2026-10-02T22:15:47 - INFO: Slick 0.0.8a13

🟢 Starting Calibration Pipeline

=== Processing MDC046_W048_2026-09-29 ===
2026-10-02T22:15:47 - INFO: Camera ID: 6393997
2026-10-02T22:15:47 - INFO: Wand ID: 
2026-10-02T22:15:47 - INFO: Recorded At: 2026-09-29T18:20:29Z

-------------------------------------------------------------------
                        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 2 las0.zip files to process
Processing Rigs:   0%|          | 0/2 [00:00<?, ?it/s][INFO] Filtered 520 stationary frames, 812 remain

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                                                                           [A[PASS2] Frame 0000657: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000658: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000659: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000660: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001114: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001115: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001116: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001117: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001235: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001236: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001237: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001238: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001256: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001257: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001258: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001259: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000659: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001116: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001237: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001258: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Summary: 8 frames fixed, 8 untrusted, 812 total

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                                                                           [A
[TIMING] 1000 — 812 frames
  Phase 1  radial detect   (parallel)  :  11.78s  (14.5 ms/frame)
  Phase 2a corner detect   (parallel)  :   5.69s  (7.0 ms/frame)
  Phase 2b corner fix      (sequential):   0.80s
  Phase 3  finalize        (sequential):  14.00s  (17.2 ms/frame)
    decode + undistort                 :   6.25s  (7.7 ms/frame)
    corner apply + refinement          :   3.64s  (4.5 ms/frame)
    segment                            :   3.38s  (4.2 ms/frame)
    smooth                             :   0.46s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  32.28s

Processing Rigs:  50%|█████     | 1/2 [00:38<00:38, 38.38s/it][INFO] Filtered 557 stationary frames, 648 remain

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                                                                          [A[PASS2] Frame 0000347: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000348: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000349: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000350: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001115: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001116: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001117: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001118: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001135: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001136: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001137: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001138: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000349: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001137: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Summary: 6 frames fixed, 7 untrusted, 648 total

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                                                                          [A
[TIMING] 500 — 648 frames
  Phase 1  radial detect   (parallel)  :  10.22s  (15.8 ms/frame)
  Phase 2a corner detect   (parallel)  :   5.43s  (8.4 ms/frame)
  Phase 2b corner fix      (sequential):   0.58s
  Phase 3  finalize        (sequential):   9.88s  (15.2 ms/frame)
    decode + undistort                 :   4.21s  (6.5 ms/frame)
    corner apply + refinement          :   2.45s  (3.8 ms/frame)
    segment                            :   2.63s  (4.1 ms/frame)
    smooth                             :   0.37s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  26.12s

Processing Rigs: 100%|██████████| 2/2 [01:08<00:00, 33.44s/it]Processing Rigs: 100%|██████████| 2/2 [01:08<00:00, 34.18s/it]
[💾] Saved RigFrameDataset to /working/MDC046_W048_2026-09-29/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 1460 frames from 2 rigs to /working/MDC046_W048_2026-09-29/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDC046_W048_2026-09-29/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 1000: 100 frames selected from 812
[📋] 500: 100 frames selected from 648
[💾] Saved RigFrameDataset to /working/MDC046_W048_2026-09-29/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDC046_W048_2026-09-29/calibration/debug/1_digitized/rig_frames.json

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

-> Calculating the casing center ...
[INFO] Using 40 total sampled bright frames
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-------------------------------------------------------------------
                        Step 3: Calibration                        
-------------------------------------------------------------------

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27%|██▋       | 27/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 512.121} (0.017):  27%|██▋       | 27/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.001 | Best: {'fx': 512.121} (0.017):  28%|██▊       | 28/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.003 | Best: {'fx': 512.121} (0.017):  29%|██▉       | 29/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.008 | Best: {'fx': 512.121} (0.017):  30%|███       | 30/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.022 | Best: {'fx': 561.616} (0.022):  31%|███       | 31/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.030 | Best: {'fx': 519.192} (0.030):  32%|███▏      | 32/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.045 | Best: {'fx': 526.263} (0.045):  33%|███▎      | 33/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.073 | Best: {'fx': 533.333} (0.073):  34%|███▍      | 34/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.032 | Best: {'fx': 533.333} (0.073):  35%|███▌      | 35/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.046 | Best: {'fx': 533.333} (0.073):  36%|███▌      | 36/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.025 | Best: {'fx': 533.333} (0.073):  37%|███▋      | 37/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.013 | Best: {'fx': 533.333} (0.073):  38%|███▊      | 38/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.015 | Best: {'fx': 533.333} (0.073):  39%|███▉      | 39/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.019 | Best: {'fx': 533.333} (0.073):  40%|████      | 40/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.016 | Best: {'fx': 533.333} (0.073):  41%|████      | 41/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.017 | Best: {'fx': 533.333} (0.073):  42%|████▏     | 42/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.014 | Best: {'fx': 533.333} (0.073):  43%|████▎     | 43/100 [00:00<00:00, 77.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.014 | Best: {'fx': 533.333} (0.073):  44%|████▍     | 44/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 533.333} (0.073):  44%|████▍     | 44/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.013 | Best: {'fx': 533.333} (0.073):  45%|████▌     | 45/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 533.333} (0.073):  46%|████▌     | 46/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.073):  47%|████▋     | 47/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 533.333} (0.073):  48%|████▊     | 48/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.073):  49%|████▉     | 49/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.073):  50%|█████     | 50/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.073):  51%|█████     | 51/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.073):  52%|█████▏    | 52/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.073):  53%|█████▎    | 53/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.073):  54%|█████▍    | 54/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.073):  55%|█████▌    | 55/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.073):  56%|█████▌    | 56/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.073):  57%|█████▋    | 57/100 [00:00<00:00, 108.09it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.073):  58%|█████▊    | 58/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.073):  58%|█████▊    | 58/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.073):  59%|█████▉    | 59/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.073):  60%|██████    | 60/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  61%|██████    | 61/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.073):  62%|██████▏   | 62/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  63%|██████▎   | 63/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  