
🟢 Starting Calibration Pipeline

=== Processing MDC048_W021(6)_2025-11-19 ===

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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 433 stationary frames, 174 remain

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→ 2000R Phase 2: corners:  96%|█████████▌| 166/173 [00:01<00:00, 134.67it/s][A
                                                                            [A[PASS2] Frame 0000258: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000479: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000480: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000481: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000482: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000484: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000480: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Summary: 4 frames fixed, 7 untrusted, 173 total

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                                                                            [A
[TIMING] 2000R — 174 frames
  Phase 1  radial detect   (parallel)  :   2.86s  (16.4 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.51s  (8.7 ms/frame)
  Phase 2b corner fix      (sequential):   0.21s
  Phase 3  finalize        (sequential):   3.37s  (19.4 ms/frame)
    decode + undistort                 :   1.79s  (10.3 ms/frame)
    corner apply + refinement          :   0.72s  (4.1 ms/frame)
    segment                            :   0.69s  (4.0 ms/frame)
    smooth                             :   0.11s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :   7.94s

Processing Rigs:  25%|██▌       | 1/4 [00:10<00:32, 10.71s/it][INFO] Filtered 469 stationary frames, 204 remain

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                                                                            [A[PASS2] Frame 0000398: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 1 frames fixed, 1 untrusted, 204 total

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                                                                            [A
[TIMING] 2000L — 204 frames
  Phase 1  radial detect   (parallel)  :   3.29s  (16.1 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.94s  (9.5 ms/frame)
  Phase 2b corner fix      (sequential):   0.09s
  Phase 3  finalize        (sequential):   3.76s  (18.5 ms/frame)
    decode + undistort                 :   1.94s  (9.5 ms/frame)
    corner apply + refinement          :   0.82s  (4.0 ms/frame)
    segment                            :   0.81s  (4.0 ms/frame)
    smooth                             :   0.12s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :   9.09s

Processing Rigs:  50%|█████     | 2/4 [00:22<00:22, 11.08s/it][INFO] Filtered 370 stationary frames, 140 remain

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                                                                           [A[PASS2] Frame 0000301: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000565: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000566: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000567: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000568: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000301: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000567: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000301: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Summary: 2 frames fixed, 4 untrusted, 140 total

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                                                                           [A
[TIMING] 1000 — 140 frames
  Phase 1  radial detect   (parallel)  :   2.44s  (17.4 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.50s  (10.7 ms/frame)
  Phase 2b corner fix      (sequential):   0.18s
  Phase 3  finalize        (sequential):   2.41s  (17.2 ms/frame)
    decode + undistort                 :   1.28s  (9.1 ms/frame)
    corner apply + refinement          :   0.46s  (3.3 ms/frame)
    segment                            :   0.53s  (3.8 ms/frame)
    smooth                             :   0.09s  (0.7 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :   6.53s

Processing Rigs:  75%|███████▌  | 3/4 [00:30<00:09,  9.76s/it][INFO] Filtered 481 stationary frames, 202 remain

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                                                                           [A[PASS2] Frame 0000338: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000647: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000648: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000649: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000650: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000338: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000649: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000338: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Summary: 2 frames fixed, 4 untrusted, 202 total

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                                                                           [A
[TIMING] 1500 — 202 frames
  Phase 1  radial detect   (parallel)  :   3.32s  (16.5 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.93s  (9.6 ms/frame)
  Phase 2b corner fix      (sequential):   0.23s
  Phase 3  finalize        (sequential):   3.78s  (18.7 ms/frame)
    decode + undistort                 :   1.91s  (9.5 ms/frame)
    corner apply + refinement          :   0.87s  (4.3 ms/frame)
    segment                            :   0.80s  (3.9 ms/frame)
    smooth                             :   0.14s  (0.7 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :   9.26s

Processing Rigs: 100%|██████████| 4/4 [00:41<00:00, 10.46s/it]Processing Rigs: 100%|██████████| 4/4 [00:41<00:00, 10.44s/it]
[💾] Saved RigFrameDataset to /working/MDC048_W021(6)_2025-11-19/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 720 frames from 4 rigs to /working/MDC048_W021(6)_2025-11-19/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDC048_W021(6)_2025-11-19/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 2000R: 100 frames selected from 174
[📋] 2000L: 100 frames selected from 204
[📋] 1000: 100 frames selected from 140
[📋] 1500: 100 frames selected from 202
[💾] Saved RigFrameDataset to /working/MDC048_W021(6)_2025-11-19/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDC048_W021(6)_2025-11-19/calibration/debug/1_digitized/rig_frames.json

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

-> Calculating the casing center ...
[INFO] Using 60 total sampled bright frames
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3.01s/it]Computing max image from bright frames:  38%|███▊      | 23/60 [01:14<01:54,  3.09s/it]Computing max image from bright frames:  40%|████      | 24/60 [01:18<01:53,  3.16s/it]Computing max image from bright frames:  42%|████▏     | 25/60 [01:21<01:52,  3.21s/it]Computing max image from bright frames:  43%|████▎     | 26/60 [01:24<01:51,  3.27s/it]Computing max image from bright frames:  45%|████▌     | 27/60 [01:28<01:49,  3.33s/it]Computing max image from bright frames:  47%|████▋     | 28/60 [01:31<01:47,  3.37s/it]Computing max image from bright frames:  48%|████▊     | 29/60 [01:35<01:44,  3.37s/it]Computing max image from bright frames:  50%|█████     | 30/60 [01:38<01:40,  3.34s/it]Computing max image from bright frames:  52%|█████▏    | 31/60 [01:41<01:36,  3.33s/it]Computing max image from bright frames:  53%|█████▎    | 32/60 [01:44<01:32,  3.31s/it]Computing max image from bright frames:  55%|█████▌    | 33/60 [01:48<01:29,  3.31s/it]Computing max image from bright frames:  57%|█████▋    | 34/60 [01:51<01:25,  3.31s/it]Computing max image from bright frames:  58%|█████▊    | 35/60 [01:54<01:22,  3.29s/it]Computing max image from bright frames:  60%|██████    | 36/60 [01:58<01:19,  3.30s/it]Computing max image from bright frames:  62%|██████▏   | 37/60 [02:01<01:15,  3.29s/it]Computing max image from bright frames:  63%|██████▎   | 38/60 [02:04<01:12,  3.28s/it]Computing max image from bright frames:  65%|██████▌   | 39/60 [02:07<01:08,  3.28s/it]Computing max image from bright frames:  67%|██████▋   | 40/60 [02:09<00:55,  2.76s/it]Computing max image from bright frames:  68%|██████▊   | 41/60 [02:12<00:55,  2.92s/it]Computing max image from bright frames:  70%|███████   | 42/60 [02:16<00:54,  3.04s/it]Computing max image from bright frames:  72%|███████▏  | 43/60 [02:19<00:53,  3.13s/it]Computing max image from bright frames:  73%|███████▎  | 44/60 [02:22<00:51,  3.19s/it]Computing max image from bright frames:  75%|███████▌  | 45/60 [02:26<00:48,  3.24s/it]Computing max image from bright frames:  77%|███████▋  | 46/60 [02:29<00:45,  3.26s/it]Computing max image from bright frames:  78%|███████▊  | 47/60 [02:32<00:42,  3.27s/it]Computing max image from bright frames:  80%|████████  | 48/60 [02:36<00:39,  3.29s/it]Computing max image from bright frames:  82%|████████▏ | 49/60 [02:39<00:36,  3.33s/it]Computing max image from bright frames:  83%|████████▎ | 50/60 [02:43<00:33,  3.39s/it]Computing max image from bright frames:  85%|████████▌ | 51/60 [02:46<00:30,  3.42s/it]Computing max image from bright frames:  87%|████████▋ | 52/60 [02:50<00:27,  3.45s/it]Computing max image from bright frames:  88%|████████▊ | 53/60 [02:53<00:24,  3.47s/it]Computing max image from bright frames:  90%|█████████ | 54/60 [02:56<00:20,  3.42s/it]Computing max image from bright frames:  92%|█████████▏| 55/60 [03:00<00:16,  3.38s/it]Computing max image from bright frames:  93%|█████████▎| 56/60 [03:03<00:13,  3.35s/it]Computing max image from bright frames:  95%|█████████▌| 57/60 [03:06<00:09,  3.33s/it]Computing max image from bright frames:  97%|█████████▋| 58/60 [03:10<00:06,  3.32s/it]Computing max image from bright frames:  98%|█████████▊| 59/60 [03:13<00:03,  3.31s/it]Computing max image from bright frames: 100%|██████████| 60/60 [03:14<00:00,  2.72s/it]                                                                                       [✅] Casing detection complete: cx=1010.0, cy=723.0

