|█████████▉| 564/569 [00:06<00:00, 82.54frame/s]

                                                                 [✅] 2000R: /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/debug/5_heatmap/2000R_heatmap.png
[✅] 2000R (fitted): /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/debug/5_heatmap/2000R_heatmap_fitted.png

📁 Rigs (heatmap):  25%|██▌       | 1/4 [00:08<00:25,  8.39s/rig]

   🔥 1500:   0%|          | 0/490 [00:00<?, ?frame/s]

   🔥 1500:   2%|▏         | 9/490 [00:00<00:05, 80.86frame/s]

   🔥 1500:   4%|▎         | 18/490 [00:00<00:05, 83.46frame/s]

   🔥 1500:   6%|▌         | 27/490 [00:00<00:05, 83.52frame/s]

   🔥 1500:   7%|▋         | 36/490 [00:00<00:05, 83.34frame/s]

   🔥 1500:   9%|▉         | 45/490 [00:00<00:05, 83.03frame/s]

   🔥 1500:  11%|█         | 54/490 [00:00<00:05, 82.97frame/s]

   🔥 1500:  13%|█▎        | 63/490 [00:00<00:05, 82.64frame/s]

   🔥 1500:  15%|█▍        | 72/490 [00:00<00:05, 83.12frame/s]

   🔥 1500:  17%|█▋        | 82/490 [00:00<00:04, 85.48frame/s]

   🔥 1500:  19%|█▊        | 91/490 [00:01<00:04, 86.22frame/s]

   🔥 1500:  20%|██        | 100/490 [00:01<00:04, 86.53frame/s]

   🔥 1500:  22%|██▏       | 109/490 [00:01<00:04, 84.76frame/s]

   🔥 1500:  24%|██▍       | 118/490 [00:01<00:04, 83.81frame/s]

   🔥 1500:  26%|██▌       | 127/490 [00:01<00:04, 84.12frame/s]

   🔥 1500:  28%|██▊       | 136/490 [00:01<00:04, 83.30frame/s]

   🔥 1500:  30%|██▉       | 145/490 [00:01<00:04, 82.76frame/s]

   🔥 1500:  31%|███▏      | 154/490 [00:01<00:04, 80.85frame/s]

   🔥 1500:  33%|███▎      | 163/490 [00:01<00:04, 79.97frame/s]

   🔥 1500:  35%|███▌      | 172/490 [00:02<00:03, 79.81frame/s]

   🔥 1500:  37%|███▋      | 180/490 [00:02<00:03, 79.19frame/s]

   🔥 1500:  38%|███▊      | 188/490 [00:02<00:03, 79.20frame/s]

   🔥 1500:  40%|████      | 196/490 [00:02<00:03, 78.97frame/s]

   🔥 1500:  42%|████▏     | 204/490 [00:02<00:03, 77.32frame/s]

   🔥 1500:  43%|████▎     | 212/490 [00:02<00:03, 76.13frame/s]

   🔥 1500:  45%|████▍     | 220/490 [00:02<00:03, 76.70frame/s]

   🔥 1500:  47%|████▋     | 228/490 [00:02<00:03, 76.41frame/s]

   🔥 1500:  48%|████▊     | 236/490 [00:02<00:03, 77.29frame/s]

   🔥 1500:  50%|█████     | 245/490 [00:03<00:03, 78.76frame/s]

   🔥 1500:  52%|█████▏    | 254/490 [00:03<00:02, 81.18frame/s]

   🔥 1500:  54%|█████▎    | 263/490 [00:03<00:02, 80.12frame/s]

   🔥 1500:  56%|█████▌    | 272/490 [00:03<00:02, 78.47frame/s]

   🔥 1500:  57%|█████▋    | 280/490 [00:03<00:02, 77.20frame/s]

   🔥 1500:  59%|█████▉    | 288/490 [00:03<00:02, 75.67frame/s]

   🔥 1500:  60%|██████    | 296/490 [00:03<00:02, 75.96frame/s]

   🔥 1500:  62%|██████▏   | 304/490 [00:03<00:02, 76.48frame/s]

   🔥 1500:  64%|██████▎   | 312/490 [00:03<00:02, 77.17frame/s]

   🔥 1500:  65%|██████▌   | 320/490 [00:03<00:02, 77.68frame/s]