64%|██████▍   | 64/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  65%|██████▌   | 65/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  66%|██████▌   | 66/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  67%|██████▋   | 67/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  68%|██████▊   | 68/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  69%|██████▉   | 69/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  70%|███████   | 70/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  71%|███████   | 71/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  72%|███████▏  | 72/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  73%|███████▎  | 73/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  74%|███████▍  | 74/100 [00:00<00:00, 115.29it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  75%|███████▌  | 75/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  75%|███████▌  | 75/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  76%|███████▌  | 76/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  77%|███████▋  | 77/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  78%|███████▊  | 78/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  79%|███████▉  | 79/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  80%|████████  | 80/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  81%|████████  | 81/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  82%|████████▏ | 82/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  83%|████████▎ | 83/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  84%|████████▍ | 84/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  85%|████████▌ | 85/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  86%|████████▌ | 86/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  87%|████████▋ | 87/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  88%|████████▊ | 88/100 [00:00<00:00, 129.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  89%|████████▉ | 89/100 [00:00<00:00, 123.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  89%|████████▉ | 89/100 [00:00<00:00, 123.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  90%|█████████ | 90/100 [00:00<00:00, 123.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  91%|█████████ | 91/100 [00:00<00:00, 123.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  92%|█████████▏| 92/100 [00:00<00:00, 123.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  93%|█████████▎| 93/100 [00:00<00:00, 123.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  94%|█████████▍| 94/100 [00:00<00:00, 123.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  95%|█████████▌| 95/100 [00:00<00:00, 123.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  96%|█████████▌| 96/100 [00:00<00:00, 123.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  97%|█████████▋| 97/100 [00:00<00:00, 123.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  98%|█████████▊| 98/100 [00:00<00:00, 123.71it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.073):  99%|█████████▉| 99/100 [00:00<00:00, 123.71it/s]                                                                                                                                          0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.011 | Best: {'fx': 508.333} (0.011):   0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.011 | Best: {'fx': 508.333} (0.011):   2%|▏         | 1/50 [00:00<00:05,  8.53it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.012 | Best: {'fx': 510.374} (0.012):   2%|▏         | 1/50 [00:00<00:05,  8.53it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.012 | Best: {'fx': 510.374} (0.012):   4%|▍         | 2/50 [00:00<00:05,  8.53it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.020 | Best: {'fx': 513.435} (0.020):   6%|▌         | 3/50 [00:00<00:05,  8.53it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.015 | Best: {'fx': 513.435} (0.020):   8%|▊         | 4/50 [00:00<00:05,  8.53it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.017 | Best: {'fx': 513.435} (0.020):  10%|█         | 5/50 [00:00<00:05,  8.53it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.023 | Best: {'fx': 514.456} (0.023):  12%|█▏        | 6/50 [00:00<00:05,  8.53it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.024 | Best: {'fx': 515.476} (0.024):  14%|█▍        | 7/50 [00:00<00:05,  8.53it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.026 | Best: {'fx': 516.497} (0.026):  16%|█▌        | 8/50 [00:00<00:04,  8.53it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.029 | Best: {'fx': 517.517} (0.029):  18%|█▊        | 9/50 [00:00<00:04,  8.53it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.029 | Best: {'fx': 517.517} (0.029):  20%|██        | 10/50 [00:00<00:00, 52.08it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.030 | Best: {'fx': 518.537} (0.030):  20%|██        | 10/50 [00:00<00:00, 52.08it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.040 | Best: {'fx': 523.639} (0.040):  22%|██▏       | 11/50 [00:00<00:00, 52.08it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.035 | Best: {'fx': 523.639} (0.040):  24%|██▍       | 12/50 [00:00<00:00, 52.08it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.032 | Best: {'fx': 523.639} (0.040):  26%|██▌       | 13/50 [00:00<00:00, 52.08it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.035 | Best: {'fx': 523.639} (0.040):  28%|██▊       | 14/50 [00:00<00:00, 52.08it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.038 | Best: {'fx': 523.639} (0.040):  30%|███       | 15/50 [00:00<00:00, 52.08it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.042 | Best: {'fx': 524.66} (0.042):  32%|███▏      | 16/50 [00:00<00:00, 52.08it/s] Brute | Start: {'fx': 533.333} (0.073) | Current: 0.042 | Best: {'fx': 525.68} (0.042):  34%|███▍      | 17/50 [00:00<00:00, 52.08it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.047 | Best: {'fx': 526.701} (0.047):  36%|███▌      | 18/50 [00:00<00:00, 52.08it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.049 | Best: {'fx': 527.721} (0.049):  38%|███▊      | 19/50 [00:00<00:00, 52.08it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.078 | Best: {'fx': 532.823} (0.078):  40%|████      | 20/50 [00:00<00:00, 52.08it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.055 | Best: {'fx': 532.823} (0.078):  42%|████▏     | 21/50 [00:00<00:00, 52.08it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.062 | Best: {'fx': 532.823} (0.078):  44%|████▍     | 22/50 [00:00<00:00, 52.08it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.074 | Best: {'fx': 532.823} (0.078):  46%|████▌     | 23/50 [00:00<00:00, 52.08it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.074 | Best: {'fx': 532.823} (0.078):  48%|████▊     | 24/50 [00:00<00:00, 89.64it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.066 | Best: {'fx': 532.823} (0.078):  48%|████▊     | 24/50 [00:00<00:00, 89.64it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.075 | Best: {'fx': 532.823} (0.078):  50%|█████     | 25/50 [00:00<00:00, 89.64it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.066 | Best: {'fx': 532.823} (0.078):  52%|█████▏    | 26/50 [00:00<00:00, 89.64it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.066 | Best: {'fx': 532.823} (0.078):  54%|█████▍    | 27/50 [00:00<00:00, 89.64it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.059 | Best: {'fx': 532.823} (0.078):  56%|█████▌    | 28/50 [00:00<00:00, 89.64it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.055 | Best: {'fx': 532.823} (0.078):  58%|█████▊    | 29/50 [00:00<00:00, 89.64it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.052 | Best: {'fx': 532.823} (0.078):  60%|██████    | 30/50 [00:00<00:00, 89.64it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.047 | Best: {'fx': 532.823} (0.078):  62%|██████▏   | 31/50 [00:00<00:00, 89.64it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.043 | Best: {'fx': 532.823} (0.078):  64%|██████▍   | 32/50 [00:00<00:00, 89.64it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.042 | Best: {'fx': 532.823} (0.078):  66%|██████▌   | 33/50 [00:00<00:00, 89.64it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.042 | Best: {'fx': 532.823} (0.078):  68%|██████▊   | 34/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.041 | Best: {'fx': 532.823} (0.078):  68%|██████▊   | 34/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.033 | Best: {'fx': 532.823} (0.078):  70%|███████   | 35/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.038 | Best: {'fx': 532.823} (0.078):  72%|███████▏  | 36/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.035 | Best: {'fx': 532.823} (0.078):  74%|███████▍  | 37/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.034 | Best: {'fx': 532.823} (0.078):  76%|███████▌  | 38/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.031 | Best: {'fx': 532.823} (0.078):  78%|███████▊  | 39/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.030 | Best: {'fx': 532.823} (0.078):  80%|████████  | 40/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.029 | Best: {'fx': 532.823} (0.078):  82%|████████▏ | 41/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.027 | Best: {'fx': 532.823} (0.078):  84%|████████▍ | 42/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.029 | Best: {'fx': 532.823} (0.078):  86%|████████▌ | 43/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.026 | Best: {'fx': 532.823} (0.078):  88%|████████▊ | 44/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.026 | Best: {'fx': 532.823} (0.078):  90%|█████████ | 45/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.024 | Best: {'fx': 532.823} (0.078):  92%|█████████▏| 46/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.023 | Best: {'fx': 532.823} (0.078):  94%|█████████▍| 47/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.025 | Best: {'fx': 532.823} (0.078):  96%|█████████▌| 48/50 [00:00<00:00, 90.00it/s]Brute | Start: {'fx': 533.333} (0.073) | Current: 0.024 | Best: {'fx': 532.823} (0.078):  98%|█████████▊| 49/50 [00:00<00:00, 90.00it/s]                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 532.8231292517007