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

  0%|          | 0/100 [00:00<?, ?it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   1%|          | 1/100 [00:00<00:34,  2.90it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   1%|          | 1/100 [00:00<00:34,  2.90it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   2%|▏         | 2/100 [00:00<00:33,  2.90it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   3%|▎         | 3/100 [00:00<00:33,  2.90it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   4%|▍         | 4/100 [00:00<00:33,  2.90it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.000 | Best: {'fx': 335.354} (0.000):   5%|▌         | 5/100 [00:00<00:32,  2.90it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.000 | Best: {'fx': 342.424} (0.000):   6%|▌         | 6/100 [00:00<00:32,  2.90it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.000 | Best: {'fx': 342.424} (0.000):   7%|▋         | 7/100 [00:00<00:05, 17.29it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.001 | Best: {'fx': 349.495} (0.001):   7%|▋         | 7/100 [00:00<00:05, 17.29it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.001 | Best: {'fx': 356.566} (0.001):   8%|▊         | 8/100 [00:00<00:05, 17.29it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.001 | Best: {'fx': 363.636} (0.001):   9%|▉         | 9/100 [00:00<00:05, 17.29it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.001 | Best: {'fx': 363.636} (0.001):  10%|█         | 10/100 [00:00<00:04, 19.03it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.003 | Best: {'fx': 384.848} (0.003):  10%|█         | 10/100 [00:00<00:04, 19.03it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.002 | Best: {'fx': 384.848} (0.003):  11%|█         | 11/100 [00:00<00:04, 19.03it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.003 | Best: {'fx': 384.848} (0.003):  12%|█▏        | 12/100 [00:00<00:04, 19.03it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.004 | Best: {'fx': 398.99} (0.004):  13%|█▎        | 13/100 [00:00<00:04, 19.03it/s] Brute | Start: {'fx': 500.0} (0.040) | Current: 0.005 | Best: {'fx': 406.061} (0.005):  14%|█▍        | 14/100 [00:00<00:04, 19.03it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.005 | Best: {'fx': 406.061} (0.005):  15%|█▌        | 15/100 [00:00<00:03, 25.76it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.004 | Best: {'fx': 406.061} (0.005):  15%|█▌        | 15/100 [00:00<00:03, 25.76it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.005 | Best: {'fx': 413.131} (0.005):  16%|█▌        | 16/100 [00:00<00:03, 25.76it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.006 | Best: {'fx': 420.202} (0.006):  17%|█▋        | 17/100 [00:00<00:03, 25.76it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.006 | Best: {'fx': 427.273} (0.006):  18%|█▊        | 18/100 [00:00<00:03, 25.76it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.006 | Best: {'fx': 427.273} (0.006):  19%|█▉        | 19/100 [00:00<00:02, 28.82it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.007 | Best: {'fx': 434.343} (0.007):  19%|█▉        | 19/100 [00:00<00:02, 28.82it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.012 | Best: {'fx': 455.556} (0.012):  20%|██        | 20/100 [00:01<00:02, 28.82it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.009 | Best: {'fx': 455.556} (0.012):  21%|██        | 21/100 [00:01<00:02, 28.82it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.008 | Best: {'fx': 455.556} (0.012):  22%|██▏       | 22/100 [00:01<00:02, 28.82it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.008 | Best: {'fx': 455.556} (0.012):  23%|██▎       | 23/100 [00:01<00:02, 26.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.016 | Best: {'fx': 469.697} (0.016):  23%|██▎       | 23/100 [00:01<00:02, 26.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 476.768} (0.019):  24%|██▍       | 24/100 [00:01<00:02, 26.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.015 | Best: {'fx': 476.768} (0.019):  25%|██▌       | 25/100 [00:01<00:02, 26.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.029 | Best: {'fx': 490.909} (0.029):  26%|██▌       | 26/100 [00:01<00:02, 26.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.029 | Best: {'fx': 490.909} (0.029):  27%|██▋       | 27/100 [00:01<00:02, 26.42it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.022 | Best: {'fx': 490.909} (0.029):  27%|██▋       | 27/100 [00:01<00:02, 26.42it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.046 | Best: {'fx': 505.051} (0.046):  28%|██▊       | 28/100 [00:01<00:02, 26.42it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.038 | Best: {'fx': 505.051} (0.046):  29%|██▉       | 29/100 [00:01<00:02, 26.42it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.055 | Best: {'fx': 512.121} (0.055):  30%|███       | 30/100 [00:01<00:02, 26.42it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.055 | Best: {'fx': 512.121} (0.055):  31%|███       | 31/100 [00:01<00:02, 25.65it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.070 | Best: {'fx': 519.192} (0.070):  31%|███       | 31/100 [00:01<00:02, 25.65it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.086 | Best: {'fx': 526.263} (0.086):  32%|███▏      | 32/100 [00:01<00:02, 25.65it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.082 | Best: {'fx': 526.263} (0.086):  33%|███▎      | 33/100 [00:01<00:02, 25.65it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.082 | Best: {'fx': 526.263} (0.086):  34%|███▍      | 34/100 [00:01<00:02, 24.48it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.100 | Best: {'fx': 533.333} (0.100):  34%|███▍      | 34/100 [00:01<00:02, 24.48it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.046 | Best: {'fx': 533.333} (0.100):  35%|███▌      | 35/100 [00:01<00:02, 24.48it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.052 | Best: {'fx': 533.333} (0.100):  36%|███▌      | 36/100 [00:01<00:02, 24.48it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.052 | Best: {'fx': 533.333} (0.100):  37%|███▋      | 37/100 [00:01<00:02, 21.85it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.037 | Best: {'fx': 533.333} (0.100):  37%|███▋      | 37/100 [00:01<00:02, 21.85it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.042 | Best: {'fx': 533.333} (0.100):  38%|███▊      | 38/100 [00:01<00:02, 21.85it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.035 | Best: {'fx': 533.333} (0.100):  39%|███▉      | 39/100 [00:01<00:02, 21.85it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.035 | Best: {'fx': 533.333} (0.100):  40%|████      | 40/100 [00:01<00:02, 23.57it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.070 | Best: {'fx': 533.333} (0.100):  40%|████      | 40/100 [00:01<00:02, 23.57it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.039 | Best: {'fx': 533.333} (0.100):  41%|████      | 41/100 [00:01<00:02, 23.57it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.059 | Best: {'fx': 533.333} (0.100):  42%|████▏     | 42/100 [00:01<00:02, 23.57it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.033 | Best: {'fx': 533.333} (0.100):  43%|████▎     | 43/100 [00:01<00:02, 23.57it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.032 | Best: {'fx': 533.333} (0.100):  44%|████▍     | 44/100 [00:01<00:02, 23.57it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.029 | Best: {'fx': 533.333} (0.100):  45%|████▌     | 45/100 [00:01<00:02, 23.57it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.029 | Best: {'fx': 533.333} (0.100):  46%|████▌     | 46/100 [00:01<00:01, 28.58it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.031 | Best: {'fx': 533.333} (0.100):  46%|████▌     | 46/100 [00:02<00:01, 28.58it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.030 | Best: {'fx': 533.333} (0.100):  47%|████▋     | 47/100 [00:02<00:01, 28.58it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.026 | Best: {'fx': 533.333} (0.100):  48%|████▊     | 48/100 [00:02<00:01, 28.58it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.026 | Best: {'fx': 533.333} (0.100):  49%|████▉     | 49/100 [00:02<00:02, 23.49it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.022 | Best: {'fx': 533.333} (0.100):  49%|████▉     | 49/100 [00:02<00:02, 23.49it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.025 | Best: {'fx': 533.333} (0.100):  50%|█████     | 50/100 [00:02<00:02, 23.49it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.027 | Best: {'fx': 533.333} (0.100):  51%|█████     | 51/100 [00:02<00:02, 23.49it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.029 | Best: {'fx': 533.333} (0.100):  52%|█████▏    | 52/100 [00:02<00:02, 23.49it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.027 | Best: {'fx': 533.333} (0.100):  53%|█████▎    | 53/100 [00:02<00:02, 23.49it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.023 | Best: {'fx': 533.333} (0.100):  54%|█████▍    | 54/100 [00:02<00:01, 23.49it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.024 | Best: {'fx': 533.333} (0.100):  55%|█████▌    | 55/100 [00:02<00:01, 23.49it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 533.333} (0.100):  56%|█████▌    | 56/100 [00:02<00:01, 23.49it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 533.333} (0.100):  57%|█████▋    | 57/100 [00:02<00:01, 34.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.026 | Best: {'fx': 533.333} (0.100):  57%|█████▋    | 57/100 [00:02<00:01, 34.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.025 | Best: {'fx': 533.333} (0.100):  58%|█████▊    | 58/100 [00:02<00:01, 34.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.024 | Best: {'fx': 533.333} (0.100):  59%|█████▉    | 59/100 [00:02<00:01, 34.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.022 | Best: {'fx': 533.333} (0.100):  60%|██████    | 60/100 [00:02<00:01, 34.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.022 | Best: {'fx': 533.333} (0.100):  61%|██████    | 61/100 [00:02<00:01, 34.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.024 | Best: {'fx': 533.333} (0.100):  62%|██████▏   | 62/100 [00:02<00:01, 34.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.022 | Best: {'fx': 533.333} (0.100):  63%|██████▎   | 63/100 [00:02<00:01, 34.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.022 | Best: {'fx': 533.333} (0.100):  64%|██████▍   | 64/100 [00:02<00:00, 42.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 533.333} (0.100):  64%|██████▍   | 64/100 [00:02<00:00, 42.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.023 | Best: {'fx': 533.333} (0.100):  65%|██████▌   | 65/100 [00:02<00:00, 42.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 533.333} (0.100):  66%|██████▌   | 66/100 [00:02<00:00, 42.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.023 | Best: {'fx': 533.333} (0.100):  67%|██████▋   | 67/100 [00:02<00:00, 42.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 533.333} (0.100):  68%|██████▊   | 68/100 [00:02<00:00, 42.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 533.333} (0.100):  69%|██████▉   | 69/100 [00:02<00:00, 42.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.022 | Best: {'fx': 533.333} (0.100):  70%|███████   | 70/100 [00:02<00:00, 42.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 533.333} (0.100):  71%|███████   | 71/100 [00:02<00:00, 42.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.100):  72%|███████▏  | 72/100 [00:02<00:00, 42.17it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.100):  73%|███████▎  | 73/100 [00:02<00:00, 45.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.100):  73%|███████▎  | 73/100 [00:02<00:00, 45.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.100):  74%|███████▍  | 74/100 [00:02<00:00, 45.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.100):  75%|███████▌  | 75/100 [00:02<00:00, 45.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.100):  76%|███████▌  | 76/100 [00:02<00:00, 45.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.100):  77%|███████▋  | 77/100 [00:02<00:00, 45.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.100):  78%|███████▊  | 78/100 [00:02<00:00, 45.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.100):  79%|███████▉  | 79/100 [00:02<00:00, 45.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  80%|████████  | 80/100 [00:02<00:00, 45.84it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  81%|████████  | 81/100 [00:02<00:00, 51.55it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  81%|████████  | 81/100 [00:02<00:00, 51.55it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  82%|████████▏ | 82/100 [00:02<00:00, 51.55it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  83%|████████▎ | 83/100 [00:02<00:00, 51.55it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  84%|████████▍ | 84/100 [00:02<00:00, 51.55it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  85%|████████▌ | 85/100 [00:02<00:00, 51.55it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  86%|████████▌ | 86/100 [00:02<00:00, 51.55it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  87%|████████▋ | 87/100 [00:02<00:00, 43.19it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  87%|████████▋ | 87/100 [00:02<00:00, 43.19it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  88%|████████▊ | 88/100 [00:02<00:00, 43.19it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  89%|████████▉ | 89/100 [00:02<00:00, 43.19it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  90%|█████████ | 90/100 [00:02<00:00, 43.19it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  91%|█████████ | 91/100 [00:02<00:00, 43.19it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  92%|█████████▏| 92/100 [00:02<00:00, 39.72it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.018 | Best: {'fx': 533.333} (0.100):  92%|█████████▏| 92/100 [00:03<00:00, 39.72it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.018 | Best: {'fx': 533.333} (0.100):  93%|█████████▎| 93/100 [00:03<00:00, 39.72it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  94%|█████████▍| 94/100 [00:03<00:00, 39.72it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  95%|█████████▌| 95/100 [00:03<00:00, 39.72it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  96%|█████████▌| 96/100 [00:03<00:00, 39.72it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  97%|█████████▋| 97/100 [00:03<00:00, 38.01it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.100):  97%|█████████▋| 97/100 [00:03<00:00, 38.01it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.018 | Best: {'fx': 533.333} (0.100):  98%|█████████▊| 98/100 [00:03<00:00, 38.01it/s]Brute | Start: {'fx': 500.0} (0.040) | Current: 0.018 | Best: {'fx': 533.333} (0.100):  99%|█████████▉| 99/100 [00:03<00:00, 38.01it/s]                                                                                                                                         0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.051 | Best: {'fx': 510.374} (0.051):   0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.051 | Best: {'fx': 510.374} (0.051):   2%|▏         | 1/50 [00:00<00:25,  1.91it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.053 | Best: {'fx': 511.395} (0.053):   2%|▏         | 1/50 [00:00<00:25,  1.91it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.055 | Best: {'fx': 512.415} (0.055):   4%|▍         | 2/50 [00:00<00:25,  1.91it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.049 | Best: {'fx': 512.415} (0.055):   6%|▌         | 3/50 [00:00<00:24,  1.91it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.058 | Best: {'fx': 513.435} (0.058):   8%|▊         | 4/50 [00:00<00:24,  1.91it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.058 | Best: {'fx': 513.435} (0.058):  10%|█         | 5/50 [00:00<00:04,  9.50it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.050 | Best: {'fx': 513.435} (0.058):  10%|█         | 5/50 [00:00<00:04,  9.50it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.062 | Best: {'fx': 515.476} (0.062):  12%|█▏        | 6/50 [00:00<00:04,  9.50it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.060 | Best: {'fx': 515.476} (0.062):  14%|█▍        | 7/50 [00:00<00:04,  9.50it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.068 | Best: {'fx': 518.537} (0.068):  16%|█▌        | 8/50 [00:00<00:04,  9.50it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.068 | Best: {'fx': 518.537} (0.068):  18%|█▊        | 9/50 [00:00<00:02, 14.46it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.064 | Best: {'fx': 518.537} (0.068):  18%|█▊        | 9/50 [00:00<00:02, 14.46it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.074 | Best: {'fx': 520.578} (0.074):  20%|██        | 10/50 [00:00<00:02, 14.46it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.066 | Best: {'fx': 520.578} (0.074):  22%|██▏       | 11/50 [00:00<00:02, 14.46it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.071 | Best: {'fx': 520.578} (0.074):  24%|██▍       | 12/50 [00:00<00:02, 14.46it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.071 | Best: {'fx': 520.578} (0.074):  26%|██▌       | 13/50 [00:00<00:01, 19.29it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.076 | Best: {'fx': 521.599} (0.076):  26%|██▌       | 13/50 [00:01<00:01, 19.29it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.083 | Best: {'fx': 523.639} (0.083):  28%|██▊       | 14/50 [00:01<00:01, 19.29it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.083 | Best: {'fx': 524.66} (0.083):  30%|███       | 15/50 [00:01<00:01, 19.29it/s] Brute | Start: {'fx': 533.333} (0.100) | Current: 0.083 | Best: {'fx': 524.66} (0.083):  32%|███▏      | 16/50 [00:01<00:01, 20.29it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.079 | Best: {'fx': 524.66} (0.083):  32%|███▏      | 16/50 [00:01<00:01, 20.29it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.086 | Best: {'fx': 525.68} (0.086):  34%|███▍      | 17/50 [00:01<00:01, 20.29it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.087 | Best: {'fx': 526.701} (0.087):  36%|███▌      | 18/50 [00:01<00:01, 20.29it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.087 | Best: {'fx': 526.701} (0.087):  38%|███▊      | 19/50 [00:01<00:01, 20.54it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.090 | Best: {'fx': 528.741} (0.090):  38%|███▊      | 19/50 [00:01<00:01, 20.54it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.097 | Best: {'fx': 530.782} (0.097):  40%|████      | 20/50 [00:01<00:01, 20.54it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.094 | Best: {'fx': 530.782} (0.097):  42%|████▏     | 21/50 [00:01<00:01, 20.54it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.101 | Best: {'fx': 531.803} (0.101):  44%|████▍     | 22/50 [00:01<00:01, 20.54it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.087 | Best: {'fx': 531.803} (0.101):  46%|████▌     | 23/50 [00:01<00:01, 20.54it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.087 | Best: {'fx': 531.803} (0.101):  48%|████▊     | 24/50 [00:01<00:00, 