   🔥 1500:  67%|██████▋   | 328/490 [00:04<00:02, 77.93frame/s]

   🔥 1500:  69%|██████▊   | 336/490 [00:04<00:01, 78.39frame/s]

   🔥 1500:  70%|███████   | 344/490 [00:04<00:01, 78.73frame/s]

   🔥 1500:  72%|███████▏  | 352/490 [00:04<00:01, 78.30frame/s]

   🔥 1500:  73%|███████▎  | 360/490 [00:04<00:01, 78.02frame/s]

   🔥 1500:  75%|███████▌  | 368/490 [00:04<00:01, 78.41frame/s]

   🔥 1500:  77%|███████▋  | 377/490 [00:04<00:01, 79.21frame/s]

   🔥 1500:  79%|███████▊  | 385/490 [00:04<00:01, 78.60frame/s]

   🔥 1500:  80%|████████  | 393/490 [00:04<00:01, 77.76frame/s]

   🔥 1500:  82%|████████▏ | 401/490 [00:05<00:01, 77.27frame/s]

   🔥 1500:  83%|████████▎ | 409/490 [00:05<00:01, 77.73frame/s]

   🔥 1500:  85%|████████▌ | 417/490 [00:05<00:00, 77.73frame/s]

   🔥 1500:  87%|████████▋ | 426/490 [00:05<00:00, 79.20frame/s]

   🔥 1500:  89%|████████▉ | 435/490 [00:05<00:00, 80.78frame/s]

   🔥 1500:  91%|█████████ | 444/490 [00:05<00:00, 82.41frame/s]

   🔥 1500:  92%|█████████▏| 453/490 [00:05<00:00, 84.14frame/s]

   🔥 1500:  94%|█████████▍| 463/490 [00:05<00:00, 86.79frame/s]

   🔥 1500:  97%|█████████▋| 473/490 [00:05<00:00, 87.80frame/s]

   🔥 1500:  99%|█████████▊| 483/490 [00:05<00:00, 88.72frame/s]

                                                                [✅] 1500: /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/debug/5_heatmap/1500_heatmap.png
[✅] 1500 (fitted): /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/debug/5_heatmap/1500_heatmap_fitted.png

📁 Rigs (heatmap):  50%|█████     | 2/4 [00:15<00:15,  7.85s/rig]

   🔥 2000L:   0%|          | 0/589 [00:00<?, ?frame/s]

   🔥 2000L:   2%|▏         | 9/589 [00:00<00:06, 83.85frame/s]

   🔥 2000L:   3%|▎         | 18/589 [00:00<00:07, 80.79frame/s]

   🔥 2000L:   5%|▍         | 27/589 [00:00<00:07, 79.48frame/s]

   🔥 2000L:   6%|▌         | 36/589 [00:00<00:06, 80.53frame/s]

   🔥 2000L:   8%|▊         | 45/589 [00:00<00:06, 80.38frame/s]

   🔥 2000L:   9%|▉         | 54/589 [00:00<00:06, 80.87frame/s]

   🔥 2000L:  11%|█         | 63/589 [00:00<00:06, 82.39frame/s]

   🔥 2000L:  12%|█▏        | 72/589 [00:00<00:06, 84.00frame/s]

   🔥 2000L:  14%|█▍        | 82/589 [00:00<00:05, 87.00frame/s]

   🔥 2000L:  15%|█▌        | 91/589 [00:01<00:05, 87.69frame/s]

   🔥 2000L:  17%|█▋        | 101/589 [00:01<00:05, 89.93frame/s]

   🔥 2000L:  19%|█▉        | 111/589 [00:01<00:05, 91.80frame/s]

   🔥 2000L:  21%|██        | 122/589 [00:01<00:04, 94.65frame/s]

   🔥 2000L:  22%|██▏       | 132/589 [00:01<00:04, 95.08frame/s]

   🔥 2000L:  24%|██▍       | 142/589 [00:01<00:04, 94.71frame/s]

   🔥 2000L:  26%|██▌       | 152/589 [00:01<00:04, 95.36frame/s]

   🔥 2000L:  28%|██▊       | 162/589 [00:01<00:04, 94.70frame/s]

   🔥 2000L:  29%|██▉       | 172/589 [00:01<00:04, 92.59frame/s]