    px: 987.0
    py: 751.0
    k1: 0.0
    k2: 0.0
    k3: 0.0
    k4: 0.0
    p1: 0.0
    p2: 0.0
    p3: 0.0
    p4: 0.0
    scale: 3.0
    rotation: 0.0


[🔲] Square Reference Optimization
    Including tangential distortion parameters (p1, p2, p3, p4) in joint optimization
  Selecting up to 20 frames per rig (excluded 0 incomplete frames): 20 frames will be used for optimization
  Rigs: 1000(1000mm):20/20
  Total: 20/20 frames used for optimization
Initial score: 57.3459: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 57.3459, picklable_objective(x0) = 57.3064
Best score: 57.3064: : 0iter [00:01, ?iter/s] Best score: 57.3064: : 1iter [00:01,  2.00s/iter]Best score: 57.3064: : 1iter [00:02,  2.00s/iter]Best score: 57.3064: : 2iter [00:02,  2.00s/iter]Best score: 57.3064: : 3iter [00:02,  2.00s/iter]Best score: 57.3064: : 4iter [00:02,  2.41iter/s]Best score: 57.3064: : 4iter [00:02,  2.41iter/s]Best score: 57.3064: : 5iter [00:02,  2.41iter/s]Best score: 57.3064: : 6iter [00:02,  2.41iter/s]Best score: 57.3064: : 7iter [00:02,  2.41iter/s]Best score: 57.3064: : 8iter [00:02,  5.58iter/s]Best score: 57.3064: : 8iter [00:02,  5.58iter/s]Best score: 57.3064: : 9iter [00:02,  5.58iter/s]Best score: 57.3064: : 10iter [00:02,  5.58iter/s]Best score: 57.3064: : 11iter [00:02,  5.58iter/s]Best score: 57.3064: : 12iter [00:02,  9.23iter/s]Best score: 57.3064: : 12iter [00:02,  9.23iter/s]Best score: 57.3064: : 13iter [00:02,  9.23iter/s]Best score: 57.3064: : 14iter [00:02,  9.23iter/s]Best score: 57.3064: : 15iter [00:02,  9.23iter/s]Best score: 57.3064: : 16iter [00:02, 13.29iter/s]Best score: 57.3064: : 16iter [00:02, 13.29iter/s]Best score: 57.3064: : 17iter [00:02, 13.29iter/s]Best score: 57.3064: : 18iter [00:02, 13.29iter/s]Best score: 57.3064: : 19iter [00:02, 13.29iter/s]Best score: 57.3064: : 20iter [00:02, 17.37iter/s]Best score: 57.3064: : 20iter [00:02, 17.37iter/s]Best score: 57.3064: : 21iter [00:02, 17.37iter/s]Best score: 57.3064: : 22iter [00:02, 17.37iter/s]Best score: 57.3064: : 23iter [00:02, 17.37iter/s]Best score: 57.3064: : 24iter [00:02, 21.50iter/s]Best score: 57.3064: : 24iter [00:02, 21.50iter/s]Best score: 57.3064: : 25iter [00:02, 21.50iter/s]Best score: 57.3064: : 26iter [00:02, 21.50iter/s]Best score: 57.3064: : 27iter [00:02, 21.50iter/s]Best score: 57.3064: : 28iter [00:02, 25.31iter/s]Best score: 57.3064: : 28iter [00:02, 25.31iter/s]Best score: 57.3064: : 29iter [00:02, 25.31iter/s]Best score: 57.3064: : 30iter [00:02, 25.31iter/s]Best score: 57.3064: : 31iter [00:02, 25.31iter/s]Best score: 57.3064: : 32iter [00:02, 28.53iter/s]Best score: 57.3064: : 32iter [00:02, 28.53iter/s]Best score: 57.3064: : 33iter [00:02, 28.53iter/s]Best score: 57.3064: : 34iter [00:02, 28.53iter/s]Best score: 57.3064: : 35iter [00:02, 28.53iter/s]Best score: 57.3064: : 36iter [00:02, 31.09iter/s]Best score: 57.3064: : 36iter [00:02, 31.09iter/s]Best score: 57.3064: : 37iter [00:03, 31.09iter/s]Best score: 57.3064: : 38iter [00:03, 31.09iter/s]Best score: 57.3064: : 39iter [00:03, 31.09iter/s]Best score: 57.3064: : 40iter [00:03, 33.20iter/s]Best score: 57.3064: : 40iter [00:03, 33.20iter/s]Best score: 57.3064: : 41iter [00:03, 33.20iter/s]Best score: 57.3064: : 42iter [00:03, 33.20iter/s]Best score: 57.3064: : 43iter [00:03, 33.20iter/s]Best score: 57.3064: : 44iter [00:03, 34.95iter/s]Best score: 57.3064: : 44iter [00:03, 34.95iter/s]Best score: 57.3064: : 45iter [00:03, 34.95iter/s]Best score: 57.3064: : 46iter [00:03, 34.95iter/s]Best score: 57.3064: : 47iter [00:03, 34.95iter/s]Best score: 57.3064: : 48iter [00:03, 36.20iter/s]Best score: 57.3064: : 48iter [00:03, 36.20iter/s]
[ITER 50] Best: 57.3064
[PARAMS] Current best parameters:
  fx: 532.8231
  fy: 532.8231
  px: 987.0000
  py: 751.0000
  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: 57.3064: : 49iter [00:03, 36.20iter/s]Best score: 57.3064: : 50iter [00:03, 36.20iter/s]Best score: 57.3064: : 51iter [00:03, 36.20iter/s]Best score: 57.3064: : 52iter [00:03, 36.41iter/s]Best score: 57.3064: : 52iter [00:03, 36.41iter/s]Best score: 57.3064: : 53iter [00:03, 36.41iter/s]Best score: 57.3064: : 54iter [00:03, 36.41iter/s]Best score: 57.3064: : 55iter [00:03, 36.41iter/s]Best score: 57.3064: : 56iter [00:03, 36.92iter/s]Best score: 57.3064: : 56iter [00:03, 36.92iter/s]Best score: 57.3064: : 57iter [00:03, 36.92iter/s]Best score: 57.3064: : 58iter [00:03, 36.92iter/s]Best score: 57.3064: : 59iter [00:03, 36.92iter/s]Best score: 57.3064: : 60iter [00:03, 37.48iter/s]Best score: 57.3064: : 60iter [00:03, 37.48iter/s]Best score: 57.3064: : 61iter [00:03, 37.48iter/s]Best score: 57.3064: : 62iter [00:03, 37.48iter/s]Best score: 57.3064: : 63iter [00:03, 37.48iter/s]Best score: 57.3064: : 64iter [00:03, 38.02iter/s]Best score: 57.3064: : 64iter [00:03, 38.02iter/s]Best score: 57.3064: : 65iter [00:03, 38.02iter/s]Best score: 57.3064: : 66iter [00:03, 38.02iter/s]Best score: 57.3064: : 67iter [00:03, 38.02iter/s]Best score: 57.3064: : 68iter [00:03, 38.56iter/s]Best score: 57.3064: : 68iter [00:03, 38.56iter/s]Best score: 57.3064: : 69iter [00:03, 38.56iter/s]Best score: 57.3064: : 70iter [00:03, 38.56iter/s]Best score: 57.3064: : 71iter [00:03, 38.56iter/s]Best score: 57.3064: : 72iter [00:03, 38.62iter/s]Best score: 57.3064: : 72iter [00:03, 38.62iter/s]Best score: 57.3064: : 73iter [00:03, 38.62iter/s]Best score: 57.3064: : 74iter [00:03, 38.62iter/s]Best score: 57.3064: : 75iter [00:03, 38.62iter/s]Best score: 57.3064: : 76iter [00:03, 38.96iter/s]Best score: 57.3064: : 76iter [00:04, 38.96iter/s]Best score: 57.3064: : 77iter [00:04, 38.96iter/s]Best score: 57.3064: : 78iter [00:04, 38.96iter/s]Best score: 57.3064: : 79iter [00:04, 38.96iter/s]Best score: 57.3064: : 80iter [00:04, 38.92iter/s]Best score: 57.3064: : 80iter [00:04, 38.92iter/s]Best score: 57.3064: : 81iter [00:04, 38.92iter/s]Best score: 57.3064: : 82iter [00:04, 38.92iter/s]Best score: 57.3064: : 83iter [00:04, 38.92iter/s]Best score: 57.3064: : 84iter [00:04, 39.14iter/s]Best score: 57.3064: : 84iter [00:04, 39.14iter/s]Best score: 57.3064: : 85iter [00:04, 39.14iter/s]Best score: 57.3064: : 86iter [00:04, 39.14iter/s]Best score: 57.3064: : 87iter [00:04, 39.14iter/s]Best score: 57.3064: : 88iter [00:04, 39.25iter/s]Best score: 57.3064: : 88iter [00:04, 39.25iter/s]Best score: 57.3064: : 89iter [00:04, 39.25iter/s]Best score: 57.3064: : 90iter [00:04, 39.25iter/s]Best score: 57.3064: : 91iter [00:04, 39.25iter/s]Best score: 57.3064: : 92iter [00:04, 39.10iter/s]Best score: 57.3064: : 92iter [00:04, 39.10iter/s]Best score: 57.3064: : 93iter [00:04, 39.10iter/s]Best score: 57.3064: : 94iter [00:04, 39.10iter/s]Best score: 57.3064: : 95iter [00:04, 39.10iter/s]Best score: 57.3064: : 96iter [00:04, 39.10iter/s]Best score: 57.3064: : 97iter [00:04, 39.43iter/s]Best score: 57.3064: : 97iter [00:04, 39.43iter/s]Best score: 57.3064: : 98iter [00:04, 39.43iter/s]
[ITER 100] Best: 40.3775
[PARAMS] Current best parameters:
  fx: 558.7711
  fy: 554.4115
  px: 970.3963
  py: 743.9871
  k1: 0.00162218
  k2: -0.02973757
  k3: 0.00541127
  k4: 0.00233096
  p1: -0.02386769
  p2: -0.00856927
  p3: -0.00438695
  p4: -0.00967899
  s1: -0.0197
  s2: 0.0171
  s3: 0.0084
  s4: 0.0253
  tilt_x: -0.0280
  tilt_y: 0.0419
  scale: 2.9927
  rotation: -0.2374