26.90it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.101 | Best: {'fx': 532.823} (0.101):  48%|████▊     | 24/50 [00:01<00:00, 26.90it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.081 | Best: {'fx': 532.823} (0.101):  50%|█████     | 25/50 [00:01<00:00, 26.90it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.095 | Best: {'fx': 532.823} (0.101):  52%|█████▏    | 26/50 [00:01<00:00, 26.90it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.100 | Best: {'fx': 532.823} (0.101):  54%|█████▍    | 27/50 [00:01<00:00, 26.90it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.100 | Best: {'fx': 532.823} (0.101):  56%|█████▌    | 28/50 [00:01<00:00, 28.81it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.078 | Best: {'fx': 532.823} (0.101):  56%|█████▌    | 28/50 [00:01<00:00, 28.81it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.082 | Best: {'fx': 532.823} (0.101):  58%|█████▊    | 29/50 [00:01<00:00, 28.81it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.079 | Best: {'fx': 532.823} (0.101):  60%|██████    | 30/50 [00:01<00:00, 28.81it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.076 | Best: {'fx': 532.823} (0.101):  62%|██████▏   | 31/50 [00:01<00:00, 28.81it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.076 | Best: {'fx': 532.823} (0.101):  64%|██████▍   | 32/50 [00:01<00:00, 30.03it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.068 | Best: {'fx': 532.823} (0.101):  64%|██████▍   | 32/50 [00:01<00:00, 30.03it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.074 | Best: {'fx': 532.823} (0.101):  66%|██████▌   | 33/50 [00:01<00:00, 30.03it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.063 | Best: {'fx': 532.823} (0.101):  68%|██████▊   | 34/50 [00:01<00:00, 30.03it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.090 | Best: {'fx': 532.823} (0.101):  70%|███████   | 35/50 [00:01<00:00, 30.03it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.073 | Best: {'fx': 532.823} (0.101):  72%|███████▏  | 36/50 [00:01<00:00, 30.03it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.062 | Best: {'fx': 532.823} (0.101):  74%|███████▍  | 37/50 [00:01<00:00, 30.03it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.094 | Best: {'fx': 532.823} (0.101):  76%|███████▌  | 38/50 [00:01<00:00, 30.03it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.071 | Best: {'fx': 532.823} (0.101):  78%|███████▊  | 39/50 [00:01<00:00, 30.03it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.065 | Best: {'fx': 532.823} (0.101):  80%|████████  | 40/50 [00:01<00:00, 30.03it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.066 | Best: {'fx': 532.823} (0.101):  82%|████████▏ | 41/50 [00:01<00:00, 30.03it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.066 | Best: {'fx': 532.823} (0.101):  84%|████████▍ | 42/50 [00:01<00:00, 46.82it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.085 | Best: {'fx': 532.823} (0.101):  84%|████████▍ | 42/50 [00:01<00:00, 46.82it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.088 | Best: {'fx': 532.823} (0.101):  86%|████████▌ | 43/50 [00:01<00:00, 46.82it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.061 | Best: {'fx': 532.823} (0.101):  88%|████████▊ | 44/50 [00:01<00:00, 46.82it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.057 | Best: {'fx': 532.823} (0.101):  90%|█████████ | 45/50 [00:01<00:00, 46.82it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.060 | Best: {'fx': 532.823} (0.101):  92%|█████████▏| 46/50 [00:01<00:00, 46.82it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.059 | Best: {'fx': 532.823} (0.101):  94%|█████████▍| 47/50 [00:01<00:00, 46.82it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.059 | Best: {'fx': 532.823} (0.101):  96%|█████████▌| 48/50 [00:01<00:00, 46.36it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.056 | Best: {'fx': 532.823} (0.101):  96%|█████████▌| 48/50 [00:01<00:00, 46.36it/s]Brute | Start: {'fx': 533.333} (0.100) | Current: 0.055 | Best: {'fx': 532.823} (0.101):  98%|█████████▊| 49/50 [00:01<00:00, 46.36it/s]                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 532.8231292517007
    px: 1010.0
    py: 723.0
    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 4 incomplete frames): 76 frames will be used for optimization
  Rigs: 2000R(2000mm):19/20, 2000L(2000mm):19/20, 1000(1000mm):19/20, 1500(1500mm):19/20
  Total: 76/80 frames used for optimization
Initial score: 13.4732: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 13.4732, picklable_objective(x0) = 13.2588
Best score: 13.2588: : 0iter [00:02, ?iter/s] Best score: 13.2588: : 1iter [00:02,  2.03s/iter]Best score: 13.2588: : 1iter [00:02,  2.03s/iter]Best score: 13.2588: : 2iter [00:02,  2.03s/iter]Best score: 13.2588: : 3iter [00:02,  1.70iter/s]Best score: 13.2588: : 3iter [00:02,  1.70iter/s]Best score: 13.2588: : 4iter [00:02,  1.70iter/s]Best score: 13.2588: : 5iter [00:02,  3.04iter/s]Best score: 13.2588: : 5iter [00:02,  3.04iter/s]Best score: 13.2588: : 6iter [00:02,  3.04iter/s]Best score: 13.2588: : 7iter [00:02,  4.46iter/s]Best score: 13.2588: : 7iter [00:02,  4.46iter/s]Best score: 13.2588: : 8iter [00:02,  4.46iter/s]Best score: 13.2588: : 9iter [00:02,  5.86iter/s]Best score: 13.2588: : 9iter [00:02,  5.86iter/s]Best score: 13.2588: : 10iter [00:02,  5.86iter/s]Best score: 13.2588: : 11iter [00:02,  7.08iter/s]Best score: 13.2588: : 11iter [00:02,  7.08iter/s]Best score: 13.2588: : 12iter [00:03,  7.08iter/s]Best score: 13.2588: : 13iter [00:03,  8.19iter/s]Best score: 13.2588: : 13iter [00:03,  8.19iter/s]Best score: 13.2588: : 14iter [00:03,  8.19iter/s]Best score: 13.2588: : 15iter [00:03,  9.12iter/s]Best score: 13.2588: : 15iter [00:03,  9.12iter/s]Best score: 13.2588: : 16iter [00:03,  9.12iter/s]Best score: 13.2588: : 17iter [00:03,  9.86iter/s]Best score: 13.2588: : 17iter [00:03,  9.86iter/s]Best score: 13.2588: : 18iter [00:03,  9.86iter/s]Best score: 13.2588: : 19iter [00:03, 10.46iter/s]Best score: 13.2588: : 19iter [00:03, 10.46iter/s]Best score: 13.2588: : 20iter [00:03, 10.46iter/s]Best score: 13.2588: : 21iter [00:03, 10.74iter/s]Best score: 13.2588: : 21iter [00:03, 10.74iter/s]Best score: 13.2588: : 22iter [00:03, 10.74iter/s]Best score: 13.2588: : 23iter [00:03, 11.12iter/s]Best score: 13.2588: : 23iter [00:03, 11.12iter/s]Best score: 13.2588: : 24iter [00:04, 11.12iter/s]Best score: 13.2588: : 25iter [00:04, 11.41iter/s]Best score: 13.2588: : 25iter [00:04, 11.41iter/s]Best score: 13.2588: : 26iter [00:04, 11.41iter/s]Best score: 13.2588: : 27iter [00:04, 11.61iter/s]Best score: 13.2588: : 27iter [00:04, 11.61iter/s]Best score: 13.2588: : 28iter [00:04, 11.61iter/s]Best score: 13.2588: : 29iter [00:04, 11.77iter/s]Best score: 13.2588: : 29iter [00:04, 11.77iter/s]Best score: 13.2588: : 30iter [00:04, 11.77iter/s]Best score: 13.2588: : 31iter [00:04, 11.70iter/s]Best score: 13.2588: : 31iter [00:04, 11.70iter/s]Best score: 13.2588: : 32iter [00:04, 11.70iter/s]Best score: 13.2588: : 33iter [00:04, 11.82iter/s]Best score: 13.2588: : 33iter [00:04, 11.82iter/s]Best score: 13.2588: : 34iter [00:04, 11.82iter/s]Best score: 13.2588: : 35iter [00:04, 11.94iter/s]Best score: 13.2588: : 35iter [00:04, 11.94iter/s]Best score: 13.2588: : 36iter [00:05, 11.94iter/s]Best score: 13.2588: : 37iter [00:05, 11.97iter/s]Best score: 13.2588: : 37iter [00:05, 11.97iter/s]Best score: 13.2588: : 38iter [00:05, 11.97iter/s]Best score: 13.2588: : 39iter [00:05, 11.99iter/s]Best score: 13.2588: : 39iter [00:05, 11.99iter/s]Best score: 13.2588: : 40iter [00:05, 11.99iter/s]Best score: 13.2588: : 41iter [00:05, 11.90iter/s]Best score: 13.2588: : 41iter [00:05, 11.90iter/s]Best score: 13.2588: : 42iter [00:05, 11.90iter/s]Best score: 13.2588: : 43iter [00:05, 12.00iter/s]Best score: 13.2588: : 43iter [00:05, 12.00iter/s]Best score: 13.2588: : 44iter [00:05, 12.00iter/s]Best score: 13.2588: : 45iter [00:05, 12.05iter/s]Best score: 13.2588: : 45iter [00:05, 12.05iter/s]Best score: 13.2588: : 46iter [00:05, 12.05iter/s]Best score: 13.2588: : 47iter [00:05, 12.07iter/s]Best score: 13.2588: : 47iter [00:05, 12.07iter/s]Best score: 13.2588: : 48iter [00:06, 12.07iter/s]Best score: 13.2588: : 49iter [00:06, 12.09iter/s]
[ITER 50] Best: 13.2588
[PARAMS] Current best parameters:
  fx: 532.8231
  fy: 532.8231
  px: 1010.0000
  py: 723.0000
  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: 13.2588: : 49iter [00:06, 12.09iter/s]Best score: 13.2588: : 50iter [00:06, 12.09iter/s]Best score: 13.2588: : 51iter [00:06, 11.96iter/s]Best score: 13.2588: : 51iter [00:06, 11.96iter/s]Best score: 13.2588: : 52iter [00:06, 11.96iter/s]Best score: 13.2588: : 53iter [00:06, 11.99iter/s]Best score: 13.2588: : 53iter [00:06, 11.99iter/s]Best score: 13.2588: : 54iter [00:06, 11.99iter/s]Best score: 13.2588: : 55iter [00:06, 12.08iter/s]Best score: 13.2588: : 55iter [00:06, 12.08iter/s]Best score: 13.2588: : 56iter [00:06, 12.08iter/s]Best score: 13.2588: : 57iter [00:06, 12.10iter/s]Best score: 13.2588: : 57iter [00:06, 12.10iter/s]Best score: 13.2588: : 58iter [00:06, 12.10iter/s]Best score: 13.2588: : 59iter [00:06, 12.21iter/s]Best score: 13.0079: : 59iter [00:06, 12.21iter/s]Best score: 13.0079: : 60iter [00:07, 12.21iter/s]Best score: 13.0079: : 61iter [00:07, 12.01iter/s]Best score: 13.0079: : 61iter [00:07, 12.01iter/s]Best score: 13.0079: : 62iter [00:07, 12.01iter/s]Best score: 13.0079: : 63iter [00:07, 12.07iter/s]Best score: 13.0079: : 63iter [00:07, 12.07iter/s]Best score: 13.0079: : 64iter [00:07, 12.07iter/s]Best score: 13.0079: : 65iter [00:07, 12.19iter/s]Best score: 13.0079: : 65iter [00:07, 12.19iter/s]Best score: 13.0079: : 66iter [00:07, 12.19iter/s]Best score: 13.0079: : 67iter [00:07, 12.24iter/s]Best score: 13.0079: : 67iter [00:07, 12.24iter/s]Best score: 13.0079: : 68iter [00:07, 12.24iter/s]Best score: 13.0079: : 69iter [00:07, 12.25iter/s]Best score: 7.2395: : 69iter [00:07, 12.25iter/s] Best score: 7.2395: : 70iter [00:07, 12.25iter/s]Best score: 7.2395: : 71iter [00:07, 12.11iter/s]Best score: 7.2395: : 71iter [00:07, 12.11iter/s]Best score: 7.2395: : 72iter [00:08, 12.11iter/s]Best score: 7.2395: : 73iter [00:08, 12.15iter/s]Best score: 7.2395: : 73iter [00:08, 12.15iter/s]Best score: 7.2395: : 74iter [00:08, 12.15iter/s]Best score: 7.2395: : 75iter [00:08, 12.19iter/s]Best score: 7.2395: : 75iter [00:08, 12.19iter/s]Best score: 7.2395: : 76iter [00:08, 12.19iter/s]Best score: 7.2395: : 77iter [00:08, 12.25iter/s]Best score: 7.2395: : 77iter [00:08, 12.25iter/s]Best score: 7.2395: : 78iter [00:08, 12.25iter/s]Best score: 7.2395: : 79iter [00:08, 12.33iter/s]Best score: 7.2395: : 79iter [00:08, 12.33iter/s]Best score: 7.2395: : 80iter [00:08, 12.33iter/s]Best score: 7.2395: : 81iter [00:08, 12.16iter/s]Best score: 7.2395: : 81iter [00:08, 12.16iter/s]Best score: 7.2395: : 82iter [00:08, 12.16iter/s]Best score: 7.2395: : 83iter [00:08, 12.19iter/s]Best score: 7.2395: : 83iter [00:08, 12.19iter/s]Best score: 7.2395: : 84iter [00:08, 12.19iter/s]Best score: 7.2395: : 85iter [00:08, 12.28iter/s]Best score: 7.2395: : 85iter [00:09, 12.28iter/s]Best score: 7.2395: : 86iter [00:09, 12.28iter/s]Best score: 7.2395: : 87iter [00:09, 12.34iter/s]Best score: 7.2395: : 87iter [00:09, 12.34iter/s]Best score: 7.2395: : 88iter [00:09, 12.34iter/s]Best score: 7.2395: : 89iter [00:09, 12.31iter/s]Best score: 5.2520: : 89iter [00:09, 12.31iter/s]Best score: 5.2520: : 90iter [00:09, 12.31iter/s]Best score: 5.2520: : 91iter [00:09, 12.15iter/s]Best score: 5.2520: : 91iter [00:09, 12.15iter/s]Best score: 5.2520: : 92iter [00:09, 12.15iter/s]Best score: 5.2520: : 93iter [00:09, 12.25iter/s]Best score: 5.2520: : 93iter [00:09, 12.25iter/s]Best score: 5.2520: : 94iter [00:09, 12.25iter/s]Best score: 5.2520: : 95iter [00:09, 12.31iter/s]Best score: 5.2520: : 95iter [00:09, 12.31iter/s]Best score: 5.2520: : 96iter [00:09, 12.31iter/s]Best score: 5.2520: : 97iter [00:09, 12.33iter/s]Best score: 5.2520: : 97iter [00:10, 12.33iter/s]Best score: 5.2520: : 98iter [00:10, 12.33iter/s]Best score: 5.2520: : 99iter [00:10, 12.37iter/s]
[ITER 100] Best: 3.6652
[PARAMS] Current best parameters:
  fx: 567.6509
  fy: 567.6288
  px: 1023.6381
  py: 727.8358
  k1: 0.01735679
  k2: -0.06338629
  k3: 0.02198980
  k4: -0.00093659
  p1: -0.00843666
  p2: -0.00114962
  p3: 0.01454345
  p4: 0.03356804
  s1: -0.0224
  s2: -0.0166
  s3: 0.0033
  s4: -0.0464
  tilt_x: 0.0339
  tilt_y: -0.0615
  scale: 2.9575
  rotation: -0.1137
Best score: 3.6652: : 99iter [00:10, 12.37iter/s]Best score: 3.6652: : 100iter [00:10, 12.37iter/s]Best score: 3.6652: : 101iter [00:10, 10.54iter/s]Best score: 3.6652: : 101iter [00:10, 10.54iter/s]Best score: 3.6652: : 102iter [00:10, 10.54iter/s]Best score: 3.6652: : 103iter [00:10, 10.95iter/s]Best score: 3.6652: : 103iter [00:10, 10.95iter/s]Best score: 3.6652: : 104iter [00:10, 10.95iter/s]Best score: 3.6652: : 105iter [00:10, 11.30iter/s]Best score: 3.6652: : 105iter [00:10, 11.30iter/s]Best score: 3.6652: : 106iter [00:10, 11.30iter/s]Best score: 3.6652: : 107iter [00:10, 11.51iter/s]Best score: 3.6652: : 107iter [00:10, 11.51iter/s]Best score: 3.6652: : 108iter [00:11, 11.51iter/s]Best score: 3.6652: : 109iter [00:11, 11.66iter/s]Best score: 3.6652: : 109iter [00:11, 11.66iter/s]Best score: 3.6652: : 110iter [00:11, 11.66iter/s]Best score: 3.6652: : 111iter [00:11, 11.61iter/s]Best score: 3.6652: : 111iter [00:11, 11.61iter/s]Best score: 3.6652: : 112iter [00:11, 11.61iter/s]Best score: 3.6652: : 113iter [00:11, 11.76iter/s]Best score: 3.6652: : 113iter [00:11, 11.76iter/s]Best score: 3.6652: : 114iter [00:11, 11.76iter/s]Best score: 3.6652: : 115iter [00:11, 11.87iter/s]Best score: 3.6652: : 115iter [00:11, 11.87iter/s]Best score: 3.6652: : 116iter [00:11, 11.87iter/s]Best score: 3.6652: : 117iter [00:11, 11.93iter/s]Best score: 3.6652: : 117iter [00:11, 11.93iter/s]Best score: 3.6652: : 118iter [00:11, 11.93iter/s]Best score: 3.6652: : 119iter [00:11, 12.03iter/s]Best score: 3.6652: : 119iter [00:11, 12.03iter/s]Best score: 3.6652: : 120iter [00:12, 12.03iter/s]Best score: 3.6652: : 121iter [00:12, 11.86iter/s]Best score: 3.6652: : 121iter [00:12, 11.86iter/s]Best score: 3.6652: : 122iter [00:12, 11.86iter/s]Best score: 3.6652: : 123iter [00:12, 11.95iter/s]Best score: 3.6652: : 123iter [00:12, 11.95iter/s]Best score: 3.6652: : 124iter [00:12, 11.95iter/s]Best score: 3.6652: : 125iter [00:12, 12.00iter/s]Best score: 3.6652: : 125iter [00:12, 12.00iter/s]Best score: 3.6652: : 126iter [00:12, 12.00iter/s]Best score: 3.6652: : 127iter [00:12, 12.01iter/s]Best score: 3.6652: : 127iter [00:12, 12.01iter/s]Best score: 3.6652: : 128iter [00:12, 12.01iter/s]Best score: 3.6652: : 129iter [00:12, 12.07iter/s]Best score: 3.6652: : 129iter [00:12, 12.07iter/s]Best score: 3.6652: : 130iter [00:12, 12.07iter/s]Best score: 3.6652: : 131iter [00:12, 11.89iter/s]Best score: 3.6652: : 131iter [00:12, 11.89iter/s]Best score: 3.6652: : 132iter [00:13, 11.89iter/s]Best score: 3.6652: : 133iter [00:13, 12.01iter/s]Best score: 3.6652: : 133iter [00:13, 12.01iter/s]Best score: 3.6652: : 134iter [00:13, 12.01iter/s]Best score: 3.6652: : 135iter [00:13, 12.09iter/s]Best score: 3.6652: : 135iter [00:13, 12.09iter/s]Best score: 3.6652: : 136iter [00:13, 12.09iter/s]Best score: 3.6652: : 137iter [00:13, 12.17iter/s]Best score: 3.6652: : 137iter [00:13, 12.17iter/s]Best score: 3.6652: : 138iter [00:13, 12.17iter/s]Best score: 3.6652: : 139iter [00:13, 12.19iter/s]Best score: 3.6652: : 139iter [00:13, 12.19iter/s]Best score: 3.6652: : 140iter [00:13, 12.19iter/s]Best score: 3.6652: : 141iter [00:13, 12.03iter/s]Best score: 3.6652: : 141iter [00:13, 12.03iter/s]Best score: 3.6652: : 142iter [00:13, 12.03iter/s]Best score: 3.6652: : 143iter [00:13, 12.14iter/s]Best score: 3.6652: : 143iter [00:13, 12.14iter/s]Best score: 3.6652: : 144iter [00:14, 12.14iter/s]Best score: 3.6652: : 145iter [00:14, 12.20iter/s]Best score: 3.6652: : 145iter [00:14, 12.20iter/s]Best score: 3.6652: : 146iter [00:14, 12.20iter/s]Best score: 3.6652: : 147iter [00:14, 12.23iter/s]Best score: 3.6652: : 147iter [00:14, 12.23iter/s]Best score: 3.6652: : 148iter [00:14, 12.23iter/s]Best score: 3.6652: : 149iter [00:14, 12.21iter/s]
[ITER 150] Best: 3.6652
[PARAMS] Current best parameters:
  fx: 567.6509
  fy: 567.6288
  px: 1023.6381
  py: 727.8358
  k1: 0.01735679
  k2: -0.06338629
  k3: 0.02198980
  k4: -0.00093659
  p1: -0.00843666
  p2: -0.00114962
  p3: 0.01454345
  p4: 0.03356804
  s1: -0.0224
  s2: -0.0166
  s3: 0.0033
  s4: -0.0464
  tilt_x: 0.0339
  tilt_y: -0.0615
  scale: 2.9575
  rotation: -0.1137
Best score: 3.6652: : 149iter [00:14, 12.21iter/s]Best score: 3.6652: : 150iter [00:14, 12.21iter/s]Best score: 3.6652: : 151iter [00:14,  7.85iter/s]Best score: 3.6652: : 151iter [00:14,  7.85iter/s]Best score: 3.6652: : 152iter [00:14,  7.85iter/s]Best score: 3.6652: : 153iter [00:14,  8.82iter/s]Best score: 3.6652: : 153iter [00:15,  8.82iter/s]Best score: 3.6652: : 154iter [00:15,  8.82iter/s]Best score: 3.6652: : 155iter [00:15,  9.66iter/s]Best score: 3.6652: : 155iter [00:15,  9.66iter/s]Best score: 3.6652: : 156iter [00:15,  9.66iter/s]Best score: 3.6652: : 157iter [00:15, 10.38iter/s]Best score: 3.6652: : 157iter [00:15, 10.38iter/s]Best score: 3.6652: : 158iter [00:15, 10.38iter/s]Best score: 3.6652: : 159iter [00:15, 10.92iter/s]Best score: 3.6652: : 159iter [00:15, 10.92iter/s]Best score: 3.6652: : 160iter [00:15, 10.92iter/s]Best score: 3.6652: : 161iter [00:15, 11.18iter/s]Best score: 3.6652: : 161iter [00:15, 11.18iter/s]Best score: 3.6652: : 162iter [00:15, 11.18iter/s]Best score: 3.6652: : 163iter [00:15, 11.53iter/s]Best score: 3.6652: : 163iter [00:15, 11.53iter/s]Best score: 3.6652: : 164iter [00:15, 11.53iter/s]Best score: 3.6652: : 165iter [00:15, 11.83iter/s]Best score: 3.6652: : 165iter [00:16, 11.83iter/s]Best score: 3.6652: : 166iter [00:16, 11.83iter/s]Best score: 3.6652: : 167iter [00:16, 12.01iter/s]Best score: 3.6652: : 167iter [00:16, 12.01iter/s]Best score: 3.6652: : 168iter [00:16, 12.01iter/s]Best score: 3.6652: : 169iter [00:16, 12.16iter/s]Best score: 3.6652: : 169iter [00:16, 12.16iter/s]Best score: 3.6652: : 170iter [00:16, 12.16iter/s]Best score: 3.6652: : 171iter [00:16, 12.05iter/s]Best score: 3.6652: : 171iter [00:16, 12.05iter/s]Best score: 3.6652: : 172iter [00:16, 12.05iter/s]Best score: 3.6652: : 173iter [00:16, 12.19iter/s]Best score: 3.6652: : 173iter [00:16, 12.19iter/s]Best score: 3.6652: : 174iter [00:16, 12.19iter/s]Best score: 3.6652: : 175iter [00:16,  9.97iter/s]Best score: 3.6652: : 175iter [00:16,  9.97iter/s]Best score: 3.6652: : 176iter [00:17,  9.97iter/s]Best score: 3.6652: : 177iter [00:17, 10.62iter/s]Best score: 3.6652: : 177iter [00:17, 10.62iter/s]Best score: 3.6652: : 178iter [00:17, 10.62iter/s]Best score: 3.6652: : 179iter [00:17, 11.10iter/s]Best score: 3.6652: : 179iter [00:17, 11.10iter/s]Best score: 3.6652: : 180iter [00:17, 11.10iter/s]Best score: 3.6652: : 181iter [00:17, 11.30iter/s]Best score: 3.6652: : 181iter [00:17, 11.30iter/s]Best score: 3.6652: : 182iter [00:17, 11.30iter/s]Best score: 3.6652: : 183iter [00:17, 11.64iter/s]Best score: 3.6652: : 183iter [00:17, 11.64iter/s]Best score: 3.6652: : 184iter [00:17, 11.64iter/s]Best score: 3.6652: : 185iter [00:17, 11.87iter/s]Best score: 3.6652: : 185iter [00:17, 11.87iter/s]Best score: 3.6652: : 186iter [00:17, 11.87iter/s]Best score: 3.6652: : 187iter [00:17, 12.00iter/s]Best score: 3.6652: : 187iter [00:17, 12.00iter/s]Best score: 3.6652: : 188iter [00:18, 12.00iter/s]Best score: 3.6652: : 189iter [00:18, 12.14iter/s]Best score: 3.6652: : 189iter [00:18, 12.14iter/s]Best score: 3.6652: : 190iter [00:18, 12.14iter/s]Best score: 3.6652: : 191iter [00:18, 12.02iter/s]Best score: 3.6652: : 191iter [00:18, 12.02iter/s]Best score: 3.6652: : 192iter [00:18, 12.02iter/s]Best score: 3.6652: : 193iter [00:18, 12.15iter/s]Best score: 3.6652: : 193iter [00:18, 12.15iter/s]Best score: 3.6652: : 194iter [00:18, 12.15iter/s]Best score: 3.6652: : 195iter [00:18, 12.20iter/s]Best score: 3.6652: : 195iter [00:18, 12.20iter/s]Best score: 3.6652: : 196iter [00:18, 12.20iter/s]Best score: 3.6652: : 197iter [00:18, 12.30iter/s]Best score: 3.6652: : 197iter [00:18, 12.30iter/s]Best score: 3.6652: : 198iter [00:18, 12.30iter/s]Best score: 3.6652: : 199iter [00:18, 12.40iter/s]