   🔥 2000L:  31%|███       | 182/589 [00:02<00:04, 91.92frame/s]

   🔥 2000L:  33%|███▎      | 192/589 [00:02<00:04, 91.52frame/s]

   🔥 2000L:  34%|███▍      | 202/589 [00:02<00:04, 92.08frame/s]

   🔥 2000L:  36%|███▌      | 212/589 [00:02<00:04, 93.06frame/s]

   🔥 2000L:  38%|███▊      | 222/589 [00:02<00:03, 93.18frame/s]

   🔥 2000L:  39%|███▉      | 232/589 [00:02<00:03, 93.04frame/s]

   🔥 2000L:  41%|████      | 242/589 [00:02<00:03, 91.82frame/s]

   🔥 2000L:  43%|████▎     | 252/589 [00:02<00:03, 92.37frame/s]

   🔥 2000L:  44%|████▍     | 262/589 [00:02<00:03, 92.33frame/s]

   🔥 2000L:  46%|████▌     | 272/589 [00:03<00:03, 89.72frame/s]

   🔥 2000L:  48%|████▊     | 281/589 [00:03<00:03, 87.67frame/s]

   🔥 2000L:  49%|████▉     | 290/589 [00:03<00:03, 87.00frame/s]

   🔥 2000L:  51%|█████     | 299/589 [00:03<00:03, 87.70frame/s]

   🔥 2000L:  52%|█████▏    | 309/589 [00:03<00:03, 89.98frame/s]

   🔥 2000L:  54%|█████▍    | 319/589 [00:03<00:03, 89.16frame/s]

   🔥 2000L:  56%|█████▌    | 328/589 [00:03<00:03, 86.44frame/s]

   🔥 2000L:  57%|█████▋    | 337/589 [00:03<00:02, 84.45frame/s]

   🔥 2000L:  59%|█████▊    | 346/589 [00:03<00:02, 84.34frame/s]

   🔥 2000L:  60%|██████    | 355/589 [00:04<00:02, 84.78frame/s]

   🔥 2000L:  62%|██████▏   | 364/589 [00:04<00:02, 84.90frame/s]

   🔥 2000L:  63%|██████▎   | 373/589 [00:04<00:02, 85.58frame/s]

   🔥 2000L:  65%|██████▍   | 382/589 [00:04<00:02, 86.44frame/s]

   🔥 2000L:  66%|██████▋   | 391/589 [00:04<00:02, 86.34frame/s]

   🔥 2000L:  68%|██████▊   | 400/589 [00:04<00:02, 86.73frame/s]

   🔥 2000L:  69%|██████▉   | 409/589 [00:04<00:02, 86.57frame/s]

   🔥 2000L:  71%|███████   | 418/589 [00:04<00:01, 85.68frame/s]

   🔥 2000L:  72%|███████▏  | 427/589 [00:04<00:01, 85.93frame/s]

   🔥 2000L:  74%|███████▍  | 437/589 [00:04<00:01, 87.37frame/s]

   🔥 2000L:  76%|███████▌  | 447/589 [00:05<00:01, 88.70frame/s]

   🔥 2000L:  78%|███████▊  | 457/589 [00:05<00:01, 89.79frame/s]

   🔥 2000L:  79%|███████▉  | 467/589 [00:05<00:01, 91.12frame/s]

   🔥 2000L:  81%|████████  | 477/589 [00:05<00:01, 89.19frame/s]

   🔥 2000L:  83%|████████▎ | 486/589 [00:05<00:01, 87.15frame/s]

   🔥 2000L:  84%|████████▍ | 495/589 [00:05<00:01, 85.69frame/s]

   🔥 2000L:  86%|████████▌ | 504/589 [00:05<00:01, 84.54frame/s]

   🔥 2000L:  87%|████████▋ | 513/589 [00:05<00:00, 84.31frame/s]

   🔥 2000L:  89%|████████▊ | 522/589 [00:05<00:00, 85.63frame/s]

   🔥 2000L:  90%|█████████ | 532/589 [00:06<00:00, 87.74frame/s]

   🔥 2000L:  92%|█████████▏| 541/589 [00:06<00:00, 87.82frame/s]

   🔥 2000L:  93%|█████████▎| 550/589 [00:06<00:00, 87.43frame/s]

   🔥 2000L:  95%|█████████▍| 559/589 [00:06<00:00, 86.85frame/s]