Best score: 40.3775: : 99iter [00:04, 39.43iter/s]Best score: 40.3775: : 100iter [00:04, 39.43iter/s]Best score: 40.3775: : 101iter [00:04, 36.77iter/s]Best score: 40.3775: : 101iter [00:04, 36.77iter/s]Best score: 40.3775: : 102iter [00:04, 36.77iter/s]Best score: 40.3775: : 103iter [00:04, 36.77iter/s]Best score: 40.3775: : 104iter [00:04, 36.77iter/s]Best score: 40.3775: : 105iter [00:04, 37.51iter/s]Best score: 40.3775: : 105iter [00:04, 37.51iter/s]Best score: 40.3775: : 106iter [00:04, 37.51iter/s]Best score: 40.3775: : 107iter [00:04, 37.51iter/s]Best score: 40.3775: : 108iter [00:04, 37.51iter/s]Best score: 40.3775: : 109iter [00:04, 38.10iter/s]Best score: 40.3775: : 109iter [00:04, 38.10iter/s]Best score: 40.3775: : 110iter [00:04, 38.10iter/s]Best score: 40.3775: : 111iter [00:04, 38.10iter/s]Best score: 40.3775: : 112iter [00:04, 38.10iter/s]Best score: 40.3775: : 113iter [00:04, 38.17iter/s]Best score: 40.3775: : 113iter [00:04, 38.17iter/s]Best score: 40.3775: : 114iter [00:05, 38.17iter/s]Best score: 40.3775: : 115iter [00:05, 38.17iter/s]Best score: 40.3775: : 116iter [00:05, 38.17iter/s]Best score: 40.3775: : 117iter [00:05, 38.62iter/s]Best score: 40.3775: : 117iter [00:05, 38.62iter/s]Best score: 40.3775: : 118iter [00:05, 38.62iter/s]Best score: 40.3775: : 119iter [00:05, 38.62iter/s]Best score: 40.3775: : 120iter [00:05, 38.62iter/s]Best score: 40.3775: : 121iter [00:05, 38.75iter/s]Best score: 40.3775: : 121iter [00:05, 38.75iter/s]Best score: 40.3775: : 122iter [00:05, 38.75iter/s]Best score: 40.3775: : 123iter [00:05, 38.75iter/s]Best score: 40.3775: : 124iter [00:05, 38.75iter/s]Best score: 40.3775: : 125iter [00:05, 39.04iter/s]Best score: 40.3775: : 125iter [00:05, 39.04iter/s]Best score: 40.3775: : 126iter [00:05, 39.04iter/s]Best score: 40.3775: : 127iter [00:05, 39.04iter/s]Best score: 40.3775: : 128iter [00:05, 39.04iter/s]Best score: 40.3775: : 129iter [00:05, 39.12iter/s]Best score: 40.3775: : 129iter [00:05, 39.12iter/s]Best score: 40.3775: : 130iter [00:05, 39.12iter/s]Best score: 40.3775: : 131iter [00:05, 39.12iter/s]Best score: 40.3775: : 132iter [00:05, 39.12iter/s]Best score: 40.3775: : 133iter [00:05, 39.06iter/s]Best score: 40.3775: : 133iter [00:05, 39.06iter/s]Best score: 40.3775: : 134iter [00:05, 39.06iter/s]Best score: 40.3775: : 135iter [00:05, 39.06iter/s]Best score: 40.3775: : 136iter [00:05, 39.06iter/s]Best score: 40.3775: : 137iter [00:05, 39.26iter/s]Best score: 40.3775: : 137iter [00:05, 39.26iter/s]Best score: 40.3775: : 138iter [00:05, 39.26iter/s]Best score: 40.3775: : 139iter [00:05, 39.26iter/s]Best score: 40.3775: : 140iter [00:05, 39.26iter/s]Best score: 40.3775: : 141iter [00:05, 38.75iter/s]Best score: 40.3775: : 141iter [00:05, 38.75iter/s]Best score: 40.3775: : 142iter [00:05, 38.75iter/s]Best score: 40.3775: : 143iter [00:05, 38.75iter/s]Best score: 40.3775: : 144iter [00:05, 38.75iter/s]Best score: 40.3775: : 145iter [00:05, 38.94iter/s]Best score: 40.3775: : 145iter [00:05, 38.94iter/s]Best score: 40.3775: : 146iter [00:05, 38.94iter/s]Best score: 40.3775: : 147iter [00:05, 38.94iter/s]Best score: 40.3775: : 148iter [00:05, 38.94iter/s]Best score: 40.3775: : 149iter [00:05, 37.61iter/s]
[ITER 150] Best: 40.3775
[PARAMS] Current best parameters:
  fx: 558.7711
  fy: 554.4115
  px: 970.3963
  py: 743.9871
  k1: 0.00162218
  k2: -0.02973757
  k3: 0.00541127
  k4: 0.00233096
  p1: -0.02386769
  p2: -0.00856927
  p3: -0.00438695
  p4: -0.00967899
  s1: -0.0197
  s2: 0.0171
  s3: 0.0084
  s4: 0.0253
  tilt_x: -0.0280
  tilt_y: 0.0419
  scale: 2.9927
  rotation: -0.2374
Best score: 40.3775: : 149iter [00:05, 37.61iter/s]Best score: 40.3775: : 150iter [00:06, 37.61iter/s]Best score: 40.3775: : 151iter [00:06, 37.61iter/s]Best score: 40.3775: : 152iter [00:06, 37.61iter/s]Best score: 40.3775: : 153iter [00:06, 30.50iter/s]Best score: 40.3775: : 153iter [00:06, 30.50iter/s]Best score: 40.3775: : 154iter [00:06, 30.50iter/s]Best score: 40.3775: : 155iter [00:06, 30.50iter/s]Best score: 40.3775: : 156iter [00:06, 30.50iter/s]Best score: 40.3775: : 157iter [00:06, 32.54iter/s]Best score: 40.3775: : 157iter [00:06, 32.54iter/s]Best score: 40.3775: : 158iter [00:06, 32.54iter/s]Best score: 40.3775: : 159iter [00:06, 32.54iter/s]Best score: 40.3775: : 160iter [00:06, 32.54iter/s]Best score: 40.3775: : 161iter [00:06, 33.97iter/s]Best score: 40.3775: : 161iter [00:06, 33.97iter/s]Best score: 40.3775: : 162iter [00:06, 33.97iter/s]Best score: 40.3775: : 163iter [00:06, 33.97iter/s]Best score: 40.3775: : 164iter [00:06, 33.97iter/s]Best score: 40.3775: : 165iter [00:06, 35.18iter/s]Best score: 40.3775: : 165iter [00:06, 35.18iter/s]Best score: 40.3775: : 166iter [00:06, 35.18iter/s]Best score: 40.3775: : 167iter [00:06, 35.18iter/s]Best score: 40.3775: : 168iter [00:06, 35.18iter/s]Best score: 40.3775: : 169iter [00:06, 36.43iter/s]Best score: 40.3775: : 169iter [00:06, 36.43iter/s]Best score: 40.3775: : 170iter [00:06, 36.43iter/s]Best score: 40.3775: : 171iter [00:06, 36.43iter/s]Best score: 40.3775: : 172iter [00:06, 36.43iter/s]Best score: 40.3775: : 173iter [00:06, 36.92iter/s]Best score: 40.3775: : 173iter [00:06, 36.92iter/s]Best score: 40.3775: : 174iter [00:06, 36.92iter/s]Best score: 40.3775: : 175iter [00:06, 36.92iter/s]Best score: 40.3775: : 176iter [00:06, 36.92iter/s]Best score: 40.3775: : 177iter [00:06, 37.54iter/s]Best score: 40.3775: : 177iter [00:06, 37.54iter/s]Best score: 40.3775: : 178iter [00:06, 37.54iter/s]Best score: 40.3775: : 179iter [00:06, 37.54iter/s]Best score: 40.3775: : 180iter [00:06, 37.54iter/s]Best score: 40.3775: : 181iter [00:06, 37.75iter/s]Best score: 40.3775: : 181iter [00:06, 37.75iter/s]Best score: 40.3775: : 182iter [00:06, 37.75iter/s]Best score: 40.3775: : 183iter [00:06, 37.75iter/s]Best score: 40.3775: : 184iter [00:06, 37.75iter/s]Best score: 40.3775: : 185iter [00:06, 38.31iter/s]Best score: 40.3775: : 185iter [00:06, 38.31iter/s]Best score: 40.3775: : 186iter [00:06, 38.31iter/s]Best score: 40.3775: : 187iter [00:06, 38.31iter/s]Best score: 40.3775: : 188iter [00:07, 38.31iter/s]Best score: 40.3775: : 189iter [00:07, 38.39iter/s]Best score: 40.3775: : 189iter [00:07, 38.39iter/s]Best score: 40.3775: : 190iter [00:07, 38.39iter/s]Best score: 40.3775: : 191iter [00:07, 38.39iter/s]Best score: 40.3775: : 192iter [00:07, 38.39iter/s]Best score: 40.3775: : 193iter [00:07, 37.73iter/s]Best score: 40.3775: : 193iter [00:07, 37.73iter/s]Best score: 40.3775: : 194iter [00:07, 37.73iter/s]Best score: 40.3775: : 195iter [00:07, 37.73iter/s]Best score: 40.3775: : 196iter [00:07, 37.73iter/s]Best score: 40.3775: : 197iter [00:07, 38.33iter/s]Best score: 40.3775: : 197iter [00:07, 38.33iter/s]Best score: 40.3775: : 198iter [00:07, 38.33iter/s]
[ITER 200] Best: 40.3775
[PARAMS] Current best parameters:
  fx: 558.7711
  fy: 554.4115
  px: 970.3963
  py: 743.9871
  k1: 0.00162218
  k2: -0.02973757
  k3: 0.00541127
  k4: 0.00233096
  p1: -0.02386769
  p2: -0.00856927
  p3: -0.00438695
  p4: -0.00967899
  s1: -0.0197
  s2: 0.0171
  s3: 0.0084
  s4: 0.0253
  tilt_x: -0.0280
  tilt_y: 0.0419
  scale: 2.9927
  rotation: -0.2374
Best score: 40.3775: : 199iter [00:07, 38.33iter/s]Best score: 40.3775: : 200iter [00:07, 38.33iter/s]Best score: 40.3775: : 201iter [00:07, 31.22iter/s]Best score: 40.3775: : 201iter [00:07, 31.22iter/s]Best score: 40.3775: : 202iter [00:07, 31.22iter/s]Best score: 40.3775: : 203iter [00:07, 31.22iter/s]Best score: 40.3775: : 204iter [00:07, 31.22iter/s]Best score: 40.3775: : 205iter [00:07, 33.41iter/s]Best score: 40.3775: : 205iter [00:07, 33.41iter/s]Best score: 40.3775: : 206iter [00:07, 33.41iter/s]Best score: 40.3775: : 207iter [00:07, 33.41iter/s]Best score: 40.3775: : 208iter [00:07, 33.41iter/s]Best score: 40.3775: : 209iter [00:07, 33.41iter/s]Best score: 40.3775: : 210iter [00:07, 35.23iter/s]Best score: 40.3775: : 210iter [00:07, 35.23iter/s]Best score: 40.3775: : 211iter [00:07, 35.23iter/s]Best score: 40.3775: : 212iter [00:07, 35.23iter/s]Best score: 40.3775: : 213iter [00:07, 35.23iter/s]Best score: 40.3775: : 214iter [00:07, 36.45iter/s]Best score: 40.3775: : 214iter [00:07, 36.45iter/s]Best score: 40.3775: : 215iter [00:07, 36.45iter/s]Best score: 40.3775: : 216iter [00:07, 36.45iter/s]Best score: 40.3775: : 217iter [00:07, 36.45iter/s]Best score: 40.3775: : 218iter [00:07, 36.45iter/s]Best score: 40.3775: : 219iter [00:07, 37.59iter/s]Best score: 40.3775: : 219iter [00:07, 37.59iter/s]Best score: 40.3775: : 220iter [00:07, 37.59iter/s]Best score: 40.3775: : 221iter [00:07, 37.59iter/s]Best score: 40.3775: : 222iter [00:07, 37.59iter/s]Best score: 40.3775: : 223iter [00:07, 37.93iter/s]Best score: 40.3775: : 223iter [00:07, 37.93iter/s]Best score: 40.3775: : 224iter [00:08, 37.93iter/s]Best score: 40.3775: : 225iter [00:08, 37.93iter/s]Best score: 40.3775: : 226iter [00:08, 37.93iter/s]Best score: 40.3775: : 227iter [00:08, 37.93iter/s]Best score: 40.3775: : 228iter [00:08, 38.70iter/s]Best score: 40.3775: : 228iter [00:08, 38.70iter/s]Best score: 40.3775: : 229iter [00:08, 38.70iter/s]Best score: 40.3775: : 230iter [00:08, 38.70iter/s]Best score: 40.3775: : 231iter [00:08, 38.70iter/s]Best score: 40.3775: : 232iter [00:08, 38.75iter/s]Best score: 40.3775: : 232iter [00:08, 38.75iter/s]Best score: 40.3775: : 233iter [00:08, 38.75iter/s]Best score: 40.3775: : 234iter [00:08, 38.75iter/s]Best score: 40.3775: : 235iter [00:08, 38.75iter/s]Best score: 40.3775: : 236iter [00:08, 38.75iter/s]Best score: 40.3775: : 237iter [00:08, 39.27iter/s]Best score: 40.3775: : 237iter [00:08, 39.27iter/s]Best score: 40.3775: : 238iter [00:08, 39.27iter/s]Best score: 40.3775: : 239iter [00:08, 39.27iter/s]Best score: 40.3775: : 240iter [00:08, 39.27iter/s]Best score: 40.3775: : 241iter [00:08, 39.07iter/s]Best score: 40.3775: : 241iter [00:08, 39.07iter/s]Best score: 40.3775: : 242iter [00:08, 39.07iter/s]Best score: 40.3775: : 243iter [00:08, 39.07iter/s]Best score: 40.3775: : 244iter [00:08, 39.07iter/s]Best score: 40.3775: : 245iter [00:08, 39.07iter/s]Best score: 40.3775: : 246iter [00:08, 39.49iter/s]Best score: 40.3775: : 246iter [00:08, 39.49iter/s]Best score: 40.3775: : 247iter [00:08, 39.49iter/s]Best score: 40.3775: : 248iter [00:08, 39.49iter/s]
[ITER 250] Best: 40.3775
[PARAMS] Current best parameters:
  fx: 558.7711
  fy: 554.4115
  px: 970.3963
  py: 743.9871
  k1: 0.00162218
  k2: -0.02973757
  k3: 0.00541127
  k4: 0.00233096
  p1: -0.02386769
  p2: -0.00856927
  p3: -0.00438695
  p4: -0.00967899
  s1: -0.0197
  s2: 0.0171
  s3: 0.0084
  s4: 0.0253
  tilt_x: -0.0280
  tilt_y: 0.0419
  scale: 2.9927
  rotation: -0.2374