[ITER 200] Best: 3.6652
[PARAMS] Current best parameters:
  fx: 567.6509
  fy: 567.6288
  px: 1023.6381
  py: 727.8358
  k1: 0.01735679
  k2: -0.06338629
  k3: 0.02198980
  k4: -0.00093659
  p1: -0.00843666
  p2: -0.00114962
  p3: 0.01454345
  p4: 0.03356804
  s1: -0.0224
  s2: -0.0166
  s3: 0.0033
  s4: -0.0464
  tilt_x: 0.0339
  tilt_y: -0.0615
  scale: 2.9575
  rotation: -0.1137
Best score: 3.6652: : 199iter [00:18, 12.40iter/s]Best score: 3.6652: : 200iter [00:19, 12.40iter/s]Best score: 3.6652: : 201iter [00:19,  7.87iter/s]Best score: 3.6652: : 201iter [00:19,  7.87iter/s]Best score: 3.6652: : 202iter [00:19,  7.87iter/s]Best score: 3.6652: : 203iter [00:19,  8.86iter/s]Best score: 3.6652: : 203iter [00:19,  8.86iter/s]Best score: 3.6652: : 204iter [00:19,  8.86iter/s]Best score: 3.6652: : 205iter [00:19,  9.70iter/s]Best score: 3.6652: : 205iter [00:19,  9.70iter/s]Best score: 3.6652: : 206iter [00:19,  9.70iter/s]Best score: 3.6652: : 207iter [00:19, 10.35iter/s]Best score: 3.6652: : 207iter [00:19, 10.35iter/s]Best score: 3.6652: : 208iter [00:19, 10.35iter/s]Best score: 3.6652: : 209iter [00:19, 10.87iter/s]Best score: 3.6652: : 209iter [00:20, 10.87iter/s]Best score: 3.6652: : 210iter [00:20, 10.87iter/s]Best score: 3.6652: : 211iter [00:20, 11.14iter/s]Best score: 3.6652: : 211iter [00:20, 11.14iter/s]Best score: 3.6652: : 212iter [00:20, 11.14iter/s]Best score: 3.6652: : 213iter [00:20, 11.52iter/s]Best score: 3.6652: : 213iter [00:20, 11.52iter/s]Best score: 3.6652: : 214iter [00:20, 11.52iter/s]Best score: 3.6652: : 215iter [00:20, 11.73iter/s]Best score: 3.6652: : 215iter [00:20, 11.73iter/s]Best score: 3.6652: : 216iter [00:20, 11.73iter/s]Best score: 3.6652: : 217iter [00:20, 11.96iter/s]Best score: 3.6652: : 217iter [00:20, 11.96iter/s]Best score: 3.6652: : 218iter [00:20, 11.96iter/s]Best score: 3.6652: : 219iter [00:20, 12.08iter/s]Best score: 3.6652: : 219iter [00:20, 12.08iter/s]Best score: 3.6652: : 220iter [00:20, 12.08iter/s]Best score: 3.6652: : 221iter [00:20, 11.96iter/s]Best score: 3.6652: : 221iter [00:21, 11.96iter/s]Best score: 3.6652: : 222iter [00:21, 11.96iter/s]Best score: 3.6652: : 223iter [00:21, 12.13iter/s]Best score: 3.6652: : 223iter [00:21, 12.13iter/s]Best score: 3.6652: : 224iter [00:21, 12.13iter/s]Best score: 3.6652: : 225iter [00:21, 12.26iter/s]Best score: 3.6652: : 225iter [00:21, 12.26iter/s]Best score: 3.6652: : 226iter [00:21, 12.26iter/s]Best score: 3.6652: : 227iter [00:21, 12.36iter/s]Best score: 3.6652: : 227iter [00:21, 12.36iter/s]Best score: 3.6652: : 228iter [00:21, 12.36iter/s]Best score: 3.6652: : 229iter [00:21, 12.37iter/s]Best score: 3.6652: : 229iter [00:21, 12.37iter/s]Best score: 3.6652: : 230iter [00:21, 12.37iter/s]Best score: 3.6652: : 231iter [00:21, 12.22iter/s]Best score: 3.6652: : 231iter [00:21, 12.22iter/s]Best score: 3.6652: : 232iter [00:21, 12.22iter/s]Best score: 3.6652: : 233iter [00:21, 12.33iter/s]Best score: 3.6652: : 233iter [00:21, 12.33iter/s]Best score: 3.6652: : 234iter [00:22, 12.33iter/s]Best score: 3.6652: : 235iter [00:22, 12.40iter/s]Best score: 3.6652: : 235iter [00:22, 12.40iter/s]Best score: 3.6652: : 236iter [00:22, 12.40iter/s]Best score: 3.6652: : 237iter [00:22, 12.42iter/s]Best score: 3.6652: : 237iter [00:22, 12.42iter/s]Best score: 3.6652: : 238iter [00:22, 12.42iter/s]Best score: 3.6652: : 239iter [00:22, 12.45iter/s]Best score: 2.1853: : 239iter [00:22, 12.45iter/s]Best score: 2.1853: : 240iter [00:22, 12.45iter/s]Best score: 2.1853: : 241iter [00:22, 12.26iter/s]Best score: 2.1853: : 241iter [00:22, 12.26iter/s]Best score: 2.1853: : 242iter [00:22, 12.26iter/s]Best score: 2.1853: : 243iter [00:22, 12.27iter/s]Best score: 2.1853: : 243iter [00:22, 12.27iter/s]Best score: 2.1853: : 244iter [00:22, 12.27iter/s]Best score: 2.1853: : 245iter [00:22, 12.35iter/s]Best score: 2.1853: : 245iter [00:22, 12.35iter/s]Best score: 2.1853: : 246iter [00:23, 12.35iter/s]Best score: 2.1853: : 247iter [00:23, 12.35iter/s]Best score: 2.1853: : 247iter [00:23, 12.35iter/s]Best score: 2.1853: : 248iter [00:23, 12.35iter/s]Best score: 2.1853: : 249iter [00:23, 12.37iter/s]
[ITER 250] Best: 2.1853
[PARAMS] Current best parameters:
  fx: 566.7901
  fy: 567.8486
  px: 1027.2172
  py: 723.2794
  k1: 0.01050771
  k2: -0.06508850
  k3: 0.03499709
  k4: -0.00670323
  p1: -0.02045566
  p2: 0.00534412
  p3: 0.01446448
  p4: 0.03172459
  s1: -0.0218
  s2: -0.0232
  s3: 0.0030
  s4: -0.0426
  tilt_x: 0.0289
  tilt_y: -0.0579
  scale: 2.9573
  rotation: -0.4128
Best score: 2.1853: : 249iter [00:23, 12.37iter/s]Best score: 2.1853: : 250iter [00:23, 12.37iter/s]Best score: 2.1853: : 251iter [00:23,  7.97iter/s]Best score: 2.1853: : 251iter [00:23,  7.97iter/s]Best score: 2.1853: : 252iter [00:23,  7.97iter/s]Best score: 2.1853: : 253iter [00:23,  8.93iter/s]Best score: 2.1853: : 253iter [00:23,  8.93iter/s]Best score: 2.1853: : 254iter [00:23,  8.93iter/s]Best score: 2.1853: : 255iter [00:23,  9.75iter/s]Best score: 2.1853: : 255iter [00:24,  9.75iter/s]Best score: 2.1853: : 256iter [00:24,  9.75iter/s]Best score: 2.1853: : 257iter [00:24, 10.44iter/s]Best score: 2.1853: : 257iter [00:24, 10.44iter/s]Best score: 2.1853: : 258iter [00:24, 10.44iter/s]Best score: 2.1853: : 259iter [00:24, 10.96iter/s]Best score: 1.7500: : 259iter [00:24, 10.96iter/s]Best score: 1.7500: : 260iter [00:24, 10.96iter/s]Best score: 1.7500: : 261iter [00:24, 11.19iter/s]Best score: 1.7500: : 261iter [00:24, 11.19iter/s]Best score: 1.7500: : 262iter [00:24, 11.19iter/s]Best score: 1.7500: : 263iter [00:24, 11.51iter/s]Best score: 1.7500: : 263iter [00:24, 11.51iter/s]Best score: 1.7500: : 264iter [00:24, 11.51iter/s]Best score: 1.7500: : 265iter [00:24, 11.79iter/s]Best score: 1.7500: : 265iter [00:24, 11.79iter/s]Best score: 1.7500: : 266iter [00:24, 11.79iter/s]Best score: 1.7500: : 267iter [00:24, 12.00iter/s]Best score: 1.7500: : 267iter [00:25, 12.00iter/s]Best score: 1.7500: : 268iter [00:25, 12.00iter/s]Best score: 1.7500: : 269iter [00:25, 12.13iter/s]Best score: 1.7500: : 269iter [00:25, 12.13iter/s]Best score: 1.7500: : 270iter [00:25, 12.13iter/s]Best score: 1.7500: : 271iter [00:25, 12.02iter/s]Best score: 1.7500: : 271iter [00:25, 12.02iter/s]Best score: 1.7500: : 272iter [00:25, 12.02iter/s]Best score: 1.7500: : 273iter [00:25, 12.18iter/s]Best score: 1.7500: : 273iter [00:25, 12.18iter/s]Best score: 1.7500: : 274iter [00:25, 12.18iter/s]Best score: 1.7500: : 275iter [00:25, 12.25iter/s]Best score: 1.7500: : 275iter [00:25, 12.25iter/s]Best score: 1.7500: : 276iter [00:25, 12.25iter/s]Best score: 1.7500: : 277iter [00:25, 12.32iter/s]Best score: 1.7500: : 277iter [00:25, 12.32iter/s]Best score: 1.7500: : 278iter [00:25, 12.32iter/s]Best score: 1.7500: : 279iter [00:25, 12.40iter/s]Best score: 1.4586: : 279iter [00:26, 12.40iter/s]Best score: 1.4586: : 280iter [00:26, 12.40iter/s]Best score: 1.4586: : 281iter [00:26, 12.23iter/s]Best score: 1.4586: : 281iter [00:26, 12.23iter/s]Best score: 1.4586: : 282iter [00:26, 12.23iter/s]Best score: 1.4586: : 283iter [00:26, 12.28iter/s]Best score: 1.4586: : 283iter [00:26, 12.28iter/s]Best score: 1.4586: : 284iter [00:26, 12.28iter/s]Best score: 1.4586: : 285iter [00:26, 12.34iter/s]Best score: 1.4586: : 285iter [00:26, 12.34iter/s]Best score: 1.4586: : 286iter [00:26, 12.34iter/s]Best score: 1.4586: : 287iter [00:26, 12.41iter/s]Best score: 1.4586: : 287iter [00:26, 12.41iter/s]Best score: 1.4586: : 288iter [00:26, 12.41iter/s]Best score: 1.4586: : 289iter [00:26, 12.46iter/s]Best score: 1.2866: : 289iter [00:26, 12.46iter/s]Best score: 1.2866: : 290iter [00:26, 12.46iter/s]Best score: 1.2866: : 291iter [00:26, 12.28iter/s]Best score: 1.2866: : 291iter [00:26, 12.28iter/s]Best score: 1.2866: : 292iter [00:27, 12.28iter/s]Best score: 1.2866: : 293iter [00:27, 12.38iter/s]Best score: 1.2866: : 293iter [00:27, 12.38iter/s]Best score: 1.2866: : 294iter [00:27, 12.38iter/s]Best score: 1.2866: : 295iter [00:27, 12.41iter/s]Best score: 1.2866: : 295iter [00:27, 12.41iter/s]Best score: 1.2866: : 296iter [00:27, 12.41iter/s]Best score: 1.2866: : 297iter [00:27, 12.43iter/s]Best score: 1.2866: : 297iter [00:27, 12.43iter/s]Best score: 1.2866: : 298iter [00:27, 12.43iter/s]Best score: 1.2866: : 299iter [00:27, 12.42iter/s]
[ITER 300] Best: 1.2866
[PARAMS] Current best parameters:
  fx: 589.7737
  fy: 587.6015
  px: 1024.5603
  py: 715.5700
  k1: -0.05184908
  k2: -0.03363880
  k3: 0.04231982
  k4: -0.01287905
  p1: -0.03676330
  p2: -0.00678321
  p3: 0.00861535
  p4: 0.02730053
  s1: -0.0056
  s2: -0.0144
  s3: 0.0229
  s4: -0.0375
  tilt_x: 0.0210
  tilt_y: -0.0684
  scale: 3.0143
  rotation: -0.4038
Best score: 1.2866: : 299iter [00:27, 12.42iter/s]Best score: 1.2866: : 300iter [00:27, 12.42iter/s]Best score: 1.2866: : 301iter [00:27,  7.99iter/s]Best score: 1.2866: : 301iter [00:28,  7.99iter/s]Best score: 1.2866: : 302iter [00:28,  7.99iter/s]Best score: 1.2866: : 303iter [00:28,  8.94iter/s]Best score: 1.2866: : 303iter [00:28,  8.94iter/s]Best score: 1.2866: : 304iter [00:28,  8.94iter/s]Best score: 1.2866: : 305iter [00:28,  9.79iter/s]Best score: 1.2866: : 305iter [00:28,  9.79iter/s]Best score: 1.2866: : 306iter [00:28,  9.79iter/s]Best score: 1.2866: : 307iter [00:28, 10.48iter/s]Best score: 1.2866: : 307iter [00:28, 10.48iter/s]Best score: 1.2866: : 308iter [00:28, 10.48iter/s]Best score: 1.2866: : 309iter [00:28, 11.04iter/s]Best score: 1.2866: : 309iter [00:28, 11.04iter/s]Best score: 1.2866: : 310iter [00:28, 11.04iter/s]Best score: 1.2866: : 311iter [00:28, 11.26iter/s]Best score: 1.2866: : 311iter [00:28, 11.26iter/s]Best score: 1.2866: : 312iter [00:28, 11.26iter/s]Best score: 1.2866: : 313iter [00:28, 11.64iter/s]Best score: 1.2866: : 313iter [00:29, 11.64iter/s]Best score: 1.2866: : 314iter [00:29, 11.64iter/s]Best score: 1.2866: : 315iter [00:29, 11.92iter/s]Best score: 1.2866: : 315iter [00:29, 11.92iter/s]Best score: 1.2866: : 316iter [00:29, 11.92iter/s]Best score: 1.2866: : 317iter [00:29, 12.10iter/s]Best score: 1.2866: : 317iter [00:29, 12.10iter/s]Best score: 1.2866: : 318iter [00:29, 12.10iter/s]Best score: 1.2866: : 319iter [00:29, 12.23iter/s]Best score: 1.2302: : 319iter [00:29, 12.23iter/s]Best score: 1.2302: : 320iter [00:29, 12.23iter/s]Best score: 1.2302: : 321iter [00:29, 12.11iter/s]Best score: 1.2302: : 321iter [00:29, 12.11iter/s]Best score: 1.2302: : 322iter [00:29, 12.11iter/s]Best score: 1.2302: : 323iter [00:29, 12.19iter/s]Best score: 1.2302: : 323iter [00:29, 12.19iter/s]Best score: 1.2302: : 324iter [00:29, 12.19iter/s]Best score: 1.2302: : 325iter [00:29, 12.31iter/s]Best score: 1.2302: : 325iter [00:30, 12.31iter/s]Best score: 1.2302: : 326iter [00:30, 12.31iter/s]Best score: 1.2302: : 327iter [00:30, 12.36iter/s]Best score: 1.2302: : 327iter [00:30, 12.36iter/s]Best score: 1.2302: : 328iter [00:30, 12.36iter/s]Best score: 1.2302: : 329iter [00:30, 12.43iter/s]Best score: 1.1596: : 329iter [00:30, 12.43iter/s]Best score: 1.1596: : 330iter [00:30, 12.43iter/s]Best score: 1.1596: : 331iter [00:30, 12.23iter/s]Best score: 1.1596: : 331iter [00:30, 12.23iter/s]Best score: 1.1596: : 332iter [00:30, 12.23iter/s]Best score: 1.1596: : 333iter [00:30, 12.33iter/s]Best score: 1.1596: : 333iter [00:30, 12.33iter/s]Best score: 1.1596: : 334iter [00:30, 12.33iter/s]Best score: 1.1596: : 335iter [00:30, 12.40iter/s]Best score: 1.1596: : 335iter [00:30, 12.40iter/s]Best score: 1.1596: : 336iter [00:30, 12.40iter/s]Best score: 1.1596: : 337iter [00:30, 12.44iter/s]Best score: 1.1596: : 337iter [00:30, 12.44iter/s]Best score: 1.1596: : 338iter [00:31, 12.44iter/s]Best score: 1.1596: : 339iter [00:31, 12.48iter/s]Best score: 0.9153: : 339iter [00:31, 12.48iter/s]Best score: 0.9153: : 340iter [00:31, 12.48iter/s]Best score: 0.9153: : 341iter [00:31, 12.28iter/s]Best score: 0.9153: : 341iter [00:31, 12.28iter/s]Best score: 0.9153: : 342iter [00:31, 12.28iter/s]Best score: 0.9153: : 343iter [00:31, 12.35iter/s]Best score: 0.9153: : 343iter [00:31, 12.35iter/s]Best score: 0.9153: : 344iter [00:31, 12.35iter/s]Best score: 0.9153: : 345iter [00:31, 12.40iter/s]Best score: 0.9153: : 345iter [00:31, 12.40iter/s]Best score: 0.9153: : 346iter [00:31, 12.40iter/s]Best score: 0.9153: : 347iter [00:31, 12.45iter/s]Best score: 0.9153: : 347iter [00:31, 12.45iter/s]Best score: 0.9153: : 348iter [00:31, 12.45iter/s]Best score: 0.9153: : 349iter [00:31, 12.45iter/s]
[ITER 350] Best: 0.7855
[PARAMS] Current best parameters:
  fx: 583.7397
  fy: 583.4877
  px: 1005.7779
  py: 726.3769
  k1: -0.04462730
  k2: -0.04389141
  k3: 0.04801269
  k4: -0.01336108
  p1: -0.03161278
  p2: -0.03149515
  p3: 0.00680442
  p4: 0.02459851
  s1: 0.0032
  s2: -0.0121
  s3: 0.0272
  s4: -0.0312
  tilt_x: 0.0670
  tilt_y: -0.0172
  scale: 3.0369
  rotation: -0.2054
Best score: 0.7855: : 349iter [00:31, 12.45iter/s]Best score: 0.7855: : 350iter [00:32, 12.45iter/s]Best score: 0.7855: : 351iter [00:32,  8.00iter/s]Best score: 0.7855: : 351iter [00:32,  8.00iter/s]Best score: 0.7855: : 352iter [00:32,  8.00iter/s]Best score: 0.7855: : 353iter [00:32,  8.97iter/s]Best score: 0.7855: : 353iter [00:32,  8.97iter/s]Best score: 0.7855: : 354iter [00:32,  8.97iter/s]Best score: 0.7855: : 355iter [00:32,  9.79iter/s]Best score: 0.7855: : 355iter [00:32,  9.79iter/s]Best score: 0.7855: : 356iter [00:32,  9.79iter/s]Best score: 0.7855: : 357iter [00:32, 10.46iter/s]Best score: 0.7855: : 357iter [00:32, 10.46iter/s]Best score: 0.7855: : 358iter [00:32, 10.46iter/s]Best score: 0.7855: : 359iter [00:32, 11.01iter/s]Best score: 0.7855: : 359iter [00:33, 11.01iter/s]Best score: 0.7855: : 360iter [00:33, 11.01iter/s]Best score: 0.7855: : 361iter [00:33, 11.26iter/s]Best score: 0.7855: : 361iter [00:33, 11.26iter/s]Best score: 0.7855: : 362iter [00:33, 11.26iter/s]Best score: 0.7855: : 363iter [00:33, 11.58iter/s]Best score: 0.7855: : 363iter [00:33, 11.58iter/s]Best score: 0.7855: : 364iter [00:33, 11.58iter/s]Best score: 0.7855: : 365iter [00:33, 11.83iter/s]Best score: 0.7855: : 365iter [00:33, 11.83iter/s]Best score: 0.7855: : 366iter [00:33, 11.83iter/s]Best score: 0.7855: : 367iter [00:33, 12.01iter/s]Best score: 0.7855: : 367iter [00:33, 12.01iter/s]Best score: 0.7855: : 368iter [00:33, 12.01iter/s]Best score: 0.7855: : 369iter [00:33, 12.16iter/s]Best score: 0.6601: : 369iter [00:33, 12.16iter/s]Best score: 0.6601: : 370iter [00:33, 12.16iter/s]Best score: 0.6601: : 371iter [00:33, 12.06iter/s]Best score: 0.6601: : 371iter [00:34, 12.06iter/s]Best score: 0.6601: : 372iter [00:34, 12.06iter/s]Best score: 0.6601: : 373iter [00:34, 12.20iter/s]Best score: 0.6601: : 373iter [00:34, 12.20iter/s]Best score: 0.6601: : 374iter [00:34, 12.20iter/s]Best score: 0.6601: : 375iter [00:34, 12.26iter/s]Best score: 0.6601: : 375iter [00:34, 12.26iter/s]Best score: 0.6601: : 376iter [00:34, 12.26iter/s]Best score: 0.6601: : 377iter [00:34, 12.29iter/s]Best score: 0.6601: : 377iter [00:34, 12.29iter/s]Best score: 0.6601: : 378iter [00:34, 12.29iter/s]Best score: 0.6601: : 379iter [00:34, 12.37iter/s]Best score: 0.4575: : 379iter [00:34, 12.37iter/s]Best score: 0.4575: : 380iter [00:34, 12.37iter/s]Best score: 0.4575: : 381iter [00:34, 12.12iter/s]Best score: 0.4575: : 381iter [00:34, 12.12iter/s]Best score: 0.4575: : 382iter [00:34, 12.12iter/s]Best score: 0.4575: : 383iter [00:34, 12.18iter/s]Best score: 0.4575: : 383iter [00:34, 12.18iter/s]Best score: 0.4575: : 384iter [00:35, 12.18iter/s]Best score: 0.4575: : 385iter [00:35, 12.28iter/s]Best score: 0.4575: : 385iter [00:35, 12.28iter/s]Best score: 0.4575: : 386iter [00:35, 12.28iter/s]Best score: 0.4575: : 387iter [00:35, 12.34iter/s]Best score: 0.4575: : 387iter [00:35, 12.34iter/s]Best score: 0.4575: : 388iter [00:35, 12.34iter/s]Best score: 0.4575: : 389iter [00:35, 12.37iter/s]Best score: 0.4575: : 389iter [00:35, 12.37iter/s]Best score: 0.4575: : 390iter [00:35, 12.37iter/s]Best score: 0.4575: : 391iter [00:35, 12.20iter/s]Best score: 0.4575: : 391iter [00:35, 12.20iter/s]Best score: 0.4575: : 392iter [00:35, 12.20iter/s]Best score: 0.4575: : 393iter [00:35, 12.30iter/s]Best score: 0.4575: : 393iter [00:35, 12.30iter/s]Best score: 0.4575: : 394iter [00:35, 12.30iter/s]Best score: 0.4575: : 395iter [00:35, 12.37iter/s]Best score: 0.4575: : 395iter [00:35, 12.37iter/s]Best score: 0.4575: : 396iter [00:36, 12.37iter/s]Best score: 0.4575: : 397iter [00:36, 12.41iter/s]Best score: 0.4575: : 397iter [00:36, 12.41iter/s]Best score: 0.4575: : 398iter [00:36, 12.41iter/s]Best score: 0.4575: : 399iter [00:36, 12.44iter/s]
[ITER 400] Best: 0.4575
[PARAMS] Current best parameters:
  fx: 583.8894
  fy: 583.8199
  px: 1006.3716
  py: 725.5061
  k1: -0.03205962
  k2: -0.04723816
  k3: 0.03995168
  k4: -0.00979793
  p1: -0.03049909
  p2: -0.02633846
  p3: 0.00073059
  p4: 0.02559472
  s1: 0.0071
  s2: -0.0170
  s3: 0.0347
  s4: -0.0313
  tilt_x: 0.0570
  tilt_y: -0.0119
  scale: 2.9978
  rotation: -0.2244