   🔥 2000L:  96%|█████████▋| 568/589 [00:06<00:00, 85.30frame/s]

   🔥 2000L:  98%|█████████▊| 577/589 [00:06<00:00, 86.15frame/s]

                                                                 [✅] 2000L: /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/debug/5_heatmap/2000L_heatmap.png
[✅] 2000L (fitted): /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/debug/5_heatmap/2000L_heatmap_fitted.png

📁 Rigs (heatmap):  75%|███████▌  | 3/4 [00:24<00:08,  8.14s/rig]

   🔥 1000:   0%|          | 0/282 [00:00<?, ?frame/s]

   🔥 1000:   3%|▎         | 9/282 [00:00<00:03, 85.83frame/s]

   🔥 1000:   6%|▋         | 18/282 [00:00<00:02, 88.02frame/s]

   🔥 1000:  10%|▉         | 27/282 [00:00<00:02, 86.49frame/s]

   🔥 1000:  13%|█▎        | 36/282 [00:00<00:02, 84.85frame/s]

   🔥 1000:  16%|█▌        | 45/282 [00:00<00:02, 83.69frame/s]

   🔥 1000:  19%|█▉        | 54/282 [00:00<00:02, 83.14frame/s]

   🔥 1000:  22%|██▏       | 63/282 [00:00<00:02, 83.87frame/s]

   🔥 1000:  26%|██▌       | 72/282 [00:00<00:02, 82.14frame/s]

   🔥 1000:  29%|██▊       | 81/282 [00:00<00:02, 81.04frame/s]

   🔥 1000:  32%|███▏      | 90/282 [00:01<00:02, 80.53frame/s]

   🔥 1000:  35%|███▌      | 99/282 [00:01<00:02, 80.35frame/s]

   🔥 1000:  38%|███▊      | 108/282 [00:01<00:02, 79.13frame/s]

   🔥 1000:  41%|████      | 116/282 [00:01<00:02, 78.44frame/s]

   🔥 1000:  44%|████▍     | 124/282 [00:01<00:02, 78.10frame/s]

   🔥 1000:  47%|████▋     | 132/282 [00:01<00:01, 77.52frame/s]

   🔥 1000:  50%|█████     | 142/282 [00:01<00:01, 82.65frame/s]

   🔥 1000:  54%|█████▍    | 152/282 [00:01<00:01, 85.04frame/s]

   🔥 1000:  57%|█████▋    | 161/282 [00:01<00:01, 84.75frame/s]

   🔥 1000:  60%|██████    | 170/282 [00:02<00:01, 83.27frame/s]

   🔥 1000:  63%|██████▎   | 179/282 [00:02<00:01, 82.52frame/s]

   🔥 1000:  67%|██████▋   | 188/282 [00:02<00:01, 82.62frame/s]

   🔥 1000:  70%|██████▉   | 197/282 [00:02<00:01, 83.28frame/s]

   🔥 1000:  73%|███████▎  | 207/282 [00:02<00:00, 86.32frame/s]

   🔥 1000:  77%|███████▋  | 217/282 [00:02<00:00, 88.74frame/s]

   🔥 1000:  80%|████████  | 227/282 [00:02<00:00, 88.84frame/s]

   🔥 1000:  84%|████████▎ | 236/282 [00:02<00:00, 88.93frame/s]

   🔥 1000:  87%|████████▋ | 246/282 [00:02<00:00, 89.61frame/s]

   🔥 1000:  90%|█████████ | 255/282 [00:03<00:00, 88.86frame/s]

   🔥 1000:  94%|█████████▎| 264/282 [00:03<00:00, 86.78frame/s]

   🔥 1000:  97%|█████████▋| 273/282 [00:03<00:00, 86.21frame/s]

                                                                [✅] 1000: /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDCP3D-SL-010_W046(6)_2026-04-09/calibration/debug/5_heatmap/1000_heatmap_fitted.png

📁 Rigs (heatmap): 100%|██████████| 4/4 [00:28<00:00,  6.56s/rig]
📁 Rigs (heatmap): 100%|██████████| 4/4 [00:28<00:00,  7.12s/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-010_W046(6)_2026-04-09/calibration/debug/5_heatmap
[🏁] Finished processing MDCP3D-SL-010_W046(6)_2026-04-09


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