Best score: 40.3775: : 249iter [00:08, 39.49iter/s]Best score: 40.3775: : 250iter [00:08, 39.30iter/s]Best score: 40.3775: : 250iter [00:08, 39.30iter/s]Best score: 40.3775: : 251iter [00:08, 39.30iter/s]Best score: 40.3775: : 252iter [00:08, 39.30iter/s]Best score: 40.3775: : 253iter [00:08, 39.30iter/s]Best score: 40.3775: : 254iter [00:08, 31.73iter/s]Best score: 40.3775: : 254iter [00:08, 31.73iter/s]Best score: 40.3775: : 255iter [00:08, 31.73iter/s]Best score: 40.3775: : 256iter [00:08, 31.73iter/s]Best score: 40.3775: : 257iter [00:08, 31.73iter/s]Best score: 40.3775: : 258iter [00:08, 33.65iter/s]Best score: 40.3775: : 258iter [00:08, 33.65iter/s]Best score: 23.5984: : 259iter [00:08, 33.65iter/s]Best score: 23.5984: : 260iter [00:09, 33.65iter/s]Best score: 23.5984: : 261iter [00:09, 33.65iter/s]Best score: 23.5984: : 262iter [00:09, 34.94iter/s]Best score: 23.5984: : 262iter [00:09, 34.94iter/s]Best score: 23.5984: : 263iter [00:09, 34.94iter/s]Best score: 23.5984: : 264iter [00:09, 34.94iter/s]Best score: 23.5984: : 265iter [00:09, 34.94iter/s]Best score: 23.5984: : 266iter [00:09, 34.94iter/s]Best score: 23.5984: : 267iter [00:09, 36.61iter/s]Best score: 23.5984: : 267iter [00:09, 36.61iter/s]Best score: 23.5984: : 268iter [00:09, 36.61iter/s]Best score: 23.5984: : 269iter [00:09, 36.61iter/s]Best score: 23.5984: : 270iter [00:09, 36.61iter/s]Best score: 23.5984: : 271iter [00:09, 37.31iter/s]Best score: 23.5984: : 271iter [00:09, 37.31iter/s]Best score: 23.5984: : 272iter [00:09, 37.31iter/s]Best score: 23.5984: : 273iter [00:09, 37.31iter/s]Best score: 23.5984: : 274iter [00:09, 37.31iter/s]Best score: 23.5984: : 275iter [00:09, 37.92iter/s]Best score: 23.5984: : 275iter [00:09, 37.92iter/s]Best score: 23.5984: : 276iter [00:09, 37.92iter/s]Best score: 23.5984: : 277iter [00:09, 37.92iter/s]Best score: 23.5984: : 278iter [00:09, 37.92iter/s]Best score: 17.3773: : 279iter [00:09, 37.92iter/s]Best score: 17.3773: : 280iter [00:09, 38.60iter/s]Best score: 17.3773: : 280iter [00:09, 38.60iter/s]Best score: 17.3773: : 281iter [00:09, 38.60iter/s]Best score: 17.3773: : 282iter [00:09, 38.60iter/s]Best score: 17.3773: : 283iter [00:09, 38.60iter/s]Best score: 17.3773: : 284iter [00:09, 38.81iter/s]Best score: 17.3773: : 284iter [00:09, 38.81iter/s]Best score: 17.3773: : 285iter [00:09, 38.81iter/s]Best score: 17.3773: : 286iter [00:09, 38.81iter/s]Best score: 17.3773: : 287iter [00:09, 38.81iter/s]Best score: 17.3773: : 288iter [00:09, 39.04iter/s]Best score: 17.3773: : 288iter [00:09, 39.04iter/s]Best score: 12.3798: : 289iter [00:09, 39.04iter/s]Best score: 12.3798: : 290iter [00:09, 39.04iter/s]Best score: 12.3798: : 291iter [00:09, 39.04iter/s]Best score: 12.3798: : 292iter [00:09, 38.84iter/s]Best score: 12.3798: : 292iter [00:09, 38.84iter/s]Best score: 12.3798: : 293iter [00:09, 38.84iter/s]Best score: 12.3798: : 294iter [00:09, 38.84iter/s]Best score: 12.3798: : 295iter [00:09, 38.84iter/s]Best score: 12.3798: : 296iter [00:09, 38.94iter/s]Best score: 12.3798: : 296iter [00:09, 38.94iter/s]Best score: 12.3798: : 297iter [00:09, 38.94iter/s]Best score: 12.3798: : 298iter [00:09, 38.94iter/s]
[ITER 300] Best: 11.5300
[PARAMS] Current best parameters:
  fx: 530.5428
  fy: 527.0385
  px: 979.5206
  py: 745.0312
  k1: 0.09917650
  k2: -0.04360805
  k3: -0.01937577
  k4: 0.00922350
  p1: -0.01745862
  p2: 0.01589592
  p3: -0.01657893
  p4: -0.00808777
  s1: -0.0052
  s2: 0.0094
  s3: -0.0030
  s4: 0.0270
  tilt_x: -0.0071
  tilt_y: 0.0375
  scale: 2.6969
  rotation: -0.6506
Best score: 11.5300: : 299iter [00:10, 38.94iter/s]Best score: 11.5300: : 300iter [00:10, 38.23iter/s]Best score: 11.5300: : 300iter [00:10, 38.23iter/s]Best score: 11.5300: : 301iter [00:10, 38.23iter/s]Best score: 11.5300: : 302iter [00:10, 38.23iter/s]Best score: 11.5300: : 303iter [00:10, 38.23iter/s]Best score: 11.5300: : 304iter [00:10, 31.40iter/s]Best score: 11.5300: : 304iter [00:10, 31.40iter/s]Best score: 11.5300: : 305iter [00:10, 31.40iter/s]Best score: 11.5300: : 306iter [00:10, 31.40iter/s]Best score: 11.5300: : 307iter [00:10, 31.40iter/s]Best score: 11.5300: : 308iter [00:10, 33.43iter/s]Best score: 11.5300: : 308iter [00:10, 33.43iter/s]Best score: 11.5300: : 309iter [00:10, 33.43iter/s]Best score: 11.5300: : 310iter [00:10, 33.43iter/s]Best score: 11.5300: : 311iter [00:10, 33.43iter/s]Best score: 11.5300: : 312iter [00:10, 34.77iter/s]Best score: 11.5300: : 312iter [00:10, 34.77iter/s]Best score: 11.5300: : 313iter [00:10, 34.77iter/s]Best score: 11.5300: : 314iter [00:10, 34.77iter/s]Best score: 11.5300: : 315iter [00:10, 34.77iter/s]Best score: 11.5300: : 316iter [00:10, 36.13iter/s]Best score: 11.5300: : 316iter [00:10, 36.13iter/s]Best score: 11.5300: : 317iter [00:10, 36.13iter/s]Best score: 11.5300: : 318iter [00:10, 36.13iter/s]Best score: 10.1604: : 319iter [00:10, 36.13iter/s]Best score: 10.1604: : 320iter [00:10, 36.85iter/s]Best score: 10.1604: : 320iter [00:10, 36.85iter/s]Best score: 10.1604: : 321iter [00:10, 36.85iter/s]Best score: 10.1604: : 322iter [00:10, 36.85iter/s]Best score: 10.1604: : 323iter [00:10, 36.85iter/s]Best score: 10.1604: : 324iter [00:10, 37.55iter/s]Best score: 10.1604: : 324iter [00:10, 37.55iter/s]Best score: 10.1604: : 325iter [00:10, 37.55iter/s]Best score: 10.1604: : 326iter [00:10, 37.55iter/s]Best score: 10.1604: : 327iter [00:10, 37.55iter/s]Best score: 10.1604: : 328iter [00:10, 38.03iter/s]Best score: 10.1604: : 328iter [00:10, 38.03iter/s]Best score: 10.1604: : 329iter [00:10, 38.03iter/s]Best score: 10.1604: : 330iter [00:10, 38.03iter/s]Best score: 10.1604: : 331iter [00:10, 38.03iter/s]Best score: 10.1604: : 332iter [00:10, 37.93iter/s]Best score: 10.1604: : 332iter [00:10, 37.93iter/s]Best score: 10.1604: : 333iter [00:10, 37.93iter/s]Best score: 10.1604: : 334iter [00:10, 37.93iter/s]Best score: 10.1604: : 335iter [00:11, 37.93iter/s]Best score: 10.1604: : 336iter [00:11, 37.89iter/s]Best score: 10.1604: : 336iter [00:11, 37.89iter/s]Best score: 10.1604: : 337iter [00:11, 37.89iter/s]Best score: 10.1604: : 338iter [00:11, 37.89iter/s]Best score: 5.2407: : 339iter [00:11, 37.89iter/s] Best score: 5.2407: : 340iter [00:11, 38.07iter/s]Best score: 5.2407: : 340iter [00:11, 38.07iter/s]Best score: 5.2407: : 341iter [00:11, 38.07iter/s]Best score: 5.2407: : 342iter [00:11, 38.07iter/s]Best score: 5.2407: : 343iter [00:11, 38.07iter/s]Best score: 5.2407: : 344iter [00:11, 38.61iter/s]Best score: 5.2407: : 344iter [00:11, 38.61iter/s]Best score: 5.2407: : 345iter [00:11, 38.61iter/s]Best score: 5.2407: : 346iter [00:11, 38.61iter/s]Best score: 5.2407: : 347iter [00:11, 38.61iter/s]Best score: 5.2407: : 348iter [00:11, 39.00iter/s]Best score: 5.2407: : 348iter [00:11, 39.00iter/s]
[ITER 350] Best: 5.2407
[PARAMS] Current best parameters:
  fx: 535.6779
  fy: 533.8413
  px: 975.7041
  py: 746.1824
  k1: 0.05552018
  k2: -0.02934614
  k3: -0.00422249
  k4: 0.00226144
  p1: -0.01688636
  p2: 0.00076096
  p3: 0.01013976
  p4: -0.01021296
  s1: -0.0226
  s2: 0.0156
  s3: -0.0064
  s4: 0.0179
  tilt_x: -0.0108
  tilt_y: 0.0360
  scale: 2.7979
  rotation: -0.8812
Best score: 5.2407: : 349iter [00:11, 39.00iter/s]Best score: 5.2407: : 350iter [00:11, 39.00iter/s]Best score: 5.2407: : 351iter [00:11, 39.00iter/s]Best score: 5.2407: : 352iter [00:11, 31.68iter/s]Best score: 5.2407: : 352iter [00:11, 31.68iter/s]Best score: 5.2407: : 353iter [00:11, 31.68iter/s]Best score: 5.2407: : 354iter [00:11, 31.68iter/s]Best score: 5.2407: : 355iter [00:11, 31.68iter/s]Best score: 5.2407: : 356iter [00:11, 31.68iter/s]Best score: 5.2407: : 357iter [00:11, 34.17iter/s]Best score: 5.2407: : 357iter [00:11, 34.17iter/s]Best score: 5.2407: : 358iter [00:11, 34.17iter/s]Best score: 5.1503: : 359iter [00:11, 34.17iter/s]Best score: 5.1503: : 360iter [00:11, 34.17iter/s]Best score: 5.1503: : 361iter [00:11, 35.45iter/s]Best score: 5.1503: : 361iter [00:11, 35.45iter/s]Best score: 5.1503: : 362iter [00:11, 35.45iter/s]Best score: 5.1503: : 363iter [00:11, 35.45iter/s]Best score: 5.1503: : 364iter [00:11, 35.45iter/s]Best score: 5.1503: : 365iter [00:11, 36.65iter/s]Best score: 5.1503: : 365iter [00:11, 36.65iter/s]Best score: 5.1503: : 366iter [00:11, 36.65iter/s]Best score: 5.1503: : 367iter [00:11, 36.65iter/s]Best score: 5.1503: : 368iter [00:11, 36.65iter/s]Best score: 5.1503: : 369iter [00:11, 37.38iter/s]Best score: 3.6982: : 369iter [00:11, 37.38iter/s]Best score: 3.6982: : 370iter [00:11, 37.38iter/s]Best score: 3.6982: : 371iter [00:12, 37.38iter/s]Best score: 3.6982: : 372iter [00:12, 37.38iter/s]Best score: 3.6982: : 373iter [00:12, 37.57iter/s]Best score: 3.6982: : 373iter [00:12, 37.57iter/s]Best score: 3.6982: : 374iter [00:12, 37.57iter/s]Best score: 3.6982: : 375iter [00:12, 37.57iter/s]Best score: 3.6982: : 376iter [00:12, 37.57iter/s]Best score: 3.6982: : 377iter [00:12, 38.23iter/s]Best score: 3.6982: : 377iter [00:12, 38.23iter/s]Best score: 3.6982: : 378iter [00:12, 38.23iter/s]Best score: 1.7296: : 379iter [00:12, 38.23iter/s]Best score: 1.7296: : 380iter [00:12, 38.23iter/s]Best score: 1.7296: : 381iter [00:12, 38.52iter/s]Best score: 1.7296: : 381iter [00:12, 38.52iter/s]Best score: 1.7296: : 382iter [00:12, 38.52iter/s]Best score: 1.7296: : 383iter [00:12, 38.52iter/s]Best score: 1.7296: : 384iter [00:12, 38.52iter/s]Best score: 1.7296: : 385iter [00:12, 38.95iter/s]Best score: 1.7296: : 385iter [00:12, 38.95iter/s]Best score: 1.7296: : 386iter [00:12, 38.95iter/s]Best score: 1.7296: : 387iter [00:12, 38.95iter/s]Best score: 1.7296: : 388iter [00:12, 38.95iter/s]Best score: 1.7296: : 389iter [00:12, 38.81iter/s]Best score: 1.2967: : 389iter [00:12, 38.81iter/s]Best score: 1.2967: : 390iter [00:12, 38.81iter/s]Best score: 1.2967: : 391iter [00:12, 38.81iter/s]Best score: 1.2967: : 392iter [00:12, 38.81iter/s]Best score: 1.2967: : 393iter [00:12, 38.85iter/s]Best score: 1.2967: : 393iter [00:12, 38.85iter/s]Best score: 1.2967: : 394iter [00:12, 38.85iter/s]Best score: 1.2967: : 395iter [00:12, 38.85iter/s]Best score: 1.2967: : 396iter [00:12, 38.85iter/s]Best score: 1.2967: : 397iter [00:12, 39.08iter/s]Best score: 1.2967: : 397iter [00:12, 39.08iter/s]Best score: 1.2967: : 398iter [00:12, 39.08iter/s]