Best score: 0.4575: : 399iter [00:36, 12.44iter/s]Best score: 0.4575: : 400iter [00:36, 12.44iter/s]Best score: 0.4575: : 401iter [00:36,  8.00iter/s]Best score: 0.4575: : 401iter [00:36,  8.00iter/s]Best score: 0.4575: : 402iter [00:36,  8.00iter/s]Best score: 0.4575: : 403iter [00:36,  8.98iter/s]Best score: 0.4575: : 403iter [00:36,  8.98iter/s]Best score: 0.4575: : 404iter [00:36,  8.98iter/s]Best score: 0.4575: : 405iter [00:36,  9.79iter/s]Best score: 0.4575: : 405iter [00:37,  9.79iter/s]Best score: 0.4575: : 406iter [00:37,  9.79iter/s]Best score: 0.4575: : 407iter [00:37, 10.46iter/s]Best score: 0.4575: : 407iter [00:37, 10.46iter/s]Best score: 0.4575: : 408iter [00:37, 10.46iter/s]Best score: 0.4575: : 409iter [00:37, 10.98iter/s]Best score: 0.4575: : 409iter [00:37, 10.98iter/s]Best score: 0.4575: : 410iter [00:37, 10.98iter/s]Best score: 0.4575: : 411iter [00:37, 11.23iter/s]Best score: 0.4575: : 411iter [00:37, 11.23iter/s]Best score: 0.4575: : 412iter [00:37, 11.23iter/s]Best score: 0.4575: : 413iter [00:37, 11.59iter/s]Best score: 0.4575: : 413iter [00:37, 11.59iter/s]Best score: 0.4575: : 414iter [00:37, 11.59iter/s]Best score: 0.4575: : 415iter [00:37, 11.82iter/s]Best score: 0.4575: : 415iter [00:37, 11.82iter/s]Best score: 0.4575: : 416iter [00:37, 11.82iter/s]Best score: 0.4575: : 417iter [00:37, 12.01iter/s]Best score: 0.4575: : 417iter [00:38, 12.01iter/s]Best score: 0.4575: : 418iter [00:38, 12.01iter/s]Best score: 0.4575: : 419iter [00:38, 12.10iter/s]Best score: 0.4497: : 419iter [00:38, 12.10iter/s]Best score: 0.4497: : 420iter [00:38, 12.10iter/s]Best score: 0.4497: : 421iter [00:38, 12.01iter/s]Best score: 0.4497: : 421iter [00:38, 12.01iter/s]Best score: 0.4497: : 422iter [00:38, 12.01iter/s]Best score: 0.4497: : 423iter [00:38, 12.15iter/s]Best score: 0.4497: : 423iter [00:38, 12.15iter/s]Best score: 0.4497: : 424iter [00:38, 12.15iter/s]Best score: 0.4497: : 425iter [00:38, 12.25iter/s]Best score: 0.4497: : 425iter [00:38, 12.25iter/s]Best score: 0.4497: : 426iter [00:38, 12.25iter/s]Best score: 0.4497: : 427iter [00:38, 12.33iter/s]Best score: 0.4497: : 427iter [00:38, 12.33iter/s]Best score: 0.4497: : 428iter [00:38, 12.33iter/s]Best score: 0.4497: : 429iter [00:38, 12.37iter/s]Best score: 0.3953: : 429iter [00:39, 12.37iter/s]Best score: 0.3953: : 430iter [00:39, 12.37iter/s]Best score: 0.3953: : 431iter [00:39, 12.17iter/s]Best score: 0.3953: : 431iter [00:39, 12.17iter/s]Best score: 0.3953: : 432iter [00:39, 12.17iter/s]Best score: 0.3953: : 433iter [00:39, 12.21iter/s]Best score: 0.3953: : 433iter [00:39, 12.21iter/s]Best score: 0.3953: : 434iter [00:39, 12.21iter/s]Best score: 0.3953: : 435iter [00:39, 12.26iter/s]Best score: 0.3953: : 435iter [00:39, 12.26iter/s]Best score: 0.3953: : 436iter [00:39, 12.26iter/s]Best score: 0.3953: : 437iter [00:39, 12.32iter/s]Best score: 0.3953: : 437iter [00:39, 12.32iter/s]Best score: 0.3953: : 438iter [00:39, 12.32iter/s]Best score: 0.3953: : 439iter [00:39, 12.37iter/s]Best score: 0.3953: : 439iter [00:39, 12.37iter/s]Best score: 0.3953: : 440iter [00:39, 12.37iter/s]Best score: 0.3953: : 441iter [00:39, 12.18iter/s]Best score: 0.3953: : 441iter [00:39, 12.18iter/s]Best score: 0.3953: : 442iter [00:40, 12.18iter/s]Best score: 0.3953: : 443iter [00:40, 12.24iter/s]Best score: 0.3953: : 443iter [00:40, 12.24iter/s]Best score: 0.3953: : 444iter [00:40, 12.24iter/s]Best score: 0.3953: : 445iter [00:40, 12.31iter/s]Best score: 0.3953: : 445iter [00:40, 12.31iter/s]Best score: 0.3953: : 446iter [00:40, 12.31iter/s]Best score: 0.3953: : 447iter [00:40, 12.36iter/s]Best score: 0.3953: : 447iter [00:40, 12.36iter/s]Best score: 0.3953: : 448iter [00:40, 12.36iter/s]Best score: 0.3953: : 449iter [00:40, 12.36iter/s]
[ITER 450] Best: 0.3550
[PARAMS] Current best parameters:
  fx: 572.1878
  fy: 572.2352
  px: 1001.8080
  py: 723.2023
  k1: -0.01392625
  k2: -0.05471099
  k3: 0.04002384
  k4: -0.00900476
  p1: -0.03349374
  p2: -0.02982501
  p3: 0.00241998
  p4: 0.02542978
  s1: 0.0126
  s2: -0.0215
  s3: 0.0291
  s4: -0.0269
  tilt_x: 0.0524
  tilt_y: 0.0072
  scale: 2.9929
  rotation: -0.2709
Best score: 0.3550: : 449iter [00:40, 12.36iter/s]Best score: 0.3550: : 450iter [00:41, 12.36iter/s]Best score: 0.3550: : 451iter [00:41,  7.95iter/s]Best score: 0.3550: : 451iter [00:41,  7.95iter/s]Best score: 0.3550: : 452iter [00:41,  7.95iter/s]Best score: 0.3550: : 453iter [00:41,  8.92iter/s]Best score: 0.3550: : 453iter [00:41,  8.92iter/s]Best score: 0.3550: : 454iter [00:41,  8.92iter/s]Best score: 0.3550: : 455iter [00:41,  9.77iter/s]Best score: 0.3550: : 455iter [00:41,  9.77iter/s]Best score: 0.3550: : 456iter [00:41,  9.77iter/s]Best score: 0.3550: : 457iter [00:41, 10.46iter/s]Best score: 0.3550: : 457iter [00:41, 10.46iter/s]Best score: 0.3550: : 458iter [00:41, 10.46iter/s]Best score: 0.3550: : 459iter [00:41, 10.97iter/s]Best score: 0.3351: : 459iter [00:41, 10.97iter/s]Best score: 0.3351: : 460iter [00:41, 10.97iter/s]Best score: 0.3351: : 461iter [00:41, 11.21iter/s]Best score: 0.3351: : 461iter [00:41, 11.21iter/s]Best score: 0.3351: : 462iter [00:41, 11.21iter/s]Best score: 0.3351: : 463iter [00:41, 11.58iter/s]Best score: 0.3351: : 463iter [00:42, 11.58iter/s]Best score: 0.3351: : 464iter [00:42, 11.58iter/s]Best score: 0.3351: : 465iter [00:42, 11.86iter/s]Best score: 0.3351: : 465iter [00:42, 11.86iter/s]Best score: 0.3351: : 466iter [00:42, 11.86iter/s]Best score: 0.3351: : 467iter [00:42, 12.05iter/s]Best score: 0.3351: : 467iter [00:42, 12.05iter/s]Best score: 0.3351: : 468iter [00:42, 12.05iter/s]Best score: 0.3351: : 469iter [00:42, 12.21iter/s]Best score: 0.3291: : 469iter [00:42, 12.21iter/s]Best score: 0.3291: : 470iter [00:42, 12.21iter/s]Best score: 0.3291: : 471iter [00:42, 12.05iter/s]Best score: 0.3291: : 471iter [00:42, 12.05iter/s]Best score: 0.3291: : 472iter [00:42, 12.05iter/s]Best score: 0.3291: : 473iter [00:42, 12.20iter/s]Best score: 0.3291: : 473iter [00:42, 12.20iter/s]Best score: 0.3291: : 474iter [00:42, 12.20iter/s]Best score: 0.3291: : 475iter [00:42, 12.27iter/s]Best score: 0.3291: : 475iter [00:43, 12.27iter/s]Best score: 0.3291: : 476iter [00:43, 12.27iter/s]Best score: 0.3291: : 477iter [00:43, 12.33iter/s]Best score: 0.3291: : 477iter [00:43, 12.33iter/s]Best score: 0.3291: : 478iter [00:43, 12.33iter/s]Best score: 0.3291: : 479iter [00:43, 12.35iter/s]Best score: 0.3225: : 479iter [00:43, 12.35iter/s]Best score: 0.3225: : 480iter [00:43, 12.35iter/s]Best score: 0.3225: : 481iter [00:43, 12.16iter/s]Best score: 0.3225: : 481iter [00:43, 12.16iter/s]Best score: 0.3225: : 482iter [00:43, 12.16iter/s]Best score: 0.3225: : 483iter [00:43, 12.23iter/s]Best score: 0.3225: : 483iter [00:43, 12.23iter/s]Best score: 0.3225: : 484iter [00:43, 12.23iter/s]Best score: 0.3225: : 485iter [00:43, 12.30iter/s]Best score: 0.3225: : 485iter [00:43, 12.30iter/s]Best score: 0.3225: : 486iter [00:43, 12.30iter/s]Best score: 0.3225: : 487iter [00:43, 12.37iter/s]Best score: 0.3225: : 487iter [00:44, 12.37iter/s]Best score: 0.3225: : 488iter [00:44, 12.37iter/s]Best score: 0.3225: : 489iter [00:44, 12.41iter/s]Best score: 0.3212: : 489iter [00:44, 12.41iter/s]Best score: 0.3212: : 490iter [00:44, 12.41iter/s]Best score: 0.3212: : 491iter [00:44, 12.22iter/s]Best score: 0.3212: : 491iter [00:44, 12.22iter/s]Best score: 0.3212: : 492iter [00:44, 12.22iter/s]Best score: 0.3212: : 493iter [00:44, 12.30iter/s]Best score: 0.3212: : 493iter [00:44, 12.30iter/s]Best score: 0.3212: : 494iter [00:44, 12.30iter/s]Best score: 0.3212: : 495iter [00:44, 12.38iter/s]Best score: 0.3212: : 495iter [00:44, 12.38iter/s]Best score: 0.3212: : 496iter [00:44, 12.38iter/s]Best score: 0.3212: : 497iter [00:44, 12.41iter/s]Best score: 0.3212: : 497iter [00:44, 12.41iter/s]Best score: 0.3212: : 498iter [00:44, 12.41iter/s]Best score: 0.3212: : 499iter [00:44, 12.45iter/s]
[ITER 500] Best: 0.3096
[PARAMS] Current best parameters:
  fx: 570.2243
  fy: 569.3970
  px: 1009.3602
  py: 718.7241
  k1: -0.00613172
  k2: -0.06838762
  k3: 0.05216137
  k4: -0.01268082
  p1: -0.03492132
  p2: -0.02650687
  p3: 0.01221770
  p4: 0.01967935
  s1: 0.0111
  s2: -0.0206
  s3: 0.0198
  s4: -0.0238
  tilt_x: 0.0303
  tilt_y: -0.0253
  scale: 2.9878
  rotation: -0.2997
Best score: 0.3096: : 499iter [00:44, 12.45iter/s]Best score: 0.3096: : 500iter [00:45, 12.45iter/s]Best score: 0.3096: : 501iter [00:45,  7.97iter/s]Best score: 0.3096: : 501iter [00:45,  7.97iter/s]Best score: 0.3096: : 502iter [00:45,  7.97iter/s]Best score: 0.3096: : 503iter [00:45,  8.93iter/s]Best score: 0.3096: : 503iter [00:45,  8.93iter/s]Best score: 0.3096: : 504iter [00:45,  8.93iter/s]Best score: 0.3096: : 505iter [00:45,  9.72iter/s]Best score: 0.3096: : 505iter [00:45,  9.72iter/s]Best score: 0.3096: : 506iter [00:45,  9.72iter/s]Best score: 0.3096: : 507iter [00:45, 10.41iter/s]Best score: 0.3096: : 507iter [00:45, 10.41iter/s]Best score: 0.3096: : 508iter [00:46, 10.41iter/s]Best score: 0.3096: : 509iter [00:46, 10.93iter/s]Best score: 0.3075: : 509iter [00:46, 10.93iter/s]Best score: 0.3075: : 510iter [00:46, 10.93iter/s]Best score: 0.3075: : 511iter [00:46, 11.13iter/s]Best score: 0.3075: : 511iter [00:46, 11.13iter/s]Best score: 0.3075: : 512iter [00:46, 11.13iter/s]Best score: 0.3075: : 513iter [00:46, 11.50iter/s]Best score: 0.3075: : 513iter [00:46, 11.50iter/s]Best score: 0.3075: : 514iter [00:46, 11.50iter/s]Best score: 0.3075: : 515iter [00:46, 11.79iter/s]Best score: 0.3075: : 515iter [00:46, 11.79iter/s]Best score: 0.3075: : 516iter [00:46, 11.79iter/s]Best score: 0.3075: : 517iter [00:46, 11.99iter/s]Best score: 0.3075: : 517iter [00:46, 11.99iter/s]Best score: 0.3075: : 518iter [00:46, 11.99iter/s]Best score: 0.3075: : 519iter [00:46, 12.12iter/s]Best score: 0.3063: : 519iter [00:46, 12.12iter/s]Best score: 0.3063: : 520iter [00:46, 12.12iter/s]Best score: 0.3063: : 521iter [00:46, 12.01iter/s]Best score: 0.3063: : 521iter [00:47, 12.01iter/s]Best score: 0.3063: : 522iter [00:47, 12.01iter/s]Best score: 0.3063: : 523iter [00:47, 12.15iter/s]Best score: 0.3063: : 523iter [00:47, 12.15iter/s]Best score: 0.3063: : 524iter [00:47, 12.15iter/s]Best score: 0.3063: : 525iter [00:47, 12.24iter/s]Best score: 0.3063: : 525iter [00:47, 12.24iter/s]Best score: 0.3063: : 526iter [00:47, 12.24iter/s]Best score: 0.3063: : 527iter [00:47, 12.30iter/s]Best score: 0.3063: : 527iter [00:47, 12.30iter/s]Best score: 0.3063: : 528iter [00:47, 12.30iter/s]Best score: 0.3063: : 529iter [00:47, 12.36iter/s]Best score: 0.3006: : 529iter [00:47, 12.36iter/s]Best score: 0.3006: : 530iter [00:47, 12.36iter/s]Best score: 0.3006: : 531iter [00:47, 12.14iter/s]Best score: 0.3006: : 531iter [00:47, 12.14iter/s]Best score: 0.3006: : 532iter [00:47, 12.14iter/s]Best score: 0.3006: : 533iter [00:47, 12.21iter/s]Best score: 0.3006: : 533iter [00:48, 12.21iter/s]Best score: 0.3006: : 534iter [00:48, 12.21iter/s]Best score: 0.3006: : 535iter [00:48, 12.27iter/s]Best score: 0.3006: : 535iter [00:48, 12.27iter/s]Best score: 0.3006: : 536iter [00:48, 12.27iter/s]Best score: 0.3006: : 537iter [00:48, 12.33iter/s]Best score: 0.3006: : 537iter [00:48, 12.33iter/s]Best score: 0.3006: : 538iter [00:48, 12.33iter/s]Best score: 0.3006: : 539iter [00:48, 12.36iter/s]Best score: 0.2961: : 539iter [00:48, 12.36iter/s]Best score: 0.2961: : 540iter [00:48, 12.36iter/s]Best score: 0.2961: : 541iter [00:48, 12.16iter/s]Best score: 0.2961: : 541iter [00:48, 12.16iter/s]Best score: 0.2961: : 542iter [00:48, 12.16iter/s]Best score: 0.2961: : 543iter [00:48, 12.25iter/s]Best score: 0.2961: : 543iter [00:48, 12.25iter/s]Best score: 0.2961: : 544iter [00:48, 12.25iter/s]Best score: 0.2961: : 545iter [00:48, 12.33iter/s]Best score: 0.2961: : 545iter [00:49, 12.33iter/s]Best score: 0.2961: : 546iter [00:49, 12.33iter/s]Best score: 0.2961: : 547iter [00:49, 12.37iter/s]Best score: 0.2961: : 547iter [00:49, 12.37iter/s]Best score: 0.2961: : 548iter [00:49, 12.37iter/s]Best score: 0.2961: : 549iter [00:49, 12.40iter/s]
[ITER 550] Best: 0.2945
[PARAMS] Current best parameters:
  fx: 568.8646
  fy: 568.4057
  px: 1005.4833
  py: 718.4864
  k1: -0.00796320
  k2: -0.06308060
  k3: 0.04782939
  k4: -0.01143684
  p1: -0.03664326
  p2: -0.03110342
  p3: 0.00956007
  p4: 0.02105173
  s1: 0.0131
  s2: -0.0216
  s3: 0.0214
  s4: -0.0225
  tilt_x: 0.0333
  tilt_y: -0.0155
  scale: 2.9917
  rotation: -0.2695
Best score: 0.2945: : 549iter [00:49, 12.40iter/s]Best score: 0.2945: : 550iter [00:49, 12.40iter/s]Best score: 0.2945: : 551iter [00:49,  7.97iter/s]Best score: 0.2945: : 551iter [00:49,  7.97iter/s]Best score: 0.2945: : 552iter [00:49,  7.97iter/s]Best score: 0.2945: : 553iter [00:49,  8.90iter/s]Best score: 0.2945: : 553iter [00:49,  8.90iter/s]Best score: 0.2945: : 554iter [00:50,  8.90iter/s]Best score: 0.2945: : 555iter [00:50,  9.73iter/s]Best score: 0.2945: : 555iter [00:50,  9.73iter/s]Best score: 0.2945: : 556iter [00:50,  9.73iter/s]Best score: 0.2945: : 557iter [00:50, 10.41iter/s]Best score: 0.2945: : 557iter [00:50, 10.41iter/s]Best score: 0.2945: : 558iter [00:50, 10.41iter/s]Best score: 0.2945: : 559iter [00:50, 10.95iter/s]Best score: 0.2945: : 559iter [00:50, 10.95iter/s]Best score: 0.2945: : 560iter [00:50, 10.95iter/s]Best score: 0.2945: : 561iter [00:50, 11.17iter/s]Best score: 0.2945: : 561iter [00:50, 11.17iter/s]Best score: 0.2945: : 562iter [00:50, 11.17iter/s]Best score: 0.2945: : 563iter [00:50, 11.49iter/s]Best score: 0.2945: : 563iter [00:50, 11.49iter/s]Best score: 0.2945: : 564iter [00:50, 11.49iter/s]Best score: 0.2945: : 565iter [00:50, 11.74iter/s]Best score: 0.2945: : 565iter [00:50, 11.74iter/s]Best score: 0.2945: : 566iter [00:51, 11.74iter/s]Best score: 0.2945: : 567iter [00:51, 11.91iter/s]Best score: 0.2945: : 567iter [00:51, 11.91iter/s]Best score: 0.2945: : 568iter [00:51, 11.91iter/s]Best score: 0.2945: : 569iter [00:51, 12.06iter/s]Best score: 0.2910: : 569iter [00:51, 12.06iter/s]Best score: 0.2910: : 570iter [00:51, 12.06iter/s]Best score: 0.2910: : 571iter [00:51, 11.97iter/s]Best score: 0.2910: : 571iter [00:51, 11.97iter/s]Best score: 0.2910: : 572iter [00:51, 11.97iter/s]Best score: 0.2910: : 573iter [00:51, 12.13iter/s]Best score: 0.2910: : 573iter [00:51, 12.13iter/s]Best score: 0.2910: : 574iter [00:51, 12.13iter/s]Best score: 0.2910: : 575iter [00:51, 12.23iter/s]Best score: 0.2910: : 575iter [00:51, 12.23iter/s]Best score: 0.2910: : 576iter [00:51, 12.23iter/s]Best score: 0.2910: : 577iter [00:51, 12.30iter/s]Best score: 0.2910: : 577iter [00:51, 12.30iter/s]Best score: 0.2910: : 578iter [00:51, 12.30iter/s]Best score: 0.2910: : 579iter [00:51, 12.34iter/s]Best score: 0.2869: : 579iter [00:52, 12.34iter/s]Best score: 0.2869: : 580iter [00:52, 12.34iter/s]Best score: 0.2869: : 581iter [00:52, 12.16iter/s]Best score: 0.2869: : 581iter [00:52, 12.16iter/s]Best score: 0.2869: : 582iter [00:52, 12.16iter/s]Best score: 0.2869: : 583iter [00:52, 12.23iter/s]Best score: 0.2869: : 583iter [00:52, 12.23iter/s]Best score: 0.2869: : 584iter [00:52, 12.23iter/s]Best score: 0.2869: : 585iter [00:52, 12.30iter/s]Best score: 0.2869: : 585iter [00:52, 12.30iter/s]Best score: 0.2869: : 586iter [00:52, 12.30iter/s]Best score: 0.2869: : 587iter [00:52, 12.20iter/s]Best score: 0.2869: : 587iter [00:52, 12.20iter/s]Best score: 0.2869: : 588iter [00:52, 12.20iter/s]Best score: 0.2869: : 589iter [00:52, 12.20iter/s]Best score: 0.2817: : 589iter [00:52, 12.20iter/s]Best score: 0.2817: : 590iter [00:52, 12.20iter/s]Best score: 0.2817: : 591iter [00:52, 12.08iter/s]Best score: 0.2817: : 591iter [00:53, 12.08iter/s]Best score: 0.2817: : 592iter [00:53, 12.08iter/s]Best score: 0.2817: : 593iter [00:53, 12.12iter/s]Best score: 0.2817: : 593iter [00:53, 12.12iter/s]Best score: 0.2817: : 594iter [00:53, 12.12iter/s]Best score: 0.2817: : 595iter [00:53, 12.17iter/s]Best score: 0.2817: : 595iter [00:53, 12.17iter/s]Best score: 0.2817: : 596iter [00:53, 12.17iter/s]Best score: 0.2817: : 597iter [00:53, 12.26iter/s]Best score: 0.2817: : 597iter [00:53, 12.26iter/s]Best score: 0.2817: : 598iter [00:53, 12.26iter/s]Best score: 0.2817: : 599iter [00:53, 12.32iter/s]
[ITER 600] Best: 0.2769
[PARAMS] Current best parameters:
  fx: 571.8874
  fy: 571.2783
  px: 1007.2905
  py: 718.8949
  k1: -0.01090536
  k2: -0.06119502
  k3: 0.04588075
  k4: -0.01079156
  p1: -0.03501998
  p2: -0.03044878
  p3: 0.00984445
  p4: 0.02092711
  s1: 0.0150
  s2: -0.0226
  s3: 0.0190
  s4: -0.0221
  tilt_x: 0.0324
  tilt_y: -0.0231
  scale: 2.9900
  rotation: -0.2575
Best score: 0.2769: : 599iter [00:53, 12.32iter/s]Best score: 0.2769: : 600iter [00:54, 12.32iter/s]Best score: 0.2769: : 601iter [00:54,  7.95iter/s]Best score: 0.2769: : 601iter [00:54,  7.95iter/s]Best score: 0.2769: : 602iter [00:54,  7.95iter/s]Best score: 0.2769: : 603iter [00:54,  8.90iter/s]Best score: 0.2769: : 603iter [00:54,  8.90iter/s]Best score: 0.2769: : 604iter [00:54,  8.90iter/s]Best score: 0.2769: : 605iter [00:54,  9.68iter/s]Best score: 0.2769: : 605iter [00:54,  9.68iter/s]Best score: 0.2769: : 606iter [00:54,  9.68iter/s]Best score: 0.2769: : 607iter [00:54, 10.37iter/s]Best score: 0.2769: : 607iter [00:54, 10.37iter/s]Best score: 0.2769: : 608iter [00:54, 10.37iter/s]Best score: 0.2769: : 609iter [00:54, 10.91iter/s]Best score: 0.2735: : 609iter [00:54, 10.91iter/s]Best score: 0.2735: : 610iter [00:54, 10.91iter/s]Best score: 0.2735: : 611iter [00:54, 11.16iter/s]Best score: 0.2735: : 611iter [00:54, 11.16iter/s]Best score: 0.2735: : 612iter [00:55, 11.16iter/s]Best score: 0.2735: : 613iter [00:55, 11.47iter/s]Best score: 0.2735: : 613iter [00:55, 11.47iter/s]Best score: 0.2735: : 614iter [00:55, 11.47iter/s]Best score: 0.2735: : 615iter [00:55, 11.75iter/s]Best score: 0.2735: : 615iter [00:55, 11.75iter/s]Best score: 0.2735: : 616iter [00:55, 11.75iter/s]Best score: 0.2735: : 617iter [00:55, 11.96iter/s]Best score: 0.2735: : 617iter [00:55, 11.96iter/s]Best score: 0.2735: : 618iter [00:55, 11.96iter/s]Best score: 0.2735: : 619iter [00:55, 12.11iter/s]Best score: 0.2735: : 619iter [00:55, 12.11iter/s]Best score: 0.2735: : 620iter [00:55, 12.11iter/s]Best score: 0.2735: : 621iter [00:55, 12.02iter/s]Best score: 0.2735: : 621iter [00:55, 12.02iter/s]Best score: 0.2735: : 622iter [00:55, 12.02iter/s]Best score: 0.2735: : 623iter [00:55, 12.16iter/s]Best score: 0.2735: : 623iter [00:55, 12.16iter/s]Best score: 0.2735: : 624iter [00:56, 12.16iter/s]Best score: 0.2735: : 625iter [00:56, 12.24iter/s]Best score: 0.2735: : 625iter [00:56, 12.24iter/s]Best score: 0.2735: : 626iter [00:56, 12.24iter/s]Best score: 0.2735: : 627iter [00:56, 12.32iter/s]Best score: 0.2735: : 627iter [00:56, 12.32iter/s]Best score: 0.2735: : 628iter [00:56, 12.32iter/s]Best score: 0.2735: : 629iter [00:56, 12.37iter/s]Best score: 0.2694: : 629iter [00:56, 12.37iter/s]Best score: 0.2694: : 630iter [00:56, 12.37iter/s]Best score: 0.2694: : 631iter [00:56, 12.18iter/s]Best score: 0.2694: : 631iter [00:56, 12.18iter/s]Best score: 0.2694: : 632iter [00:56, 12.18iter/s]Best score: 0.2694: : 633iter [00:56, 12.27iter/s]Best score: 0.2694: : 633iter [00:56, 12.27iter/s]Best score: 0.2694: : 634iter [00:56, 12.27iter/s]Best score: 0.2694: : 635iter [00:56, 12.34iter/s]Best score: 0.2694: : 635iter [00:56, 12.34iter/s]Best score: 0.2694: : 636iter [00:57, 12.34iter/s]Best score: 0.2694: : 637iter [00:57, 12.39iter/s]Best score: 0.2694: : 637iter [00:57, 12.39iter/s]Best score: 0.2694: : 638iter [00:57, 12.39iter/s]Best score: 0.2694: : 639iter [00:57, 12.42iter/s]Best score: 0.2662: : 639iter [00:57, 12.42iter/s]Best score: 0.2662: : 640iter [00:57, 12.42iter/s]Best score: 0.2662: : 641iter [00:57, 12.22iter/s]Best score: 0.2662: : 641iter [00:57, 12.22iter/s]Best score: 0.2662: : 642iter [00:57, 12.22iter/s]Best score: 0.2662: : 643iter [00:57, 12.30iter/s]Best score: 0.2662: : 643iter [00:57, 12.30iter/s]Best score: 0.2662: : 644iter [00:57, 12.30iter/s]Best score: 0.2662: : 645iter [00:57, 12.35iter/s]Best score: 0.2662: : 645iter [00:57, 12.35iter/s]Best score: 0.2662: : 646iter [00:57, 12.35iter/s]Best score: 0.2662: : 647iter [00:57, 10.29iter/s]Best score: 0.2662: : 647iter [00:58, 10.29iter/s]Best score: 0.2662: : 648iter [00:58, 10.29iter/s]Best score: 0.2662: : 649iter [00:58, 10.86iter/s]
[ITER 650] Best: 0.2662
[PARAMS] Current best parameters:
  fx: 577.4946
  fy: 577.0853
  px: 1007.7271
  py: 720.9778
  k1: -0.02428642
  k2: -0.04774621
  k3: 0.03821810
  k4: -0.00914110
  p1: -0.03203341
  p2: -0.03082761
  p3: 0.00671802
  p4: 0.02218401
  s1: 0.0199
  s2: -0.0246
  s3: 0.0197
  s4: -0.0217
  tilt_x: 0.0370
  tilt_y: -0.0256
  scale: 2.9935
  rotation: -0.2791
Best score: 0.2662: : 649iter [00:58, 10.86iter/s]Best score: 0.2662: : 650iter [00:58, 10.86iter/s]Best score: 0.2662: : 651iter [00:58,  7.54iter/s]Best score: 0.2662: : 651iter [00:58,  7.54iter/s]Best score: 0.2662: : 652iter [00:58,  7.54iter/s]Best score: 0.2662: : 653iter [00:58,  8.55iter/s]Best score: 0.2662: : 653iter [00:58,  8.55iter/s]Best score: 0.2662: : 654iter [00:58,  8.55iter/s]Best score: 0.2662: : 655iter [00:58,  9.44iter/s]Best score: 0.2662: : 655iter [00:58,  9.44iter/s]Best score: 0.2662: : 656iter [00:59,  9.44iter/s]Best score: 0.2662: : 657iter [00:59, 10.20iter/s]Best score: 0.2662: : 657iter [00:59, 10.20iter/s]Best score: 0.2662: : 658iter [00:59, 10.20iter/s]Best score: 0.2662: : 659iter [00:59, 10.79iter/s]Best score: 0.2648: : 659iter [00:59, 10.79iter/s]Best score: 0.2648: : 660iter [00:59, 10.79iter/s]Best score: 0.2648: : 661iter [00:59, 11.06iter/s]Best score: 0.2648: : 661iter [00:59, 11.06iter/s]Best score: 0.2648: : 662iter [00:59, 11.06iter/s]Best score: 0.2648: : 663iter [00:59, 11.45iter/s]Best score: 0.2648: : 663iter [00:59, 11.45iter/s]Best score: 0.2648: : 664iter [00:59, 11.45iter/s]Best score: 0.2648: : 665iter [00:59, 11.68iter/s]Best score: 0.2648: : 665iter [00:59, 11.68iter/s]Best score: 0.2648: : 666iter [00:59, 11.68iter/s]Best score: 0.2648: : 667iter [00:59, 11.91iter/s]Best score: 0.2648: : 667iter [00:59, 11.91iter/s]Best score: 0.2648: : 668iter [00:59, 11.91iter/s]Best score: 0.2648: : 669iter [00:59, 12.08iter/s]Best score: 0.2617: : 669iter [01:00, 12.08iter/s]Best score: 0.2617: : 670iter [01:00, 12.08iter/s]Best score: 0.2617: : 671iter [01:00, 11.99iter/s]Best score: 0.2617: : 671iter [01:00, 11.99iter/s]Best score: 0.2617: : 672iter [01:00, 11.99iter/s]Best score: 0.2617: : 673iter [01:00, 12.11iter/s]Best score: 0.2617: : 673iter [01:00, 12.11iter/s]Best score: 0.2617: : 674iter [01:00, 12.11iter/s]Best score: 0.2617: : 675iter [01:00, 12.21iter/s]Best score: 0.2617: : 675iter [01:00, 12.21iter/s]Best score: 0.2617: : 676iter [01:00, 12.21iter/s]Best score: 0.2617: : 677iter [01:00, 12.29iter/s]Best score: 0.2617: : 677iter [01:00, 12.29iter/s]Best score: 0.2617: : 678iter [01:00, 12.29iter/s]Best score: 0.2617: : 679iter [01:00, 12.34iter/s]Best score: 0.2605: : 679iter [01:00, 12.34iter/s]Best score: 0.2605: : 680iter [01:00, 12.34iter/s]Best score: 0.2605: : 681iter [01:00, 12.16iter/s]Best score: 0.2605: : 681iter [01:01, 12.16iter/s]Best score: 0.2605: : 682iter [01:01, 12.16iter/s]Best score: 0.2605: : 683iter [01:01, 12.21iter/s]Best score: 0.2605: : 683iter [01:01, 12.21iter/s]Best score: 0.2605: : 684iter [01:01, 12.21iter/s]Best score: 0.2605: : 685iter [01:01, 12.29iter/s]Best score: 0.2605: : 685iter [01:01, 12.29iter/s]Best score: 0.2605: : 686iter [01:01, 12.29iter/s]Best score: 0.2605: : 687iter [01:01, 12.36iter/s]Best score: 0.2605: : 687iter [01:01, 12.36iter/s]Best score: 0.2605: : 688iter [01:01, 12.36iter/s]Best score: 0.2605: : 689iter [01:01, 12.40iter/s]Best score: 0.2601: : 689iter [01:01, 12.40iter/s]Best score: 0.2601: : 690iter [01:01, 12.40iter/s]Best score: 0.2601: : 691iter [01:01, 12.13iter/s]Best score: 0.2601: : 691iter [01:01, 12.13iter/s]Best score: 0.2601: : 692iter [01:01, 12.13iter/s]Best score: 0.2601: : 693iter [01:01, 12.24iter/s]Best score: 0.2601: : 693iter [01:02, 12.24iter/s]Best score: 0.2601: : 694iter [01:02, 12.24iter/s]Best score: 0.2601: : 695iter [01:02, 12.30iter/s]Best score: 0.2601: : 695iter [01:02, 12.30iter/s]Best score: 0.2601: : 696iter [01:02, 12.30iter/s]Best score: 0.2601: : 697iter [01:02, 12.31iter/s]Best score: 0.2601: : 697iter [01:02, 12.31iter/s]Best score: 0.2601: : 698iter [01:02, 12.31iter/s]Best score: 0.2601: : 699iter [01:02, 12.35iter/s]
[ITER 700] Best: 0.2580
[PARAMS] Current best parameters:
  fx: 577.3847
  fy: 576.8692
  px: 1008.0073
  py: 720.2002
  k1: -0.02535513
  k2: -0.04351692
  k3: 0.03416466
  k4: -0.00799373
  p1: -0.03263446
  p2: -0.02963973
  p3: 0.00569803
  p4: 0.01969954
  s1: 0.0191
  s2: -0.0210
  s3: 0.0207
  s4: -0.0192
  tilt_x: 0.0341
  tilt_y: -0.0244
  scale: 2.9931
  rotation: -0.2709
Best score: 0.2580: : 699iter [01:02, 12.35iter/s]Best score: 0.2580: : 700iter [01:02, 12.35iter/s]Best score: 0.2580: : 701iter [01:02,  7.97iter/s]Best score: 0.2580: : 701iter [01:02,  7.97iter/s]Best score: 0.2580: : 702iter [01:03,  7.97iter/s]Best score: 0.2580: : 703iter [01:03,  8.94iter/s]Best score: 0.2580: : 703iter [01:03,  8.94iter/s]Best score: 0.2580: : 704iter [01:03,  8.94iter/s]Best score: 0.2580: : 705iter [01:03,  9.78iter/s]Best score: 0.2580: : 705iter [01:03,  9.78iter/s]Best score: 0.2580: : 706iter [01:03,  9.78iter/s]Best score: 0.2580: : 707iter [01:03, 10.45iter/s]Best score: 0.2580: : 707iter [01:03, 10.45iter/s]Best score: 0.2580: : 708iter [01:03, 10.45iter/s]Best score: 0.2580: : 709iter [01:03, 10.98iter/s]Best score: 0.2558: : 709iter [01:03, 10.98iter/s]Best score: 0.2558: : 710iter [01:03, 10.98iter/s]Best score: 0.2558: : 711iter [01:03, 11.21iter/s]Best score: 0.2558: : 711iter [01:03, 11.21iter/s]Best score: 0.2558: : 712iter [01:03, 11.21iter/s]Best score: 0.2558: : 713iter [01:03, 11.57iter/s]Best score: 0.2558: : 713iter [01:03, 11.57iter/s]Best score: 0.2558: : 714iter [01:04, 11.57iter/s]Best score: 0.2558: : 715iter [01:04, 11.79iter/s]Best score: 0.2558: : 715iter [01:04, 11.79iter/s]Best score: 0.2558: : 716iter [01:04, 11.79iter/s]Best score: 0.2558: : 717iter [01:04, 11.99iter/s]Best score: 0.2558: : 717iter [01:04, 11.99iter/s]Best score: 0.2558: : 718iter [01:04, 11.99iter/s]Best score: 0.2558: : 719iter [01:04, 12.08iter/s]Best score: 0.2558: : 719iter [01:04, 12.08iter/s]Best score: 0.2558: : 720iter [01:04, 12.08iter/s]Best score: 0.2558: : 721iter [01:04, 11.98iter/s]Best score: 0.2558: : 721iter [01:04, 11.98iter/s]Best score: 0.2558: : 722iter [01:04, 11.98iter/s]Best score: 0.2558: : 723iter [01:04, 12.08iter/s]Best score: 0.2558: : 723iter [01:04, 12.08iter/s]Best score: 0.2558: : 724iter [01:04, 12.08iter/s]Best score: 0.2558: : 725iter [01:04, 12.19iter/s]Best score: 0.2558: : 725iter [01:04, 12.19iter/s]Best score: 0.2558: : 726iter [01:05, 12.19iter/s]Best score: 0.2558: : 727iter [01:05, 12.27iter/s]Best score: 0.2558: : 727iter [01:05, 12.27iter/s]Best score: 0.2558: : 728iter [01:05, 12.27iter/s]Best score: 0.2558: : 729iter [01:05, 12.29iter/s]Best score: 0.2492: : 729iter [01:05, 12.29iter/s]Best score: 0.2492: : 730iter [01:05, 12.29iter/s]Best score: 0.2492: : 731iter [01:05, 12.13iter/s]Best score: 0.2492: : 731iter [01:05, 12.13iter/s]Best score: 0.2492: : 732iter [01:05, 12.13iter/s]Best score: 0.2492: : 733iter [01:05, 12.20iter/s]Best score: 0.2492: : 733iter [01:05, 12.20iter/s]Best score: 0.2492: : 734iter [01:05, 12.20iter/s]Best score: 0.2492: : 735iter [01:05, 12.30iter/s]Best score: 0.2492: : 735iter [01:05, 12.30iter/s]Best score: 0.2492: : 736iter [01:05, 12.30iter/s]Best score: 0.2492: : 737iter [01:05, 12.26iter/s]Best score: 0.2492: : 737iter [01:05, 12.26iter/s]Best score: 0.2492: : 738iter [01:05, 12.26iter/s]Best score: 0.2492: : 739iter [01:05, 12.28iter/s]Best score: 0.2441: : 739iter [01:06, 12.28iter/s]Best score: 0.2441: : 740iter [01:06, 12.28iter/s]Best score: 0.2441: : 741iter [01:06, 12.15iter/s]Best score: 0.2441: : 741iter [01:06, 12.15iter/s]Best score: 0.2441: : 742iter [01:06, 12.15iter/s]Best score: 0.2441: : 743iter [01:06, 12.25iter/s]Best score: 0.2441: : 743iter [01:06, 12.25iter/s]Best score: 0.2441: : 744iter [01:06, 12.25iter/s]Best score: 0.2441: : 745iter [01:06, 12.27iter/s]Best score: 0.2441: : 745iter [01:06, 12.27iter/s]Best score: 0.2441: : 746iter [01:06, 12.27iter/s]Best score: 0.2441: : 747iter [01:06, 12.34iter/s]Best score: 0.2441: : 747iter [01:06, 12.34iter/s]Best score: 0.2441: : 748iter [01:06, 12.34iter/s]Best score: 0.2441: : 749iter [01:06, 12.36iter/s]
[ITER 750] Best: 0.2441
[PARAMS] Current best parameters:
  fx: 576.9973
  fy: 576.3466
  px: 1009.3214
  py: 721.9871
  k1: -0.04125866
  k2: -0.01450474
  k3: 0.01564741
  k4: -0.00392491
  p1: -0.02950396
  p2: -0.02460050
  p3: 0.00133132
  p4: 0.01430010
  s1: 0.0192
  s2: -0.0147
  s3: 0.0229
  s4: -0.0131
  tilt_x: 0.0376
  tilt_y: -0.0215
  scale: 3.0068
  rotation: -0.2754
Best score: 0.2441: : 749iter [01:06, 12.36iter/s]Best score: 0.2441: : 750iter [01:07, 12.36iter/s]Best score: 0.2441: : 751iter [01:07,  7.97iter/s]Best score: 0.2441: : 751iter [01:07,  7.97iter/s]Best score: 0.2441: : 752iter [01:07,  7.97iter/s]Best score: 0.2441: : 753iter [01:07,  8.94iter/s]Best score: 0.2441: : 753iter [01:07,  8.94iter/s]Best score: 0.2441: : 754iter [01:07,  8.94iter/s]Best score: 0.2441: : 755iter [01:07,  9.74iter/s]Best score: 0.2441: : 755iter [01:07,  9.74iter/s]Best score: 0.2441: : 756iter [01:07,  9.74iter/s]Best score: 0.2441: : 757iter [01:07, 10.42iter/s]Best score: 0.2441: : 757iter [01:07, 10.42iter/s]Best score: 0.2441: : 758iter [01:07, 10.42iter/s]Best score: 0.2441: : 759iter [01:07, 10.97iter/s]Best score: 0.2431: : 759iter [01:07, 10.97iter/s]Best score: 0.2431: : 760iter [01:08, 10.97iter/s]Best score: 0.2431: : 761iter [01:08, 11.19iter/s]Best score: 0.2431: : 761iter [01:08, 11.19iter/s]Best score: 0.2431: : 762iter [01:08, 11.19iter/s]Best score: 0.2431: : 763iter [01:08, 11.52iter/s]Best score: 0.2431: : 763iter [01:08, 11.52iter/s]Best score: 0.2431: : 764iter [01:08, 11.52iter/s]Best score: 0.2431: : 765iter [01:08, 11.74iter/s]Best score: 0.2431: : 765iter [01:08, 11.74iter/s]Best score: 0.2431: : 766iter [01:08, 11.74iter/s]Best score: 0.2431: : 767iter [01:08, 11.87iter/s]Best score: 0.2431: : 767iter [01:08, 11.87iter/s]Best score: 0.2431: : 768iter [01:08, 11.87iter/s]Best score: 0.2431: : 769iter [01:08, 12.06iter/s]Best score: 0.2405: : 769iter [01:08, 12.06iter/s]Best score: 0.2405: : 770iter [01:08, 12.06iter/s]Best score: 0.2405: : 771iter [01:08, 11.98iter/s]Best score: 0.2405: : 771iter [01:08, 11.98iter/s]Best score: 0.2405: : 772iter [01:09, 11.98iter/s]Best score: 0.2405: : 773iter [01:09, 12.14iter/s]Best score: 0.2405: : 773iter [01:09, 12.14iter/s]Best score: 0.2405: : 774iter [01:09, 12.14iter/s]Best score: 0.2405: : 775iter [01:09, 12.21iter/s]Best score: 0.2405: : 775iter [01:09, 12.21iter/s]Best score: 0.2405: : 776iter [01:09, 12.21iter/s]Best score: 0.2405: : 777iter [01:09, 12.22iter/s]Best score: 0.2405: : 777iter [01:09, 12.22iter/s]Best score: 0.2405: : 778iter [01:09, 12.22iter/s]Best score: 0.2405: : 779iter [01:09, 12.31iter/s]Best score: 0.2399: : 779iter [01:09, 12.31iter/s]Best score: 0.2399: : 780iter [01:09, 12.31iter/s]Best score: 0.2399: : 781iter [01:09, 12.15iter/s]Best score: 0.2399: : 781iter [01:09, 12.15iter/s]Best score: 0.2399: : 782iter [01:09, 12.15iter/s]Best score: 0.2399: : 783iter [01:09, 12.26iter/s]Best score: 0.2399: : 783iter [01:09, 12.26iter/s]Best score: 0.2399: : 784iter [01:10, 12.26iter/s]Best score: 0.2399: : 785iter [01:10, 12.26iter/s]Best score: 0.2399: : 785iter [01:10, 12.26iter/s]Best score: 0.2399: : 786iter [01:10, 12.26iter/s]Best score: 0.2399: : 787iter [01:10, 12.30iter/s]Best score: 0.2399: : 787iter [01:10, 12.30iter/s]Best score: 0.2399: : 788iter [01:10, 12.30iter/s]Best score: 0.2399: : 789iter [01:10, 12.35iter/s]Best score: 0.2391: : 789iter [01:10, 12.35iter/s]Best score: 0.2391: : 790iter [01:10, 12.35iter/s]Best score: 0.2391: : 791iter [01:10, 12.17iter/s]Best score: 0.2391: : 791iter [01:10, 12.17iter/s]Best score: 0.2391: : 792iter [01:10, 12.17iter/s]Best score: 0.2391: : 793iter [01:10, 12.28iter/s]Best score: 0.2391: : 793iter [01:10, 12.28iter/s]Best score: 0.2391: : 794iter [01:10, 12.28iter/s]Best score: 0.2391: : 795iter [01:10, 12.34iter/s]Best score: 0.2391: : 795iter [01:10, 12.34iter/s]Best score: 0.2391: : 796iter [01:11, 12.34iter/s]Best score: 0.2391: : 797iter [01:11, 12.37iter/s]Best score: 0.2391: : 797iter [01:11, 12.37iter/s]Best score: 0.2391: : 798iter [01:11, 12.37iter/s]Best score: 0.2391: : 799iter [01:11, 12.41iter/s]
[ITER 800] Best: 0.2391
[PARAMS] Current best parameters:
  fx: 577.0052
  fy: 576.3110
  px: 1009.4760
  py: 721.5157
  k1: -0.04675592
  k2: -0.00352040
  k3: 0.00798865
  k4: -0.00211845
  p1: -0.02963457
  p2: -0.02341697
  p3: 0.00472712
  p4: 0.01223424
  s1: 0.0155
  s2: -0.0129
  s3: 0.0193
  s4: -0.0113
  tilt_x: 0.0350
  tilt_y: -0.0193
  scale: 3.0102
  rotation: -0.2623
Best score: 0.2391: : 799iter [01:11, 12.41iter/s]Best score: 0.2391: : 800iter [01:11, 12.41iter/s]Best score: 0.2391: : 801iter [01:11,  7.96iter/s]Best score: 0.2391: : 801iter [01:11,  7.96iter/s]Best score: 0.2391: : 802iter [01:11,  7.96iter/s]Best score: 0.2391: : 803iter [01:11,  8.91iter/s]Best score: 0.2391: : 803iter [01:11,  8.91iter/s]Best score: 0.2391: : 804iter [01:11,  8.91iter/s]Best score: 0.2391: : 805iter [01:11,  9.73iter/s]Best score: 0.2391: : 805iter [01:12,  9.73iter/s]Best score: 0.2391: : 806iter [01:12,  9.73iter/s]Best score: 0.2391: : 807iter [01:12, 10.43iter/s]Best score: 0.2391: : 807iter [01:12, 10.43iter/s]Best score: 0.2391: : 808iter [01:12, 10.43iter/s]Best score: 0.2391: : 809iter [01:12, 10.97iter/s]Best score: 0.2381: : 809iter [01:12, 10.97iter/s]Best score: 0.2381: : 810iter [01:12, 10.97iter/s]Best score: 0.2381: : 811iter [01:12, 11.20iter/s]Best score: 0.2381: : 811iter [01:12, 11.20iter/s]Best score: 0.2381: : 812iter [01:12, 11.20iter/s]Best score: 0.2381: : 813iter [01:12, 11.56iter/s]Best score: 0.2381: : 813iter [01:12, 11.56iter/s]Best score: 0.2381: : 814iter [01:12, 11.56iter/s]Best score: 0.2381: : 815iter [01:12, 11.83iter/s]Best score: 0.2381: : 815iter [01:12, 11.83iter/s]Best score: 0.2381: : 816iter [01:12, 11.83iter/s]Best score: 0.2381: : 817iter [01:12, 11.98iter/s]Best score: 0.2381: : 817iter [01:12, 11.98iter/s]Best score: 0.2381: : 818iter [01:13, 11.98iter/s]Best score: 0.2381: : 819iter [01:13, 12.03iter/s]Best score: 0.2368: : 819iter [01:13, 12.03iter/s]Best score: 0.2368: : 820iter [01:13, 12.03iter/s]Best score: 0.2368: : 821iter [01:13, 11.93iter/s]Best score: 0.2368: : 821iter [01:13, 11.93iter/s]Best score: 0.2368: : 822iter [01:13, 11.93iter/s]Best score: 0.2368: : 823iter [01:13, 12.05iter/s]Best score: 0.2368: : 823iter [01:13, 12.05iter/s]Best score: 0.2368: : 824iter [01:13, 12.05iter/s]Best score: 0.2368: : 825iter [01:13, 12.19iter/s]Best score: 0.2368: : 825iter [01:13, 12.19iter/s]Best score: 0.2368: : 826iter [01:13, 12.19iter/s]Best score: 0.2368: : 827iter [01:13, 12.28iter/s]Best score: 0.2368: : 827iter [01:13, 12.28iter/s]Best score: 0.2368: : 828iter [01:13, 12.28iter/s]Best score: 0.2368: : 829iter [01:13, 12.34iter/s]Best score: 0.2368: : 829iter [01:13, 12.34iter/s]Best score: 0.2368: : 830iter [01:14, 12.34iter/s]Best score: 0.2368: : 831iter [01:14, 12.19iter/s]Best score: 0.2368: : 831iter [01:14, 12.19iter/s]Best score: 0.2368: : 832iter [01:14, 12.19iter/s]Best score: 0.2368: : 833iter [01:14, 12.28iter/s]Best score: 0.2368: : 833iter [01:14, 12.28iter/s]Best score: 0.2368: : 834iter [01:14, 12.28iter/s]Best score: 0.2368: : 835iter [01:14, 12.28iter/s]Best score: 0.2368: : 835iter [01:14, 12.28iter/s]Best score: 0.2368: : 836iter [01:14, 12.28iter/s]Best score: 0.2368: : 837iter [01:14, 12.35iter/s]Best score: 0.2368: : 837iter [01:14, 12.35iter/s]Best score: 0.2368: : 838iter [01:14, 12.35iter/s]Best score: 0.2368: : 839iter [01:14, 12.37iter/s]Best score: 0.2365: : 839iter [01:14, 12.37iter/s]Best score: 0.2365: : 840iter [01:14, 12.37iter/s]Best score: 0.2365: : 841iter [01:14, 12.21iter/s]Best score: 0.2365: : 841iter [01:14, 12.21iter/s]Best score: 0.2365: : 842iter [01:15, 12.21iter/s]Best score: 0.2365: : 843iter [01:15, 12.29iter/s]Best score: 0.2365: : 843iter [01:15, 12.29iter/s]Best score: 0.2365: : 844iter [01:15, 12.29iter/s]Best score: 0.2365: : 845iter [01:15, 12.35iter/s]Best score: 0.2365: : 845iter [01:15, 12.35iter/s]Best score: 0.2365: : 846iter [01:15, 12.35iter/s]Best score: 0.2365: : 847iter [01:15, 12.40iter/s]Best score: 0.2365: : 847iter [01:15, 12.40iter/s]Best score: 0.2365: : 848iter [01:15, 12.40iter/s]Best score: 0.2365: : 849iter [01:15, 12.44iter/s]
[ITER 850] Best: 0.2348
[PARAMS] Current best parameters:
  fx: 574.9611
  fy: 574.3590
  px: 1008.1643
  py: 720.2019
  k1: -0.04995021
  k2: 0.00472624
  k3: 0.00320277
  k4: -0.00123229
  p1: -0.03040893
  p2: -0.02614235
  p3: 0.01216435
  p4: 0.01149719
  s1: 0.0089
  s2: -0.0123
  s3: 0.0119
  s4: -0.0111
  tilt_x: 0.0297
  tilt_y: -0.0184
  scale: 3.0147
  rotation: -0.2692