[ITER 400] Best: 1.2967
[PARAMS] Current best parameters:
  fx: 564.3075
  fy: 563.5984
  px: 976.5501
  py: 760.4695
  k1: -0.00656900
  k2: -0.01502180
  k3: -0.00120241
  k4: 0.00207457
  p1: 0.00648073
  p2: 0.00895630
  p3: 0.00693826
  p4: -0.02042155
  s1: -0.0190
  s2: 0.0186
  s3: -0.0031
  s4: 0.0153
  tilt_x: 0.0198
  tilt_y: 0.0442
  scale: 2.9299
  rotation: -0.8125
Best score: 1.2967: : 399iter [00:12, 39.08iter/s]Best score: 1.2967: : 400iter [00:12, 39.08iter/s]Best score: 1.2967: : 401iter [00:12, 24.67iter/s]Best score: 1.2967: : 401iter [00:12, 24.67iter/s]Best score: 1.2967: : 402iter [00:12, 24.67iter/s]Best score: 1.2967: : 403iter [00:13, 24.67iter/s]Best score: 1.2967: : 404iter [00:13, 24.67iter/s]Best score: 1.2967: : 405iter [00:13, 27.80iter/s]Best score: 1.2967: : 405iter [00:13, 27.80iter/s]Best score: 1.2967: : 406iter [00:13, 27.80iter/s]Best score: 1.2967: : 407iter [00:13, 27.80iter/s]Best score: 1.2967: : 408iter [00:13, 27.80iter/s]Best score: 1.2967: : 409iter [00:13, 30.54iter/s]Best score: 1.0786: : 409iter [00:13, 30.54iter/s]Best score: 1.0786: : 410iter [00:13, 30.54iter/s]Best score: 1.0786: : 411iter [00:13, 30.54iter/s]Best score: 1.0786: : 412iter [00:13, 30.54iter/s]Best score: 1.0786: : 413iter [00:13, 32.63iter/s]Best score: 1.0786: : 413iter [00:13, 32.63iter/s]Best score: 1.0786: : 414iter [00:13, 32.63iter/s]Best score: 1.0786: : 415iter [00:13, 32.63iter/s]Best score: 1.0786: : 416iter [00:13, 32.63iter/s]Best score: 1.0786: : 417iter [00:13, 34.44iter/s]Best score: 1.0786: : 417iter [00:13, 34.44iter/s]Best score: 1.0786: : 418iter [00:13, 34.44iter/s]Best score: 1.0786: : 419iter [00:13, 34.44iter/s]Best score: 1.0786: : 420iter [00:13, 34.44iter/s]Best score: 1.0786: : 421iter [00:13, 35.51iter/s]Best score: 1.0786: : 421iter [00:13, 35.51iter/s]Best score: 1.0786: : 422iter [00:13, 35.51iter/s]Best score: 1.0786: : 423iter [00:13, 35.51iter/s]Best score: 1.0786: : 424iter [00:13, 35.51iter/s]Best score: 1.0786: : 425iter [00:13, 36.60iter/s]Best score: 1.0786: : 425iter [00:13, 36.60iter/s]Best score: 1.0786: : 426iter [00:13, 36.60iter/s]Best score: 1.0786: : 427iter [00:13, 36.60iter/s]Best score: 1.0786: : 428iter [00:13, 36.60iter/s]Best score: 1.0786: : 429iter [00:13, 37.37iter/s]Best score: 0.9006: : 429iter [00:13, 37.37iter/s]Best score: 0.9006: : 430iter [00:13, 37.37iter/s]Best score: 0.9006: : 431iter [00:13, 37.37iter/s]Best score: 0.9006: : 432iter [00:13, 37.37iter/s]Best score: 0.9006: : 433iter [00:13, 37.76iter/s]Best score: 0.9006: : 433iter [00:13, 37.76iter/s]Best score: 0.9006: : 434iter [00:13, 37.76iter/s]Best score: 0.9006: : 435iter [00:13, 37.76iter/s]Best score: 0.9006: : 436iter [00:13, 37.76iter/s]Best score: 0.9006: : 437iter [00:13, 38.31iter/s]Best score: 0.9006: : 437iter [00:13, 38.31iter/s]Best score: 0.9006: : 438iter [00:13, 38.31iter/s]Best score: 0.7047: : 439iter [00:13, 38.31iter/s]Best score: 0.7047: : 440iter [00:13, 38.31iter/s]Best score: 0.7047: : 441iter [00:13, 38.40iter/s]Best score: 0.7047: : 441iter [00:13, 38.40iter/s]Best score: 0.7047: : 442iter [00:14, 38.40iter/s]Best score: 0.7047: : 443iter [00:14, 38.40iter/s]Best score: 0.7047: : 444iter [00:14, 38.40iter/s]Best score: 0.7047: : 445iter [00:14, 38.77iter/s]Best score: 0.7047: : 445iter [00:14, 38.77iter/s]Best score: 0.7047: : 446iter [00:14, 38.77iter/s]Best score: 0.7047: : 447iter [00:14, 38.77iter/s]Best score: 0.7047: : 448iter [00:14, 38.77iter/s]Best score: 0.7047: : 449iter [00:14, 39.08iter/s]
[ITER 450] Best: 0.7047
[PARAMS] Current best parameters:
  fx: 564.7680
  fy: 564.6417
  px: 978.8343
  py: 759.1874
  k1: -0.01235121
  k2: -0.01649254
  k3: 0.00661933
  k4: -0.00111246
  p1: 0.00453262
  p2: 0.00947694
  p3: 0.00653426
  p4: -0.01920096
  s1: -0.0153
  s2: 0.0159
  s3: -0.0052
  s4: 0.0204
  tilt_x: 0.0115
  tilt_y: 0.0349
  scale: 2.9404
  rotation: -0.8085
Best score: 0.7047: : 449iter [00:14, 39.08iter/s]Best score: 0.7047: : 450iter [00:14, 39.08iter/s]Best score: 0.7047: : 451iter [00:14, 39.08iter/s]Best score: 0.7047: : 452iter [00:14, 39.08iter/s]Best score: 0.7047: : 453iter [00:14, 31.60iter/s]Best score: 0.7047: : 453iter [00:14, 31.60iter/s]Best score: 0.7047: : 454iter [00:14, 31.60iter/s]Best score: 0.7047: : 455iter [00:14, 31.60iter/s]Best score: 0.7047: : 456iter [00:14, 31.60iter/s]Best score: 0.7047: : 457iter [00:14, 31.60iter/s]Best score: 0.7047: : 458iter [00:14, 34.09iter/s]Best score: 0.7047: : 458iter [00:14, 34.09iter/s]Best score: 0.6239: : 459iter [00:14, 34.09iter/s]Best score: 0.6239: : 460iter [00:14, 34.09iter/s]Best score: 0.6239: : 461iter [00:14, 34.09iter/s]Best score: 0.6239: : 462iter [00:14, 35.33iter/s]Best score: 0.6239: : 462iter [00:14, 35.33iter/s]Best score: 0.6239: : 463iter [00:14, 35.33iter/s]Best score: 0.6239: : 464iter [00:14, 35.33iter/s]Best score: 0.6239: : 465iter [00:14, 35.33iter/s]Best score: 0.6239: : 466iter [00:14, 36.31iter/s]Best score: 0.6239: : 466iter [00:14, 36.31iter/s]Best score: 0.6239: : 467iter [00:14, 36.31iter/s]Best score: 0.6239: : 468iter [00:14, 36.31iter/s]Best score: 0.5752: : 469iter [00:14, 36.31iter/s]Best score: 0.5752: : 470iter [00:14, 36.95iter/s]Best score: 0.5752: : 470iter [00:14, 36.95iter/s]Best score: 0.5752: : 471iter [00:14, 36.95iter/s]Best score: 0.5752: : 472iter [00:14, 36.95iter/s]Best score: 0.5752: : 473iter [00:14, 36.95iter/s]Best score: 0.5752: : 474iter [00:14, 37.78iter/s]Best score: 0.5752: : 474iter [00:14, 37.78iter/s]Best score: 0.5752: : 475iter [00:14, 37.78iter/s]Best score: 0.5752: : 476iter [00:14, 37.78iter/s]Best score: 0.5752: : 477iter [00:14, 37.78iter/s]Best score: 0.5752: : 478iter [00:15, 37.78iter/s]Best score: 0.5752: : 479iter [00:15, 38.54iter/s]Best score: 0.4822: : 479iter [00:15, 38.54iter/s]Best score: 0.4822: : 480iter [00:15, 38.54iter/s]Best score: 0.4822: : 481iter [00:15, 38.54iter/s]Best score: 0.4822: : 482iter [00:15, 38.54iter/s]Best score: 0.4822: : 483iter [00:15, 38.43iter/s]Best score: 0.4822: : 483iter [00:15, 38.43iter/s]Best score: 0.4822: : 484iter [00:15, 38.43iter/s]Best score: 0.4822: : 485iter [00:15, 38.43iter/s]Best score: 0.4822: : 486iter [00:15, 38.43iter/s]Best score: 0.4822: : 487iter [00:15, 38.83iter/s]Best score: 0.4822: : 487iter [00:15, 38.83iter/s]Best score: 0.4822: : 488iter [00:15, 38.83iter/s]Best score: 0.4221: : 489iter [00:15, 38.83iter/s]Best score: 0.4221: : 490iter [00:15, 38.83iter/s]Best score: 0.4221: : 491iter [00:15, 38.76iter/s]Best score: 0.4221: : 491iter [00:15, 38.76iter/s]Best score: 0.4221: : 492iter [00:15, 38.76iter/s]Best score: 0.4221: : 493iter [00:15, 38.76iter/s]Best score: 0.4221: : 494iter [00:15, 38.76iter/s]Best score: 0.4221: : 495iter [00:15, 38.93iter/s]Best score: 0.4221: : 495iter [00:15, 38.93iter/s]Best score: 0.4221: : 496iter [00:15, 38.93iter/s]Best score: 0.4221: : 497iter [00:15, 38.93iter/s]Best score: 0.4221: : 498iter [00:15, 38.93iter/s]
[ITER 500] Best: 0.4013
[PARAMS] Current best parameters:
  fx: 563.8720
  fy: 563.5549
  px: 978.9731
  py: 760.6510
  k1: -0.03472820
  k2: 0.00344291
  k3: 0.00374931
  k4: -0.00200655
  p1: 0.00980874
  p2: 0.00734598
  p3: 0.00705494
  p4: -0.02254248
  s1: -0.0165
  s2: 0.0213
  s3: -0.0127
  s4: 0.0234
  tilt_x: 0.0113
  tilt_y: 0.0305
  scale: 2.9937
  rotation: -0.8350
Best score: 0.4013: : 499iter [00:15, 38.93iter/s]Best score: 0.4013: : 500iter [00:15, 39.08iter/s]Best score: 0.4013: : 500iter [00:15, 39.08iter/s]Best score: 0.4013: : 501iter [00:15, 39.08iter/s]Best score: 0.4013: : 502iter [00:15, 39.08iter/s]Best score: 0.4013: : 503iter [00:15, 39.08iter/s]Best score: 0.4013: : 504iter [00:15, 32.24iter/s]Best score: 0.4013: : 504iter [00:15, 32.24iter/s]Best score: 0.4013: : 505iter [00:15, 32.24iter/s]Best score: 0.4013: : 506iter [00:15, 32.24iter/s]Best score: 0.4013: : 507iter [00:15, 32.24iter/s]Best score: 0.4013: : 508iter [00:15, 34.07iter/s]Best score: 0.4013: : 508iter [00:15, 34.07iter/s]Best score: 0.3783: : 509iter [00:15, 34.07iter/s]Best score: 0.3783: : 510iter [00:15, 34.07iter/s]Best score: 0.3783: : 511iter [00:15, 34.07iter/s]Best score: 0.3783: : 512iter [00:15, 35.22iter/s]Best score: 0.3783: : 512iter [00:15, 35.22iter/s]Best score: 0.3783: : 513iter [00:15, 35.22iter/s]Best score: 0.3783: : 514iter [00:16, 35.22iter/s]Best score: 0.3783: : 515iter [00:16, 35.22iter/s]Best score: 0.3783: : 516iter [00:16, 36.41iter/s]Best score: 0.3783: : 516iter [00:16, 36.41iter/s]Best score: 0.3783: : 517iter [00:16, 36.41iter/s]Best score: 0.3783: : 518iter [00:16, 36.41iter/s]Best score: 0.3727: : 519iter [00:16, 36.41iter/s]Best score: 0.3727: : 520iter [00:16, 37.08iter/s]Best score: 0.3727: : 520iter [00:16, 37.08iter/s]Best score: 0.3727: : 521iter [00:16, 37.08iter/s]Best score: 0.3727: : 522iter [00:16, 37.08iter/s]Best score: 0.3727: : 523iter [00:16, 37.08iter/s]Best score: 0.3727: : 524iter [00:16, 37.84iter/s]Best score: 0.3727: : 524iter [00:16, 37.84iter/s]Best score: 0.3727: : 525iter [00:16, 37.84iter/s]Best score: 0.3727: : 526iter [00:16, 37.84iter/s]Best score: 0.3727: : 527iter [00:16, 37.84iter/s]Best score: 0.3727: : 528iter [00:16, 38.31iter/s]Best score: 0.3727: : 528iter [00:16, 38.31iter/s]Best score: 0.3516: : 529iter [00:16, 38.31iter/s]Best score: 0.3516: : 530iter [00:16, 38.31iter/s]Best score: 0.3516: : 531iter [00:16, 38.31iter/s]Best score: 0.3516: : 532iter [00:16, 38.45iter/s]Best score: 0.3516: : 532iter [00:16, 38.45iter/s]Best score: 0.3516: : 533iter [00:16, 38.45iter/s]Best score: 0.3516: : 534iter [00:16, 38.45iter/s]Best score: 0.3516: : 535iter [00:16, 38.45iter/s]Best score: 0.3516: : 536iter [00:16, 38.80iter/s]Best score: 0.3516: : 536iter [00:16, 38.80iter/s]Best score: 0.3516: : 537iter [00:16, 38.80iter/s]Best score: 0.3516: : 538iter [00:16, 38.80iter/s]Best score: 0.3248: : 539iter [00:16, 38.80iter/s]Best score: 0.3248: : 540iter [00:16, 38.73iter/s]Best score: 0.3248: : 540iter [00:16, 38.73iter/s]Best score: 0.3248: : 541iter [00:16, 38.73iter/s]Best score: 0.3248: : 542iter [00:16, 38.73iter/s]Best score: 0.3248: : 543iter [00:16, 38.73iter/s]Best score: 0.3248: : 544iter [00:16, 38.75iter/s]Best score: 0.3248: : 544iter [00:16, 38.75iter/s]Best score: 0.3248: : 545iter [00:16, 38.75iter/s]Best score: 0.3248: : 546iter [00:16, 38.75iter/s]Best score: 0.3248: : 547iter [00:16, 38.75iter/s]Best score: 0.3248: : 548iter [00:16, 39.06iter/s]Best score: 0.3248: : 548iter [00:16, 39.06iter/s]
[ITER 550] Best: 0.3008
[PARAMS] Current best parameters:
  fx: 558.6666
  fy: 558.3571
  px: 982.8735
  py: 759.7748
  k1: -0.02982371
  k2: 0.00050004
  k3: 0.00647511
  k4: -0.00274021
  p1: 0.00709748
  p2: 0.00655502
  p3: 0.01411296
  p4: -0.02088976
  s1: -0.0204
  s2: 0.0202
  s3: -0.0156
  s4: 0.0208
  tilt_x: 0.0107
  tilt_y: 0.0076
  scale: 2.9985
  rotation: -0.8681
Best score: 0.3008: : 549iter [00:16, 39.06iter/s]Best score: 0.3008: : 550iter [00:17, 39.06iter/s]Best score: 0.3008: : 551iter [00:17, 39.06iter/s]Best score: 0.3008: : 552iter [00:17, 31.59iter/s]Best score: 0.3008: : 552iter [00:17, 31.59iter/s]Best score: 0.3008: : 553iter [00:17, 31.59iter/s]Best score: 0.3008: : 554iter [00:17, 31.59iter/s]Best score: 0.3008: : 555iter [00:17, 31.59iter/s]Best score: 0.3008: : 556iter [00:17, 33.52iter/s]Best score: 0.3008: : 556iter [00:17, 33.52iter/s]Best score: 0.3008: : 557iter [00:17, 33.52iter/s]Best score: 0.3008: : 558iter [00:17, 33.52iter/s]Best score: 0.3008: : 559iter [00:17, 33.52iter/s]Best score: 0.3008: : 560iter [00:17, 34.87iter/s]Best score: 0.3008: : 560iter [00:17, 34.87iter/s]Best score: 0.3008: : 561iter [00:17, 34.87iter/s]Best score: 0.3008: : 562iter [00:17, 34.87iter/s]Best score: 0.3008: : 563iter [00:17, 34.87iter/s]Best score: 0.3008: : 564iter [00:17, 36.05iter/s]Best score: 0.3008: : 564iter [00:17, 36.05iter/s]Best score: 0.3008: : 565iter [00:17, 36.05iter/s]Best score: 0.3008: : 566iter [00:17, 36.05iter/s]Best score: 0.3008: : 567iter [00:17, 36.05iter/s]Best score: 0.3008: : 568iter [00:17, 36.90iter/s]Best score: 0.3008: : 568iter [00:17, 36.90iter/s]Best score: 0.3008: : 569iter [00:17, 36.90iter/s]Best score: 0.3008: : 570iter [00:17, 36.90iter/s]Best score: 0.3008: : 571iter [00:17, 36.90iter/s]Best score: 0.3008: : 572iter [00:17, 37.38iter/s]Best score: 0.3008: : 572iter [00:17, 37.38iter/s]Best score: 0.3008: : 573iter [00:17, 37.38iter/s]Best score: 0.3008: : 574iter [00:17, 37.38iter/s]Best score: 0.3008: : 575iter [00:17, 37.38iter/s]Best score: 0.3008: : 576iter [00:17, 37.81iter/s]Best score: 0.3008: : 576iter [00:17, 37.81iter/s]Best score: 0.3008: : 577iter [00:17, 37.81iter/s]Best score: 0.3008: : 578iter [00:17, 37.81iter/s]Best score: 0.3008: : 579iter [00:17, 37.81iter/s]Best score: 0.3008: : 580iter [00:17, 38.19iter/s]Best score: 0.3008: : 580iter [00:17, 38.19iter/s]Best score: 0.3008: : 581iter [00:17, 38.19iter/s]Best score: 0.3008: : 582iter [00:17, 38.19iter/s]Best score: 0.3008: : 583iter [00:17, 38.19iter/s]Best score: 0.3008: : 584iter [00:17, 38.19iter/s]Best score: 0.3008: : 585iter [00:17, 38.84iter/s]Best score: 0.3008: : 585iter [00:17, 38.84iter/s]Best score: 0.3008: : 586iter [00:17, 38.84iter/s]Best score: 0.3008: : 587iter [00:17, 38.84iter/s]Best score: 0.3008: : 588iter [00:17, 38.84iter/s]Best score: 0.3008: : 589iter [00:17, 39.00iter/s]Best score: 0.2973: : 589iter [00:18, 39.00iter/s]Best score: 0.2973: : 590iter [00:18, 39.00iter/s]Best score: 0.2973: : 591iter [00:18, 39.00iter/s]Best score: 0.2973: : 592iter [00:18, 39.00iter/s]Best score: 0.2973: : 593iter [00:18, 38.80iter/s]Best score: 0.2973: : 593iter [00:18, 38.80iter/s]Best score: 0.2973: : 594iter [00:18, 38.80iter/s]Best score: 0.2973: : 595iter [00:18, 38.80iter/s]Best score: 0.2973: : 596iter [00:18, 38.80iter/s]Best score: 0.2973: : 597iter [00:18, 39.10iter/s]Best score: 0.2973: : 597iter [00:18, 39.10iter/s]Best score: 0.2973: : 598iter [00:18, 39.10iter/s]
[ITER 600] Best: 0.2528
[PARAMS] Current best parameters:
  fx: 558.6808
  fy: 558.3827
  px: 984.2792
  py: 758.5289
  k1: -0.02647833
  k2: -0.00001979
  k3: 0.00503140
  k4: -0.00228535
  p1: 0.00503618
  p2: 0.00608808
  p3: 0.01443832
  p4: -0.01836329
  s1: -0.0181
  s2: 0.0177
  s3: -0.0138
  s4: 0.0173
  tilt_x: 0.0090
  tilt_y: -0.0002
  scale: 2.9831
  rotation: -0.8495
Best score: 0.2528: : 599iter [00:18, 39.10iter/s]Best score: 0.2528: : 600iter [00:18, 39.10iter/s]Best score: 0.2528: : 601iter [00:18, 31.61iter/s]Best score: 0.2528: : 601iter [00:18, 31.61iter/s]Best score: 0.2528: : 602iter [00:18, 31.61iter/s]Best score: 0.2528: : 603iter [00:18, 31.61iter/s]Best score: 0.2528: : 604iter [00:18, 31.61iter/s]Best score: 0.2528: : 605iter [00:18, 31.61iter/s]Best score: 0.2528: : 606iter [00:18, 34.08iter/s]Best score: 0.2528: : 606iter [00:18, 34.08iter/s]Best score: 0.2528: : 607iter [00:18, 34.08iter/s]Best score: 0.2528: : 608iter [00:18, 34.08iter/s]Best score: 0.2528: : 609iter [00:18, 34.08iter/s]Best score: 0.2528: : 610iter [00:18, 35.31iter/s]Best score: 0.2528: : 610iter [00:18, 35.31iter/s]Best score: 0.2528: : 611iter [00:18, 35.31iter/s]Best score: 0.2528: : 612iter [00:18, 35.31iter/s]Best score: 0.2528: : 613iter [00:18, 35.31iter/s]Best score: 0.2528: : 614iter [00:18, 36.34iter/s]Best score: 0.2528: : 614iter [00:18, 36.34iter/s]Best score: 0.2528: : 615iter [00:18, 36.34iter/s]Best score: 0.2528: : 616iter [00:18, 36.34iter/s]Best score: 0.2528: : 617iter [00:18, 36.34iter/s]Best score: 0.2528: : 618iter [00:18, 37.27iter/s]Best score: 0.2528: : 618iter [00:18, 37.27iter/s]Best score: 0.2528: : 619iter [00:18, 37.27iter/s]Best score: 0.2528: : 620iter [00:18, 37.27iter/s]Best score: 0.2528: : 621iter [00:18, 37.27iter/s]Best score: 0.2528: : 622iter [00:18, 37.60iter/s]Best score: 0.2528: : 622iter [00:18, 37.60iter/s]Best score: 0.2528: : 623iter [00:18, 37.60iter/s]Best score: 0.2528: : 624iter [00:18, 37.60iter/s]Best score: 0.2528: : 625iter [00:18, 37.60iter/s]Best score: 0.2528: : 626iter [00:18, 38.12iter/s]Best score: 0.2528: : 626iter [00:19, 38.12iter/s]Best score: 0.2528: : 627iter [00:19, 38.12iter/s]Best score: 0.2528: : 628iter [00:19, 38.12iter/s]Best score: 0.2528: : 629iter [00:19, 38.12iter/s]Best score: 0.2528: : 630iter [00:19, 38.11iter/s]Best score: 0.2528: : 630iter [00:19, 38.11iter/s]Best score: 0.2528: : 631iter [00:19, 38.11iter/s]Best score: 0.2528: : 632iter [00:19, 38.11iter/s]Best score: 0.2528: : 633iter [00:19, 38.11iter/s]Best score: 0.2528: : 634iter [00:19, 38.62iter/s]Best score: 0.2528: : 634iter [00:19, 38.62iter/s]Best score: 0.2528: : 635iter [00:19, 38.62iter/s]Best score: 0.2528: : 636iter [00:19, 38.62iter/s]Best score: 0.2528: : 637iter [00:19, 38.62iter/s]Best score: 0.2528: : 638iter [00:19, 38.91iter/s]Best score: 0.2528: : 638iter [00:19, 38.91iter/s]Best score: 0.2469: : 639iter [00:19, 38.91iter/s]Best score: 0.2469: : 640iter [00:19, 38.91iter/s]Best score: 0.2469: : 641iter [00:19, 38.91iter/s]Best score: 0.2469: : 642iter [00:19, 38.66iter/s]Best score: 0.2469: : 642iter [00:19, 38.66iter/s]Best score: 0.2469: : 643iter [00:19, 38.66iter/s]Best score: 0.2469: : 644iter [00:19, 38.66iter/s]Best score: 0.2469: : 645iter [00:19, 38.66iter/s]Best score: 0.2469: : 646iter [00:19, 38.99iter/s]Best score: 0.2469: : 646iter [00:19, 38.99iter/s]Best score: 0.2469: : 647iter [00:19, 38.99iter/s]Best score: 0.2469: : 648iter [00:19, 38.99iter/s]
[ITER 650] Best: 0.2432
[PARAMS] Current best parameters:
  fx: 560.4328
  fy: 560.2205
  px: 984.0112
  py: 757.5619
  k1: -0.02676528
  k2: 0.00264390
  k3: 0.00082415
  k4: -0.00092252
  p1: 0.00418051
  p2: 0.00502014
  p3: 0.01361658
  p4: -0.01683540
  s1: -0.0160
  s2: 0.0159
  s3: -0.0130
  s4: 0.0157
  tilt_x: 0.0055
  tilt_y: -0.0011
  scale: 2.9747
  rotation: -0.8568