Best score: 0.2348: : 849iter [01:15, 12.44iter/s]Best score: 0.2348: : 850iter [01:15, 12.44iter/s]Best score: 0.2348: : 851iter [01:15,  8.01iter/s]Best score: 0.2348: : 851iter [01:16,  8.01iter/s]Best score: 0.2348: : 852iter [01:16,  8.01iter/s]Best score: 0.2348: : 853iter [01:16,  8.98iter/s]Best score: 0.2348: : 853iter [01:16,  8.98iter/s]Best score: 0.2348: : 854iter [01:16,  8.98iter/s]Best score: 0.2348: : 855iter [01:16,  9.79iter/s]Best score: 0.2348: : 855iter [01:16,  9.79iter/s]Best score: 0.2348: : 856iter [01:16,  9.79iter/s]Best score: 0.2348: : 857iter [01:16, 10.48iter/s]Best score: 0.2348: : 857iter [01:16, 10.48iter/s]Best score: 0.2348: : 858iter [01:16, 10.48iter/s]Best score: 0.2348: : 859iter [01:16, 11.01iter/s]Best score: 0.2335: : 859iter [01:16, 11.01iter/s]Best score: 0.2335: : 860iter [01:16, 11.01iter/s]Best score: 0.2335: : 861iter [01:16, 11.24iter/s]Best score: 0.2335: : 861iter [01:16, 11.24iter/s]Best score: 0.2335: : 862iter [01:16, 11.24iter/s]Best score: 0.2335: : 863iter [01:16, 11.59iter/s]Best score: 0.2335: : 863iter [01:17, 11.59iter/s]Best score: 0.2335: : 864iter [01:17, 11.59iter/s]Best score: 0.2335: : 865iter [01:17, 11.85iter/s]Best score: 0.2335: : 865iter [01:17, 11.85iter/s]Best score: 0.2335: : 866iter [01:17, 11.85iter/s]Best score: 0.2335: : 867iter [01:17, 12.00iter/s]Best score: 0.2335: : 867iter [01:17, 12.00iter/s]Best score: 0.2335: : 868iter [01:17, 12.00iter/s]Best score: 0.2335: : 869iter [01:17, 12.15iter/s]Best score: 0.2332: : 869iter [01:17, 12.15iter/s]Best score: 0.2332: : 870iter [01:17, 12.15iter/s]Best score: 0.2332: : 871iter [01:17, 12.06iter/s]Best score: 0.2332: : 871iter [01:17, 12.06iter/s]Best score: 0.2332: : 872iter [01:17, 12.06iter/s]Best score: 0.2332: : 873iter [01:17, 12.15iter/s]Best score: 0.2332: : 873iter [01:17, 12.15iter/s]Best score: 0.2332: : 874iter [01:17, 12.15iter/s]Best score: 0.2332: : 875iter [01:17, 12.23iter/s]Best score: 0.2332: : 875iter [01:17, 12.23iter/s]Best score: 0.2332: : 876iter [01:18, 12.23iter/s]Best score: 0.2332: : 877iter [01:18, 12.32iter/s]Best score: 0.2332: : 877iter [01:18, 12.32iter/s]Best score: 0.2332: : 878iter [01:18, 12.32iter/s]Best score: 0.2332: : 879iter [01:18, 12.39iter/s]Best score: 0.2320: : 879iter [01:18, 12.39iter/s]Best score: 0.2320: : 880iter [01:18, 12.39iter/s]Best score: 0.2320: : 881iter [01:18, 12.21iter/s]Best score: 0.2320: : 881iter [01:18, 12.21iter/s]Best score: 0.2320: : 882iter [01:18, 12.21iter/s]Best score: 0.2320: : 883iter [01:18, 12.31iter/s]Best score: 0.2320: : 883iter [01:18, 12.31iter/s]Best score: 0.2320: : 884iter [01:18, 12.31iter/s]Best score: 0.2320: : 885iter [01:18, 12.38iter/s]Best score: 0.2320: : 885iter [01:18, 12.38iter/s]Best score: 0.2320: : 886iter [01:18, 12.38iter/s]Best score: 0.2320: : 887iter [01:18, 12.43iter/s]Best score: 0.2320: : 887iter [01:18, 12.43iter/s]Best score: 0.2320: : 888iter [01:19, 12.43iter/s]Best score: 0.2320: : 889iter [01:19, 12.48iter/s]Best score: 0.2315: : 889iter [01:19, 12.48iter/s]Best score: 0.2315: : 890iter [01:19, 12.48iter/s]Best score: 0.2315: : 891iter [01:19, 12.28iter/s]Best score: 0.2315: : 891iter [01:19, 12.28iter/s]Best score: 0.2315: : 892iter [01:19, 12.28iter/s]Best score: 0.2315: : 893iter [01:19, 12.30iter/s]Best score: 0.2315: : 893iter [01:19, 12.30iter/s]Best score: 0.2315: : 894iter [01:19, 12.30iter/s]Best score: 0.2315: : 895iter [01:19, 12.32iter/s]Best score: 0.2315: : 895iter [01:19, 12.32iter/s]Best score: 0.2315: : 896iter [01:19, 12.32iter/s]Best score: 0.2315: : 897iter [01:19, 12.37iter/s]Best score: 0.2315: : 897iter [01:19, 12.37iter/s]Best score: 0.2315: : 898iter [01:19, 12.37iter/s]Best score: 0.2315: : 899iter [01:19, 12.38iter/s]
[ITER 900] Best: 0.2309
[PARAMS] Current best parameters:
  fx: 577.5212
  fy: 576.9400
  px: 1009.1144
  py: 719.5170
  k1: -0.06061351
  k2: 0.01968405
  k3: -0.00622777
  k4: 0.00087551
  p1: -0.02961654
  p2: -0.02612990
  p3: 0.01280592
  p4: 0.01127508
  s1: 0.0092
  s2: -0.0119
  s3: 0.0088
  s4: -0.0102
  tilt_x: 0.0248
  tilt_y: -0.0232
  scale: 3.0193
  rotation: -0.2568
Best score: 0.2309: : 899iter [01:19, 12.38iter/s]Best score: 0.2309: : 900iter [01:20, 12.38iter/s]Best score: 0.2309: : 901iter [01:20,  7.99iter/s]Best score: 0.2309: : 901iter [01:20,  7.99iter/s]Best score: 0.2309: : 902iter [01:20,  7.99iter/s]Best score: 0.2309: : 903iter [01:20,  8.98iter/s]Best score: 0.2309: : 903iter [01:20,  8.98iter/s]Best score: 0.2309: : 904iter [01:20,  8.98iter/s]Best score: 0.2309: : 905iter [01:20,  9.81iter/s]Best score: 0.2309: : 905iter [01:20,  9.81iter/s]Best score: 0.2309: : 906iter [01:20,  9.81iter/s]Best score: 0.2309: : 907iter [01:20, 10.51iter/s]Best score: 0.2309: : 907iter [01:20, 10.51iter/s]Best score: 0.2309: : 908iter [01:20, 10.51iter/s]Best score: 0.2309: : 909iter [01:20, 11.07iter/s]Best score: 0.2309: : 909iter [01:21, 11.07iter/s]Best score: 0.2309: : 910iter [01:21, 11.07iter/s]Best score: 0.2309: : 911iter [01:21, 11.30iter/s]Best score: 0.2309: : 911iter [01:21, 11.30iter/s]Best score: 0.2309: : 912iter [01:21, 11.30iter/s]Best score: 0.2309: : 913iter [01:21, 11.62iter/s]Best score: 0.2309: : 913iter [01:21, 11.62iter/s]Best score: 0.2309: : 914iter [01:21, 11.62iter/s]Best score: 0.2309: : 915iter [01:21, 11.91iter/s]Best score: 0.2309: : 915iter [01:21, 11.91iter/s]Best score: 0.2309: : 916iter [01:21, 11.91iter/s]Best score: 0.2309: : 917iter [01:21, 12.11iter/s]Best score: 0.2309: : 917iter [01:21, 12.11iter/s]Best score: 0.2309: : 918iter [01:21, 12.11iter/s]Best score: 0.2309: : 919iter [01:21, 12.25iter/s]Best score: 0.2309: : 919iter [01:21, 12.25iter/s]Best score: 0.2309: : 920iter [01:21, 12.25iter/s]Best score: 0.2309: : 921iter [01:21, 12.16iter/s]Best score: 0.2309: : 921iter [01:21, 12.16iter/s]Best score: 0.2309: : 922iter [01:22, 12.16iter/s]Best score: 0.2309: : 923iter [01:22, 12.31iter/s]Best score: 0.2309: : 923iter [01:22, 12.31iter/s]Best score: 0.2309: : 924iter [01:22, 12.31iter/s]Best score: 0.2309: : 925iter [01:22, 12.41iter/s]Best score: 0.2309: : 925iter [01:22, 12.41iter/s]Best score: 0.2309: : 926iter [01:22, 12.41iter/s]Best score: 0.2309: : 927iter [01:22, 12.48iter/s]Best score: 0.2309: : 927iter [01:22, 12.48iter/s]Best score: 0.2309: : 928iter [01:22, 12.48iter/s]Best score: 0.2309: : 929iter [01:22, 12.53iter/s]Best score: 0.2305: : 929iter [01:22, 12.53iter/s]Best score: 0.2305: : 930iter [01:22, 12.53iter/s]Best score: 0.2305: : 931iter [01:22, 12.34iter/s]Best score: 0.2305: : 931iter [01:22, 12.34iter/s]Best score: 0.2305: : 932iter [01:22, 12.34iter/s]Best score: 0.2305: : 933iter [01:22, 12.40iter/s]Best score: 0.2305: : 933iter [01:22, 12.40iter/s]Best score: 0.2305: : 934iter [01:23, 12.40iter/s]Best score: 0.2305: : 935iter [01:23, 12.41iter/s]Best score: 0.2305: : 935iter [01:23, 12.41iter/s]Best score: 0.2305: : 936iter [01:23, 12.41iter/s]Best score: 0.2305: : 937iter [01:23, 12.47iter/s]Best score: 0.2305: : 937iter [01:23, 12.47iter/s]Best score: 0.2305: : 938iter [01:23, 12.47iter/s]Best score: 0.2305: : 939iter [01:23, 12.52iter/s]Best score: 0.2305: : 939iter [01:23, 12.52iter/s]Best score: 0.2305: : 940iter [01:23, 12.52iter/s]Best score: 0.2305: : 941iter [01:23, 12.33iter/s]Best score: 0.2305: : 941iter [01:23, 12.33iter/s]Best score: 0.2305: : 942iter [01:23, 12.33iter/s]Best score: 0.2305: : 943iter [01:23, 12.41iter/s]Best score: 0.2305: : 943iter [01:23, 12.41iter/s]Best score: 0.2305: : 944iter [01:23, 12.41iter/s]Best score: 0.2305: : 945iter [01:23, 12.48iter/s]Best score: 0.2305: : 945iter [01:23, 12.48iter/s]Best score: 0.2305: : 946iter [01:23, 12.48iter/s]Best score: 0.2305: : 947iter [01:23, 12.52iter/s]Best score: 0.2305: : 947iter [01:24, 12.52iter/s]Best score: 0.2305: : 948iter [01:24, 12.52iter/s]Best score: 0.2305: : 949iter [01:24, 12.55iter/s]
[ITER 950] Best: 0.2305
[PARAMS] Current best parameters:
  fx: 581.8707
  fy: 581.2469
  px: 1010.3629
  py: 719.5114
  k1: -0.06994931
  k2: 0.02809939
  k3: -0.01079905
  k4: 0.00185036
  p1: -0.02886855
  p2: -0.02558713
  p3: 0.01131370
  p4: 0.01120738
  s1: 0.0117
  s2: -0.0121
  s3: 0.0100
  s4: -0.0108
  tilt_x: 0.0231
  tilt_y: -0.0284
  scale: 3.0226
  rotation: -0.2592
Best score: 0.2305: : 949iter [01:24, 12.55iter/s]Best score: 0.2305: : 950iter [01:24, 12.55iter/s]Best score: 0.2305: : 951iter [01:24,  8.03iter/s]Best score: 0.2305: : 951iter [01:24,  8.03iter/s]Best score: 0.2305: : 952iter [01:24,  8.03iter/s]Best score: 0.2305: : 953iter [01:24,  9.01iter/s]Best score: 0.2305: : 953iter [01:24,  9.01iter/s]Best score: 0.2305: : 954iter [01:24,  9.01iter/s]Best score: 0.2305: : 955iter [01:24,  9.83iter/s]Best score: 0.2305: : 955iter [01:25,  9.83iter/s]Best score: 0.2305: : 956iter [01:25,  9.83iter/s]Best score: 0.2305: : 957iter [01:25, 10.51iter/s]Best score: 0.2305: : 957iter [01:25, 10.51iter/s]Best score: 0.2305: : 958iter [01:25, 10.51iter/s]Best score: 0.2305: : 959iter [01:25, 11.03iter/s]Best score: 0.2304: : 959iter [01:25, 11.03iter/s]Best score: 0.2304: : 960iter [01:25, 11.03iter/s]Best score: 0.2304: : 961iter [01:25, 11.24iter/s]Best score: 0.2304: : 961iter [01:25, 11.24iter/s]Best score: 0.2304: : 962iter [01:25, 11.24iter/s]Best score: 0.2304: : 963iter [01:25, 11.56iter/s]Best score: 0.2304: : 963iter [01:25, 11.56iter/s]Best score: 0.2304: : 964iter [01:25, 11.56iter/s]Best score: 0.2304: : 965iter [01:25, 11.80iter/s]Best score: 0.2304: : 965iter [01:25, 11.80iter/s]Best score: 0.2304: : 966iter [01:25, 11.80iter/s]Best score: 0.2304: : 967iter [01:25, 12.03iter/s]Best score: 0.2304: : 967iter [01:25, 12.03iter/s]Best score: 0.2304: : 968iter [01:26, 12.03iter/s]Best score: 0.2304: : 969iter [01:26, 12.15iter/s]Best score: 0.2301: : 969iter [01:26, 12.15iter/s]Best score: 0.2301: : 970iter [01:26, 12.15iter/s]Best score: 0.2301: : 971iter [01:26, 12.08iter/s]Best score: 0.2301: : 971iter [01:26, 12.08iter/s]Best score: 0.2301: : 972iter [01:26, 12.08iter/s]Best score: 0.2301: : 973iter [01:26, 12.20iter/s]Best score: 0.2301: : 973iter [01:26, 12.20iter/s]Best score: 0.2301: : 974iter [01:26, 12.20iter/s]Best score: 0.2301: : 975iter [01:26, 12.32iter/s]Best score: 0.2301: : 975iter [01:26, 12.32iter/s]Best score: 0.2301: : 976iter [01:26, 12.32iter/s]Best score: 0.2301: : 977iter [01:26, 12.42iter/s]Best score: 0.2301: : 977iter [01:26, 12.42iter/s]Best score: 0.2301: : 978iter [01:26, 12.42iter/s]Best score: 0.2301: : 979iter [01:26, 12.46iter/s]Best score: 0.2300: : 979iter [01:26, 12.46iter/s]Best score: 0.2300: : 980iter [01:27, 12.46iter/s]Best score: 0.2300: : 981iter [01:27, 12.30iter/s]Best score: 0.2300: : 981iter [01:27, 12.30iter/s]Best score: 0.2300: : 982iter [01:27, 12.30iter/s]Best score: 0.2300: : 983iter [01:27, 12.39iter/s]Best score: 0.2300: : 983iter [01:27, 12.39iter/s]Best score: 0.2300: : 984iter [01:27, 12.39iter/s]Best score: 0.2300: : 985iter [01:27, 12.42iter/s]Best score: 0.2300: : 985iter [01:27, 12.42iter/s]Best score: 0.2300: : 986iter [01:27, 12.42iter/s]Best score: 0.2300: : 987iter [01:27, 12.47iter/s]Best score: 0.2300: : 987iter [01:27, 12.47iter/s]Best score: 0.2300: : 988iter [01:27, 12.47iter/s]Best score: 0.2300: : 989iter [01:27, 12.50iter/s]Best score: 0.2300: : 989iter [01:27, 12.50iter/s]Best score: 0.2300: : 990iter [01:27, 12.50iter/s]Best score: 0.2300: : 991iter [01:27, 12.33iter/s]Best score: 0.2300: : 991iter [01:27, 12.33iter/s]Best score: 0.2300: : 992iter [01:28, 12.33iter/s]Best score: 0.2300: : 993iter [01:28, 12.42iter/s]Best score: 0.2300: : 993iter [01:28, 12.42iter/s]Best score: 0.2300: : 994iter [01:28, 12.42iter/s]Best score: 0.2300: : 995iter [01:28, 12.43iter/s]Best score: 0.2300: : 995iter [01:28, 12.43iter/s]Best score: 0.2300: : 996iter [01:28, 12.43iter/s]Best score: 0.2300: : 997iter [01:28, 12.48iter/s]Best score: 0.2300: : 997iter [01:28, 12.48iter/s]Best score: 0.2300: : 998iter [01:28, 12.48iter/s]Best score: 0.2300: : 999iter [01:28, 12.52iter/s]
[ITER 1000] Best: 0.2300
[PARAMS] Current best parameters:
  fx: 581.8269
  fy: 581.1874
  px: 1009.4373
  py: 719.6471
  k1: -0.06880031
  k2: 0.02673448
  k3: -0.01032309
  k4: 0.00182807
  p1: -0.02949800
  p2: -0.02547324
  p3: 0.00871940
  p4: 0.01228947
  s1: 0.0128
  s2: -0.0127
  s3: 0.0130
  s4: -0.0115
  tilt_x: 0.0251
  tilt_y: -0.0233
  scale: 3.0206
  rotation: -0.2538
Best score: 0.2300: : 999iter [01:28, 12.52iter/s]Best score: 0.2300: : 1000iter [01:28, 12.52iter/s]Best score: 0.2300: : 1001iter [01:28,  8.05iter/s]Best score: 0.2300: : 1001iter [01:29,  8.05iter/s]Best score: 0.2300: : 1002iter [01:29,  8.05iter/s]Best score: 0.2300: : 1003iter [01:29,  9.04iter/s]Best score: 0.2300: : 1003iter [01:29,  9.04iter/s]Best score: 0.2300: : 1004iter [01:29,  9.04iter/s]Best score: 0.2300: : 1005iter [01:29,  9.87iter/s]Best score: 0.2300: : 1005iter [01:29,  9.87iter/s]Best score: 0.2300: : 1006iter [01:29,  9.87iter/s]Best score: 0.2300: : 1007iter [01:29, 10.51iter/s]Best score: 0.2300: : 1007iter [01:29, 10.51iter/s]Best score: 0.2300: : 1008iter [01:29, 10.51iter/s]Best score: 0.2300: : 1009iter [01:29, 11.07iter/s]Best score: 0.2300: : 1009iter [01:29, 11.07iter/s]Best score: 0.2300: : 1010iter [01:29, 11.07iter/s]Best score: 0.2300: : 1011iter [01:29, 11.31iter/s]Best score: 0.2300: : 1011iter [01:29, 11.31iter/s]Best score: 0.2300: : 1012iter [01:29, 11.31iter/s]Best score: 0.2300: : 1013iter [01:29, 11.66iter/s]Best score: 0.2300: : 1013iter [01:29, 11.66iter/s]Best score: 0.2300: : 1014iter [01:30, 11.66iter/s]Best score: 0.2300: : 1015iter [01:30, 11.93iter/s]Best score: 0.2300: : 1015iter [01:30, 11.93iter/s]Best score: 0.2300: : 1016iter [01:30, 11.93iter/s]Best score: 0.2300: : 1017iter [01:30, 12.08iter/s]Best score: 0.2300: : 1017iter [01:30, 12.08iter/s]Best score: 0.2300: : 1018iter [01:30, 12.08iter/s]Best score: 0.2300: : 1019iter [01:30, 12.23iter/s]Best score: 0.2299: : 1019iter [01:30, 12.23iter/s]Best score: 0.2299: : 1020iter [01:30, 12.23iter/s]Best score: 0.2299: : 1021iter [01:30, 12.14iter/s]Best score: 0.2299: : 1021iter [01:30, 12.14iter/s]Best score: 0.2299: : 1022iter [01:30, 12.14iter/s]Best score: 0.2299: : 1023iter [01:30, 12.23iter/s]Best score: 0.2299: : 1023iter [01:30, 12.23iter/s]Best score: 0.2299: : 1024iter [01:30, 12.23iter/s]Best score: 0.2299: : 1025iter [01:30, 12.24iter/s]Best score: 0.2299: : 1025iter [01:30, 12.24iter/s]Best score: 0.2299: : 1026iter [01:31, 12.24iter/s]Best score: 0.2299: : 1027iter [01:31, 12.30iter/s]Best score: 0.2299: : 1027iter [01:31, 12.30iter/s]Best score: 0.2299: : 1028iter [01:31, 12.30iter/s]Best score: 0.2299: : 1029iter [01:31, 12.37iter/s]Best score: 0.2299: : 1029iter [01:31, 12.37iter/s]Best score: 0.2299: : 1030iter [01:31, 12.37iter/s]Best score: 0.2299: : 1031iter [01:31, 12.22iter/s]Best score: 0.2299: : 1031iter [01:31, 12.22iter/s]Best score: 0.2299: : 1032iter [01:31, 12.22iter/s]Best score: 0.2299: : 1033iter [01:31, 12.34iter/s]Best score: 0.2299: : 1033iter [01:31, 12.34iter/s]Best score: 0.2299: : 1034iter [01:31, 12.34iter/s]Best score: 0.2299: : 1035iter [01:31, 12.42iter/s]Best score: 0.2299: : 1035iter [01:31, 12.42iter/s]Best score: 0.2299: : 1036iter [01:31, 12.42iter/s]Best score: 0.2299: : 1037iter [01:31, 12.40iter/s]Best score: 0.2299: : 1037iter [01:31, 12.40iter/s]Best score: 0.2299: : 1038iter [01:31, 12.40iter/s]Best score: 0.2299: : 1039iter [01:31, 12.41iter/s]Best score: 0.2295: : 1039iter [01:32, 12.41iter/s]Best score: 0.2295: : 1040iter [01:32, 12.41iter/s]Best score: 0.2295: : 1041iter [01:32, 12.26iter/s]Best score: 0.2295: : 1041iter [01:32, 12.26iter/s]Best score: 0.2295: : 1042iter [01:32, 12.26iter/s]Best score: 0.2295: : 1043iter [01:32, 12.33iter/s]Best score: 0.2295: : 1043iter [01:32, 12.33iter/s]Best score: 0.2295: : 1044iter [01:32, 12.33iter/s]Best score: 0.2295: : 1045iter [01:32, 12.36iter/s]Best score: 0.2295: : 1045iter [01:32, 12.36iter/s]Best score: 0.2295: : 1046iter [01:32, 12.36iter/s]Best score: 0.2295: : 1047iter [01:32, 12.45iter/s]Best score: 0.2295: : 1047iter [01:32, 12.45iter/s]Best score: 0.2295: : 1048iter [01:32, 12.45iter/s]Best score: 0.2295: : 1049iter [01:32, 12.50iter/s]
[ITER 1050] Best: 0.2295
[PARAMS] Current best parameters:
  fx: 583.6369
  fy: 583.0293
  px: 1009.5364
  py: 718.8132
  k1: -0.07434938
  k2: 0.03327558
  k3: -0.01429784
  k4: 0.00273559
  p1: -0.02952421
  p2: -0.02656603
  p3: 0.00969762
  p4: 0.01345755
  s1: 0.0133
  s2: -0.0141
  s3: 0.0111
  s4: -0.0125
  tilt_x: 0.0205
  tilt_y: -0.0259
  scale: 3.0230
  rotation: -0.2504
Best score: 0.2295: : 1049iter [01:32, 12.50iter/s]Best score: 0.2295: : 1050iter [01:33, 12.50iter/s]Best score: 0.2295: : 1051iter [01:33,  7.99iter/s]Best score: 0.2295: : 1051iter [01:33,  7.99iter/s]Best score: 0.2295: : 1052iter [01:33,  7.99iter/s]Best score: 0.2295: : 1053iter [01:33,  8.97iter/s]Best score: 0.2295: : 1053iter [01:33,  8.97iter/s]Best score: 0.2295: : 1054iter [01:33,  8.97iter/s]Best score: 0.2295: : 1055iter [01:33,  9.82iter/s]Best score: 0.2295: : 1055iter [01:33,  9.82iter/s]Best score: 0.2295: : 1056iter [01:33,  9.82iter/s]Best score: 0.2295: : 1057iter [01:33, 10.47iter/s]Best score: 0.2295: : 1057iter [01:33, 10.47iter/s]Best score: 0.2295: : 1058iter [01:33, 10.47iter/s]Best score: 0.2295: : 1059iter [01:33, 11.04iter/s]Best score: 0.2295: : 1059iter [01:33, 11.04iter/s]Best score: 0.2295: : 1060iter [01:34, 11.04iter/s]Best score: 0.2295: : 1061iter [01:34, 11.24iter/s]Best score: 0.2295: : 1061iter [01:34, 11.24iter/s]Best score: 0.2295: : 1062iter [01:34, 11.24iter/s]Best score: 0.2295: : 1063iter [01:34, 11.60iter/s]Best score: 0.2295: : 1063iter [01:34, 11.60iter/s]Best score: 0.2295: : 1064iter [01:34, 11.60iter/s]Best score: 0.2295: : 1065iter [01:34, 11.87iter/s]Best score: 0.2295: : 1065iter [01:34, 11.87iter/s]Best score: 0.2295: : 1066iter [01:34, 11.87iter/s]Best score: 0.2295: : 1067iter [01:34, 12.09iter/s]Best score: 0.2295: : 1067iter [01:34, 12.09iter/s]Best score: 0.2295: : 1068iter [01:34, 12.09iter/s]Best score: 0.2295: : 1069iter [01:34, 12.20iter/s]Best score: 0.2294: : 1069iter [01:34, 12.20iter/s]Best score: 0.2294: : 1070iter [01:34, 12.20iter/s]Best score: 0.2294: : 1071iter [01:34, 12.05iter/s]Best score: 0.2294: : 1071iter [01:34, 12.05iter/s]Best score: 0.2294: : 1072iter [01:35, 12.05iter/s]Best score: 0.2294: : 1073iter [01:35, 12.22iter/s]Best score: 0.2294: : 1073iter [01:35, 12.22iter/s]Best score: 0.2294: : 1074iter [01:35, 12.22iter/s]Best score: 0.2294: : 1075iter [01:35, 12.25iter/s]Best score: 0.2294: : 1075iter [01:35, 12.25iter/s]Best score: 0.2294: : 1076iter [01:35, 12.25iter/s]Best score: 0.2294: : 1077iter [01:35, 12.33iter/s]Best score: 0.2294: : 1077iter [01:35, 12.33iter/s]Best score: 0.2294: : 1078iter [01:35, 12.33iter/s]Best score: 0.2294: : 1079iter [01:35, 12.35iter/s]Best score: 0.2294: : 1079iter [01:35, 12.35iter/s]Best score: 0.2294: : 1080iter [01:35, 12.35iter/s]Best score: 0.2294: : 1081iter [01:35, 12.11iter/s]Best score: 0.2294: : 1081iter [01:35, 12.11iter/s]Best score: 0.2294: : 1082iter [01:35, 12.11iter/s]Best score: 0.2294: : 1083iter [01:35, 12.14iter/s]Best score: 0.2294: : 1083iter [01:35, 12.14iter/s]Best score: 0.2294: : 1084iter [01:36, 12.14iter/s]Best score: 0.2294: : 1085iter [01:36, 12.27iter/s]Best score: 0.2294: : 1085iter [01:36, 12.27iter/s]Best score: 0.2294: : 1086iter [01:36, 12.27iter/s]Best score: 0.2294: : 1087iter [01:36, 12.37iter/s]Best score: 0.2294: : 1087iter [01:36, 12.37iter/s]Best score: 0.2294: : 1088iter [01:36, 12.37iter/s]Best score: 0.2294: : 1089iter [01:36, 12.33iter/s]Best score: 0.2293: : 1089iter [01:36, 12.33iter/s]Best score: 0.2293: : 1090iter [01:36, 12.33iter/s]Best score: 0.2293: : 1091iter [01:36, 12.19iter/s]Best score: 0.2293: : 1091iter [01:36, 12.19iter/s]Best score: 0.2293: : 1092iter [01:36, 12.19iter/s]Best score: 0.2293: : 1093iter [01:36, 12.32iter/s]Best score: 0.2293: : 1093iter [01:36, 12.32iter/s]Best score: 0.2293: : 1094iter [01:36, 12.32iter/s]Best score: 0.2293: : 1095iter [01:36, 12.35iter/s]Best score: 0.2293: : 1095iter [01:36, 12.35iter/s]Best score: 0.2293: : 1096iter [01:36, 12.35iter/s]Best score: 0.2293: : 1097iter [01:36, 12.43iter/s]Best score: 0.2293: : 1097iter [01:37, 12.43iter/s]Best score: 0.2293: : 1098iter [01:37, 12.43iter/s]Best score: 0.2293: : 1099iter [01:37, 12.48iter/s]
[ITER 1100] Best: 0.2293
[PARAMS] Current best parameters:
  fx: 583.2941
  fy: 582.6664
  px: 1009.6051
  py: 718.6541
  k1: -0.07201702
  k2: 0.02989841
  k3: -0.01223556
  k4: 0.00228307
  p1: -0.02976866
  p2: -0.02709959
  p3: 0.00934145
  p4: 0.01385622
  s1: 0.0141
  s2: -0.0144
  s3: 0.0116
  s4: -0.0129
  tilt_x: 0.0201
  tilt_y: -0.0274
  scale: 3.0212
  rotation: -0.2504
Best score: 0.2293: : 1099iter [01:37, 12.48iter/s]Best score: 0.2293: : 1100iter [01:37, 11.28iter/s]

[📈] Running L-BFGS-B polish after 1100 DE iterations...
  Polish improved score: 0.229290 -> 0.228921

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 95,379 → 88,688 within 3500mm ring
  Ring polish did not improve score: 0.228921
  Success: True
  Tangential distortion: p1=-0.029779, p2=-0.027104, p3=0.009495, p4=0.013688
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.2289
[✅] Parameters copied to: /working/MDC048_W021(6)_2025-11-19/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 583.2941257773343
    fy: 582.6664484816497
    px: 1009.6051317276222
    py: 718.6540624365351
    k1: -0.07200857955484359
    k2: 0.029892103736027246
    k3: -0.01224010174790716
    k4: 0.0022870546727215392
    p1: -0.029779347846340946
    p2: -0.027103872493109124
    p3: 0.009494520972634857
    p4: 0.013687525693341456
    scale: 3.021223618697466
    rotation: -0.250394594552319
    mmpp: 3.4527451435001266
    nmpp: 3452745.1435001264

[🔄] Converting 720 frames to PTD, creating debug images for 400 calibration frames...
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   🔄 1000:  69%|██████▊   | 96/140 [00:00<00:00, 183.87frame/s][A
   🔄 1000:  82%|████████▏ | 115/140 [00:00<00:00, 184.01frame/s][A
   🔄 1000:  96%|█████████▌| 134/140 [00:00<00:00, 183.54frame/s][A
                                                                 [A📁 Rigs:  75%|███████▌  | 3/4 [00:05<00:01,  1.72s/rig]
   🔄 1500:   0%|          | 0/202 [00:00<?, ?frame/s][A
   🔄 1500:   9%|▉         | 19/202 [00:00<00:01, 180.96frame/s][A
   🔄 1500:  19%|█▉        | 38/202 [00:00<00:00, 177.10frame/s][A
   🔄 1500:  28%|██▊       | 56/202 [00:00<00:00, 176.10frame/s][A
   🔄 1500:  37%|███▋      | 74/202 [00:00<00:00, 175.92frame/s][A
   🔄 1500:  46%|████▌     | 93/202 [00:00<00:00, 177.41frame/s][A
   🔄 1500:  55%|█████▍    | 111/202 [00:00<00:00, 178.19frame/s][A
   🔄 1500:  64%|██████▍   | 129/202 [00:00<00:00, 177.73frame/s][A
   🔄 1500:  73%|███████▎  | 147/202 [00:00<00:00, 177.25frame/s][A
   🔄 1500:  82%|████████▏ | 165/202 [00:00<00:00, 176.41frame/s][A
   🔄 1500:  91%|█████████ | 183/202 [00:01<00:00, 176.00frame/s][A
   🔄 1500: 100%|█████████▉| 201/202 [00:01<00:00, 175.93frame/s][A
                                                                 [A📁 Rigs: 100%|██████████| 4/4 [00:07<00:00,  1.84s/rig]📁 Rigs: 100%|██████████| 4/4 [00:07<00:00,  1.84s/rig]
[✅] Saved PTDs: /working/MDC048_W021(6)_2025-11-19/calibration/debug/4_undistorted/output/ptd
📁 Rigs:   0%|          | 0/4 [00:00<?, ?rig/s]
   🔄 2000R:   0%|          | 0/100 [00:00<?, ?frame/s][A
   🔄 2000R:  18%|█▊        | 18/100 [00:00<00:00, 177.04frame/s][A
   🔄 2000R:  36%|███▌      | 36/100 [00:00<00:00, 173.30frame/s][A
   🔄 2000R:  54%|█████▍    | 54/100 [00:00<00:00, 172.76frame/s][A
   🔄 2000R:  72%|███████▏  | 72/100 [00:00<00:00, 173.48frame/s][A
   🔄 2000R:  90%|█████████ | 90/100 [00:00<00:00, 173.19frame/s][A
                                                                 [A📁 Rigs:  25%|██▌       | 1/4 [00:00<00:02,  1.09rig/s]
   🔄 2000L:   0%|          | 0/100 [00:00<?, ?frame/s][A
   🔄 2000L:  19%|█▉        | 19/100 [00:00<00:00, 180.12frame/s][A
   🔄 2000L:  38%|███▊      | 38/100 [00:00<00:00, 177.68frame/s][A
   🔄 2000L:  56%|█████▌    | 56/100 [00:00<00:00, 176.24frame/s][A
   🔄 2000L:  74%|███████▍  | 74/100 [00:00<00:00, 175.64frame/s][A
   🔄 2000L:  92%|█████████▏| 92/100 [00:00<00:00, 174.63frame/s][A
                                                                 [A📁 Rigs:  50%|█████     | 2/4 [00:01<00:02,  1.01s/rig]
   🔄 1000:   0%|          | 0/100 [00:00<?, ?frame/s][A
   🔄 1000:  19%|█▉        | 19/100 [00:00<00:00, 187.01frame/s][A
   🔄 1000:  38%|███▊      | 38/100 [00:00<00:00, 183.67frame/s][A
   🔄 1000:  57%|█████▋    | 57/100 [00:00<00:00, 183.27frame/s][A
   🔄 1000:  76%|███████▌  | 76/100 [00:00<00:00, 182.78frame/s][A
   🔄 1000:  95%|█████████▌| 95/100 [00:00<00:00, 182.93frame/s][A
                                                                [A📁 Rigs:  75%|███████▌  | 3/4 [00:02<00:00,  1.05rig/s]
   🔄 1500:   0%|          | 0/100 [00:00<?, ?frame/s][A
   🔄 1500:  19%|█▉        | 19/100 [00:00<00:00, 180.94frame/s][A
   🔄 1500:  38%|███▊      | 38/100 [00:00<00:00, 177.61frame/s][A
   🔄 1500:  56%|█████▌    | 56/100 [00:00<00:00, 178.17frame/s][A
   🔄 1500:  74%|███████▍  | 74/100 [00:00<00:00, 177.34frame/s][A
   🔄 1500:  92%|█████████▏| 92/100 [00:00<00:00, 176.65frame/s][A
                                                                [A📁 Rigs: 100%|██████████| 4/4 [00:03<00:00,  1.01rig/s]📁 Rigs: 100%|██████████| 4/4 [00:03<00:00,  1.02rig/s]
[✅] Saved PTDs: /working/MDC048_W021(6)_2025-11-19/calibration/debug/4_undistorted/temp_ptd
[WARN] No .tfd files found for serial extraction
[WARN] Failed to extract serial number from .tfd file. Check that .tfd files exist and contain 'LASERbidh' or 'LASERbidg' pattern. Using 'unknown' as fallback.
📤 Writing LUT:   0%|          | 0/3080448 [00:00<?, ?px/s]📤 Writing LUT:   3%|▎         | 81647/3080448 [00:00<00:03, 816466.89px/s]📤 Writing LUT:   5%|▌         | 166766/3080448 [00:00<00:03, 836886.82px/s]📤 Writing LUT:   8%|▊         | 250455/3080448 [00:00<00:03, 833927.17px/s]📤 Writing LUT:  11%|█         | 333849/3080448 [00:00<00:03, 832016.41px/s]📤 Writing LUT:  14%|█▎        | 418700/3080448 [00:00<00:03, 837946.06px/s]📤 Writing LUT:  16%|█▋        | 504484/3080448 [00:00<00:03, 844695.53px/s]📤 Writing LUT:  19%|█▉        | 589397/3080448 [00:00<00:02, 846143.03px/s]📤 Writing LUT:  22%|██▏       | 674797/3080448 [00:00<00:02, 848639.84px/s]📤 Writing LUT:  25%|██▍       | 760218/3080448 [00:00<00:02, 850379.10px/s]📤 Writing LUT:  27%|██▋       | 845579/3080448 [00:01<00:02, 851374.51px/s]📤 Writing LUT:  30%|███       | 930718/3080448 [00:01<00:02, 848568.58px/s]📤 Writing LUT:  33%|███▎      | 1015578/3080448 [00:01<00:02, 848488.12px/s]📤 Writing LUT:  36%|███▌      | 1102133/3080448 [00:01<00:02, 853645.15px/s]📤 Writing LUT:  39%|███▊      | 1187633/3080448 [00:01<00:02, 854050.42px/s]📤 Writing LUT:  41%|████▏     | 1273040/3080448 [00:01<00:02, 853440.09px/s]📤 Writing LUT:  44%|████▍     | 1359080/3080448 [00:01<00:02, 855531.07px/s]📤 Writing LUT:  47%|████▋     | 1446959/3080448 [00:01<00:01, 862519.12px/s]📤 Writing LUT:  50%|████▉     | 1533995/3080448 [00:01<00:01, 864872.31px/s]📤 Writing LUT:  53%|█████▎    | 1620484/3080448 [00:01<00:01, 857473.90px/s]📤 Writing LUT:  55%|█████▌    | 1706247/3080448 [00:02<00:01, 849275.71px/s]📤 Writing LUT:  58%|█████▊    | 1791199/3080448 [00:02<00:01, 842415.03px/s]📤 Writing LUT:  61%|██████    | 1875463/3080448 [00:02<00:01, 841545.11px/s]📤 Writing LUT:  64%|██████▎   | 1960346/3080448 [00:02<00:01, 843705.96px/s]📤 Writing LUT:  66%|██████▋   | 2044729/3080448 [00:02<00:01, 842748.97px/s]📤 Writing LUT:  69%|██████▉   | 2129013/3080448 [00:02<00:01, 841468.25px/s]📤 Writing LUT:  72%|███████▏  | 2213611/3080448 [00:02<00:01, 842812.09px/s]📤 Writing LUT:  75%|███████▍  | 2301160/3080448 [00:02<00:00, 852578.08px/s]📤 Writing LUT:  77%|███████▋  | 2386425/3080448 [00:02<00:00, 851567.00px/s]📤 Writing LUT:  80%|████████  | 2471939/3080448 [00:02<00:00, 852633.31px/s]📤 Writing LUT:  83%|████████▎ | 2557206/3080448 [00:03<00:00, 851493.14px/s]📤 Writing LUT:  86%|████████▌ | 2642502/3080448 [00:03<00:00, 851930.03px/s]📤 Writing LUT:  89%|████████▊ | 2729704/3080448 [00:03<00:00, 857945.40px/s]📤 Writing LUT:  91%|█████████▏| 2816124/3080448 [00:03<00:00, 859816.28px/s]📤 Writing LUT:  94%|█████████▍| 2902108/3080448 [00:03<00:00, 859402.28px/s]📤 Writing LUT:  97%|█████████▋| 2988050/3080448 [00:03<00:00, 858867.72px/s]📤 Writing LUT: 100%|█████████▉| 3073938/3080448 [00:03<00:00, 858422.68px/s]📤 Writing LUT: 100%|██████████| 3080448/3080448 [00:03<00:00, 850477.12px/s]
[✅] LUT written to: /working/MDC048_W021(6)_2025-11-19/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'MDC048_W021(6)_2025-11-19' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDC048_W021(6)_2025-11-19/calibration/MDC048_W021(6)_2025-11-19_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%|          | 0/174 [00:00<?, ?frame/s][A
   🔥 2000R:   5%|▌         | 9/174 [00:00<00:02, 82.44frame/s][A
   🔥 2000R:  10%|█         | 18/174 [00:00<00:01, 84.67frame/s][A
   🔥 2000R:  16%|█▌        | 27/174 [00:00<00:01, 85.76frame/s][A
   🔥 2000R:  21%|██        | 36/174 [00:00<00:01, 87.18frame/s][A
   🔥 2000R:  26%|██▌       | 45/174 [00:00<00:01, 86.72frame/s][A
   🔥 2000R:  31%|███       | 54/174 [00:00<00:01, 87.20frame/s][A
   🔥 2000R:  37%|███▋      | 64/174 [00:00<00:01, 88.38frame/s][A
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   🔥 2000R:  53%|█████▎    | 92/174 [00:01<00:00, 87.35frame/s][A
   🔥 2000R:  59%|█████▊    | 102/174 [00:01<00:00, 89.99frame/s][A
   🔥 2000R:  64%|██████▍   | 112/174 [00:01<00:00, 90.32frame/s][A
   🔥 2000R:  70%|███████   | 122/174 [00:01<00:00, 88.77frame/s][A
   🔥 2000R:  76%|███████▌  | 132/174 [00:01<00:00, 89.74frame/s][A
   🔥 2000R:  81%|████████  | 141/174 [00:01<00:00, 89.34frame/s][A
   🔥 2000R:  86%|████████▌ | 150/174 [00:01<00:00, 87.37frame/s][A
   🔥 2000R:  91%|█████████▏| 159/174 [00:01<00:00, 86.70frame/s][A
   🔥 2000R:  97%|█████████▋| 168/174 [00:01<00:00, 85.91frame/s][A
                                                                 [A[✅] 2000R: /working/MDC048_W021(6)_2025-11-19/calibration/debug/5_heatmap/2000R_heatmap.png
[✅] 2000R (fitted): /working/MDC048_W021(6)_2025-11-19/calibration/debug/5_heatmap/2000R_heatmap_fitted.png
📁 Rigs (heatmap):  25%|██▌       | 1/4 [00:03<00:10,  3.52s/rig]
   🔥 2000L:   0%|          | 0/204 [00:00<?, ?frame/s][A
   🔥 2000L:   4%|▍         | 9/204 [00:00<00:02, 85.45frame/s][A
   🔥 2000L:   9%|▉         | 18/204 [00:00<00:02, 82.97frame/s][A
   🔥 2000L:  13%|█▎        | 27/204 [00:00<00:02, 81.78frame/s][A
   🔥 2000L:  18%|█▊        | 36/204 [00:00<00:02, 82.66frame/s][A
   🔥 2000L:  22%|██▏       | 45/204 [00:00<00:01, 83.65frame/s][A
   🔥 2000L:  26%|██▋       | 54/204 [00:00<00:01, 84.39frame/s][A
   🔥 2000L:  31%|███       | 63/204 [00:00<00:01, 85.47frame/s][A
   🔥 2000L:  36%|███▌      | 73/204 [00:00<00:01, 89.10frame/s][A
   🔥 2000L:  41%|████      | 83/204 [00:00<00:01, 91.24frame/s][A
   🔥 2000L:  46%|████▌     | 93/204 [00:01<00:01, 92.35frame/s][A
   🔥 2000L:  50%|█████     | 103/204 [00:01<00:01, 91.46frame/s][A
   🔥 2000L:  55%|█████▌    | 113/204 [00:01<00:00, 91.20frame/s][A
   🔥 2000L:  60%|██████    | 123/204 [00:01<00:00, 93.41frame/s][A
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   🔥 2000L:  70%|███████   | 143/204 [00:01<00:00, 92.20frame/s][A
   🔥 2000L:  75%|███████▌  | 153/204 [00:01<00:00, 90.87frame/s][A
   🔥 2000L:  80%|███████▉  | 163/204 [00:01<00:00, 91.93frame/s][A
   🔥 2000L:  85%|████████▍ | 173/204 [00:01<00:00, 93.70frame/s][A
   🔥 2000L:  90%|████████▉ | 183/204 [00:02<00:00, 91.30frame/s][A
   🔥 2000L:  95%|█████████▍| 193/204 [00:02<00:00, 88.68frame/s][A
   🔥 2000L:  99%|█████████▉| 202/204 [00:02<00:00, 87.79frame/s][A
                                                                 [A[✅] 2000L: /working/MDC048_W021(6)_2025-11-19/calibration/debug/5_heatmap/2000L_heatmap.png
[✅] 2000L (fitted): /working/MDC048_W021(6)_2025-11-19/calibration/debug/5_heatmap/2000L_heatmap_fitted.png
📁 Rigs (heatmap):  50%|█████     | 2/4 [00:07<00:07,  3.67s/rig]
   🔥 1000:   0%|          | 0/140 [00:00<?, ?frame/s][A
   🔥 1000:   6%|▋         | 9/140 [00:00<00:01, 89.79frame/s][A
   🔥 1000:  13%|█▎        | 18/140 [00:00<00:01, 89.82frame/s][A
   🔥 1000:  19%|█▉        | 27/140 [00:00<00:01, 88.26frame/s][A
   🔥 1000:  26%|██▌       | 36/140 [00:00<00:01, 86.25frame/s][A
   🔥 1000:  32%|███▏      | 45/140 [00:00<00:01, 84.04frame/s][A
   🔥 1000:  39%|███▊      | 54/140 [00:00<00:01, 82.39frame/s][A
   🔥 1000:  45%|████▌     | 63/140 [00:00<00:00, 83.85frame/s][A
   🔥 1000:  51%|█████▏    | 72/140 [00:00<00:00, 84.61frame/s][A
   🔥 1000:  59%|█████▊    | 82/140 [00:00<00:00, 86.05frame/s][A
   🔥 1000:  65%|██████▌   | 91/140 [00:01<00:00, 85.62frame/s][A
   🔥 1000:  72%|███████▏  | 101/140 [00:01<00:00, 87.08frame/s][A
   🔥 1000:  79%|███████▉  | 111/140 [00:01<00:00, 88.42frame/s][A
   🔥 1000:  86%|████████▌ | 120/140 [00:01<00:00, 87.82frame/s][A
   🔥 1000:  92%|█████████▏| 129/140 [00:01<00:00, 87.61frame/s][A
   🔥 1000:  99%|█████████▉| 139/140 [00:01<00:00, 88.40frame/s][A
                                                                [A[✅] 1000: /working/MDC048_W021(6)_2025-11-19/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDC048_W021(6)_2025-11-19/calibration/debug/5_heatmap/1000_heatmap_fitted.png
📁 Rigs (heatmap):  75%|███████▌  | 3/4 [00:09<00:03,  3.04s/rig]
   🔥 1500:   0%|          | 0/202 [00:00<?, ?frame/s][A
   🔥 1500:   4%|▍         | 9/202 [00:00<00:02, 84.41frame/s][A
   🔥 1500:   9%|▉         | 18/202 [00:00<00:02, 83.02frame/s][A
   🔥 1500:  13%|█▎        | 27/202 [00:00<00:02, 81.66frame/s][A
   🔥 1500:  18%|█▊        | 36/202 [00:00<00:02, 81.40frame/s][A
   🔥 1500:  22%|██▏       | 45/202 [00:00<00:01, 79.39frame/s][A
   🔥 1500:  26%|██▌       | 53/202 [00:00<00:01, 76.26frame/s][A
   🔥 1500:  30%|███       | 61/202 [00:00<00:01, 76.08frame/s][A
   🔥 1500:  34%|███▍      | 69/202 [00:00<00:01, 75.88frame/s][A
   🔥 1500:  38%|███▊      | 77/202 [00:00<00:01, 75.53frame/s][A
   🔥 1500:  42%|████▏     | 85/202 [00:01<00:01, 76.22frame/s][A
   🔥 1500:  46%|████▌     | 93/202 [00:01<00:01, 76.17frame/s][A
   🔥 1500:  50%|█████     | 102/202 [00:01<00:01, 78.24frame/s][A
   🔥 1500:  55%|█████▍    | 111/202 [00:01<00:01, 79.78frame/s][A
   🔥 1500:  59%|█████▉    | 119/202 [00:01<00:01, 79.59frame/s][A
   🔥 1500:  63%|██████▎   | 127/202 [00:01<00:00, 78.38frame/s][A
   🔥 1500:  67%|██████▋   | 135/202 [00:01<00:00, 78.51frame/s][A
   🔥 1500:  71%|███████▏  | 144/202 [00:01<00:00, 80.13frame/s][A
   🔥 1500:  76%|███████▌  | 153/202 [00:01<00:00, 80.61frame/s][A
   🔥 1500:  80%|████████  | 162/202 [00:02<00:00, 79.93frame/s][A
   🔥 1500:  84%|████████▍ | 170/202 [00:02<00:00, 79.41frame/s][A
   🔥 1500:  89%|████████▊ | 179/202 [00:02<00:00, 79.86frame/s][A
   🔥 1500:  93%|█████████▎| 188/202 [00:02<00:00, 79.88frame/s][A
   🔥 1500:  98%|█████████▊| 197/202 [00:02<00:00, 80.19frame/s][A
                                                                [A[✅] 1500: /working/MDC048_W021(6)_2025-11-19/calibration/debug/5_heatmap/1500_heatmap.png
[✅] 1500 (fitted): /working/MDC048_W021(6)_2025-11-19/calibration/debug/5_heatmap/1500_heatmap_fitted.png
📁 Rigs (heatmap): 100%|██████████| 4/4 [00:13<00:00,  3.41s/rig]📁 Rigs (heatmap): 100%|██████████| 4/4 [00:13<00:00,  3.39s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MDC048_W021(6)_2025-11-19/calibration/debug/5_heatmap
[🏁] Finished processing MDC048_W021(6)_2025-11-19


================================================================================================================================
================================================================================================================================