Best score: 0.2432: : 649iter [00:19, 38.99iter/s]Best score: 0.2432: : 650iter [00:19, 38.84iter/s]Best score: 0.2432: : 650iter [00:19, 38.84iter/s]Best score: 0.2432: : 651iter [00:19, 38.84iter/s]Best score: 0.2432: : 652iter [00:19, 38.84iter/s]Best score: 0.2432: : 653iter [00:19, 38.84iter/s]Best score: 0.2432: : 654iter [00:19, 31.38iter/s]Best score: 0.2432: : 654iter [00:19, 31.38iter/s]Best score: 0.2432: : 655iter [00:19, 31.38iter/s]Best score: 0.2432: : 656iter [00:19, 31.38iter/s]Best score: 0.2432: : 657iter [00:19, 31.38iter/s]Best score: 0.2432: : 658iter [00:19, 33.51iter/s]Best score: 0.2432: : 658iter [00:19, 33.51iter/s]Best score: 0.2412: : 659iter [00:19, 33.51iter/s]Best score: 0.2412: : 660iter [00:19, 33.51iter/s]Best score: 0.2412: : 661iter [00:20, 33.51iter/s]Best score: 0.2412: : 662iter [00:20, 34.96iter/s]Best score: 0.2412: : 662iter [00:20, 34.96iter/s]Best score: 0.2412: : 663iter [00:20, 34.96iter/s]Best score: 0.2412: : 664iter [00:20, 34.96iter/s]Best score: 0.2412: : 665iter [00:20, 34.96iter/s]Best score: 0.2412: : 666iter [00:20, 36.32iter/s]Best score: 0.2412: : 666iter [00:20, 36.32iter/s]Best score: 0.2412: : 667iter [00:20, 36.32iter/s]Best score: 0.2412: : 668iter [00:20, 36.32iter/s]Best score: 0.2412: : 669iter [00:20, 36.32iter/s]Best score: 0.2412: : 670iter [00:20, 37.04iter/s]Best score: 0.2412: : 670iter [00:20, 37.04iter/s]Best score: 0.2412: : 671iter [00:20, 37.04iter/s]Best score: 0.2412: : 672iter [00:20, 37.04iter/s]Best score: 0.2412: : 673iter [00:20, 37.04iter/s]Best score: 0.2412: : 674iter [00:20, 37.04iter/s]Best score: 0.2412: : 675iter [00:20, 38.02iter/s]Best score: 0.2412: : 675iter [00:20, 38.02iter/s]Best score: 0.2412: : 676iter [00:20, 38.02iter/s]Best score: 0.2412: : 677iter [00:20, 38.02iter/s]Best score: 0.2412: : 678iter [00:20, 38.02iter/s]Best score: 0.2412: : 679iter [00:20, 38.40iter/s]Best score: 0.2322: : 679iter [00:20, 38.40iter/s]Best score: 0.2322: : 680iter [00:20, 38.40iter/s]Best score: 0.2322: : 681iter [00:20, 38.40iter/s]Best score: 0.2322: : 682iter [00:20, 38.40iter/s]Best score: 0.2322: : 683iter [00:20, 38.55iter/s]Best score: 0.2322: : 683iter [00:20, 38.55iter/s]Best score: 0.2322: : 684iter [00:20, 38.55iter/s]Best score: 0.2322: : 685iter [00:20, 38.55iter/s]Best score: 0.2322: : 686iter [00:20, 38.55iter/s]Best score: 0.2322: : 687iter [00:20, 38.55iter/s]Best score: 0.2322: : 688iter [00:20, 39.07iter/s]Best score: 0.2322: : 688iter [00:20, 39.07iter/s]Best score: 0.2183: : 689iter [00:20, 39.07iter/s]Best score: 0.2183: : 690iter [00:20, 39.07iter/s]Best score: 0.2183: : 691iter [00:20, 39.07iter/s]Best score: 0.2183: : 692iter [00:20, 38.97iter/s]Best score: 0.2183: : 692iter [00:20, 38.97iter/s]Best score: 0.2183: : 693iter [00:20, 38.97iter/s]Best score: 0.2183: : 694iter [00:20, 38.97iter/s]Best score: 0.2183: : 695iter [00:20, 38.97iter/s]Best score: 0.2183: : 696iter [00:20, 39.14iter/s]Best score: 0.2183: : 696iter [00:20, 39.14iter/s]Best score: 0.2183: : 697iter [00:20, 39.14iter/s]Best score: 0.2183: : 698iter [00:20, 39.14iter/s]
[ITER 700] Best: 0.2152
[PARAMS] Current best parameters:
  fx: 567.3499
  fy: 567.0402
  px: 982.9751
  py: 756.0620
  k1: -0.04135784
  k2: 0.00974792
  k3: -0.00061790
  k4: -0.00081115
  p1: 0.00370626
  p2: 0.00109285
  p3: 0.01701181
  p4: -0.01232856
  s1: -0.0175
  s2: 0.0120
  s3: -0.0193
  s4: 0.0128
  tilt_x: -0.0015
  tilt_y: -0.0044
  scale: 2.9902
  rotation: -0.8551
Best score: 0.2152: : 699iter [00:20, 39.14iter/s]Best score: 0.2152: : 700iter [00:20, 39.05iter/s]Best score: 0.2152: : 700iter [00:21, 39.05iter/s]Best score: 0.2152: : 701iter [00:21, 39.05iter/s]Best score: 0.2152: : 702iter [00:21, 39.05iter/s]Best score: 0.2152: : 703iter [00:21, 39.05iter/s]Best score: 0.2152: : 704iter [00:21, 31.99iter/s]Best score: 0.2152: : 704iter [00:21, 31.99iter/s]Best score: 0.2152: : 705iter [00:21, 31.99iter/s]Best score: 0.2152: : 706iter [00:21, 31.99iter/s]Best score: 0.2152: : 707iter [00:21, 31.99iter/s]Best score: 0.2152: : 708iter [00:21, 33.92iter/s]Best score: 0.2152: : 708iter [00:21, 33.92iter/s]Best score: 0.2112: : 709iter [00:21, 33.92iter/s]Best score: 0.2112: : 710iter [00:21, 33.92iter/s]Best score: 0.2112: : 711iter [00:21, 33.92iter/s]Best score: 0.2112: : 712iter [00:21, 35.19iter/s]Best score: 0.2112: : 712iter [00:21, 35.19iter/s]Best score: 0.2112: : 713iter [00:21, 35.19iter/s]Best score: 0.2112: : 714iter [00:21, 35.19iter/s]Best score: 0.2112: : 715iter [00:21, 35.19iter/s]Best score: 0.2112: : 716iter [00:21, 27.22iter/s]Best score: 0.2112: : 716iter [00:21, 27.22iter/s]Best score: 0.2112: : 717iter [00:21, 27.22iter/s]Best score: 0.2112: : 718iter [00:21, 27.22iter/s]Best score: 0.1976: : 719iter [00:21, 27.22iter/s]Best score: 0.1976: : 720iter [00:21, 29.83iter/s]Best score: 0.1976: : 720iter [00:21, 29.83iter/s]Best score: 0.1976: : 721iter [00:21, 29.83iter/s]Best score: 0.1976: : 722iter [00:21, 29.83iter/s]Best score: 0.1976: : 723iter [00:21, 29.83iter/s]Best score: 0.1976: : 724iter [00:21, 32.10iter/s]Best score: 0.1976: : 724iter [00:21, 32.10iter/s]Best score: 0.1976: : 725iter [00:21, 32.10iter/s]Best score: 0.1976: : 726iter [00:21, 32.10iter/s]Best score: 0.1976: : 727iter [00:21, 32.10iter/s]Best score: 0.1976: : 728iter [00:21, 33.85iter/s]Best score: 0.1976: : 728iter [00:21, 33.85iter/s]Best score: 0.1946: : 729iter [00:21, 33.85iter/s]Best score: 0.1946: : 730iter [00:21, 33.85iter/s]Best score: 0.1946: : 731iter [00:21, 33.85iter/s]Best score: 0.1946: : 732iter [00:21, 35.06iter/s]Best score: 0.1946: : 732iter [00:22, 35.06iter/s]Best score: 0.1946: : 733iter [00:22, 35.06iter/s]Best score: 0.1946: : 734iter [00:22, 35.06iter/s]Best score: 0.1946: : 735iter [00:22, 35.06iter/s]Best score: 0.1946: : 736iter [00:22, 36.04iter/s]Best score: 0.1946: : 736iter [00:22, 36.04iter/s]Best score: 0.1946: : 737iter [00:22, 36.04iter/s]Best score: 0.1946: : 738iter [00:22, 36.04iter/s]Best score: 0.1859: : 739iter [00:22, 36.04iter/s]Best score: 0.1859: : 740iter [00:22, 36.63iter/s]Best score: 0.1859: : 740iter [00:22, 36.63iter/s]Best score: 0.1859: : 741iter [00:22, 36.63iter/s]Best score: 0.1859: : 742iter [00:22, 36.63iter/s]Best score: 0.1859: : 743iter [00:22, 36.63iter/s]Best score: 0.1859: : 744iter [00:22, 37.32iter/s]Best score: 0.1859: : 744iter [00:22, 37.32iter/s]Best score: 0.1859: : 745iter [00:22, 37.32iter/s]Best score: 0.1859: : 746iter [00:22, 37.32iter/s]Best score: 0.1859: : 747iter [00:22, 37.32iter/s]Best score: 0.1859: : 748iter [00:22, 37.46iter/s]Best score: 0.1859: : 748iter [00:22, 37.46iter/s]
[ITER 750] Best: 0.1859
[PARAMS] Current best parameters:
  fx: 567.5076
  fy: 567.2795
  px: 981.1043
  py: 752.0070
  k1: -0.05096465
  k2: 0.02030239
  k3: -0.00413002
  k4: -0.00058704
  p1: -0.00409941
  p2: -0.00588396
  p3: 0.02419215
  p4: -0.00824192
  s1: -0.0182
  s2: 0.0073
  s3: -0.0210
  s4: 0.0076
  tilt_x: -0.0073
  tilt_y: -0.0086
  scale: 3.0055
  rotation: -0.8614
Best score: 0.1859: : 749iter [00:22, 37.46iter/s]Best score: 0.1859: : 750iter [00:22, 37.46iter/s]Best score: 0.1859: : 751iter [00:22, 37.46iter/s]Best score: 0.1859: : 752iter [00:22, 30.79iter/s]Best score: 0.1859: : 752iter [00:22, 30.79iter/s]Best score: 0.1859: : 753iter [00:22, 30.79iter/s]Best score: 0.1859: : 754iter [00:22, 30.79iter/s]Best score: 0.1859: : 755iter [00:22, 30.79iter/s]Best score: 0.1859: : 756iter [00:22, 32.86iter/s]Best score: 0.1859: : 756iter [00:22, 32.86iter/s]Best score: 0.1859: : 757iter [00:22, 32.86iter/s]Best score: 0.1859: : 758iter [00:22, 32.86iter/s]Best score: 0.1848: : 759iter [00:22, 32.86iter/s]Best score: 0.1848: : 760iter [00:22, 34.39iter/s]Best score: 0.1848: : 760iter [00:22, 34.39iter/s]Best score: 0.1848: : 761iter [00:22, 34.39iter/s]Best score: 0.1848: : 762iter [00:22, 34.39iter/s]Best score: 0.1848: : 763iter [00:22, 34.39iter/s]Best score: 0.1848: : 764iter [00:22, 35.69iter/s]Best score: 0.1848: : 764iter [00:22, 35.69iter/s]Best score: 0.1848: : 765iter [00:22, 35.69iter/s]Best score: 0.1848: : 766iter [00:22, 35.69iter/s]Best score: 0.1848: : 767iter [00:23, 35.69iter/s]Best score: 0.1848: : 768iter [00:23, 36.63iter/s]Best score: 0.1848: : 768iter [00:23, 36.63iter/s]Best score: 0.1833: : 769iter [00:23, 36.63iter/s]Best score: 0.1833: : 770iter [00:23, 36.63iter/s]Best score: 0.1833: : 771iter [00:23, 36.63iter/s]Best score: 0.1833: : 772iter [00:23, 37.22iter/s]Best score: 0.1833: : 772iter [00:23, 37.22iter/s]Best score: 0.1833: : 773iter [00:23, 37.22iter/s]Best score: 0.1833: : 774iter [00:23, 37.22iter/s]Best score: 0.1833: : 775iter [00:23, 37.22iter/s]Best score: 0.1833: : 776iter [00:23, 37.82iter/s]Best score: 0.1833: : 776iter [00:23, 37.82iter/s]Best score: 0.1833: : 777iter [00:23, 37.82iter/s]Best score: 0.1833: : 778iter [00:23, 37.82iter/s]Best score: 0.1803: : 779iter [00:23, 37.82iter/s]Best score: 0.1803: : 780iter [00:23, 38.03iter/s]Best score: 0.1803: : 780iter [00:23, 38.03iter/s]Best score: 0.1803: : 781iter [00:23, 38.03iter/s]Best score: 0.1803: : 782iter [00:23, 38.03iter/s]Best score: 0.1803: : 783iter [00:23, 38.03iter/s]Best score: 0.1803: : 784iter [00:23, 38.26iter/s]Best score: 0.1803: : 784iter [00:23, 38.26iter/s]Best score: 0.1803: : 785iter [00:23, 38.26iter/s]Best score: 0.1803: : 786iter [00:23, 38.26iter/s]Best score: 0.1803: : 787iter [00:23, 38.26iter/s]Best score: 0.1803: : 788iter [00:23, 38.32iter/s]Best score: 0.1803: : 788iter [00:23, 38.32iter/s]Best score: 0.1792: : 789iter [00:23, 38.32iter/s]Best score: 0.1792: : 790iter [00:23, 38.32iter/s]Best score: 0.1792: : 791iter [00:23, 38.32iter/s]Best score: 0.1792: : 792iter [00:23, 38.02iter/s]Best score: 0.1792: : 792iter [00:23, 38.02iter/s]Best score: 0.1792: : 793iter [00:23, 38.02iter/s]Best score: 0.1792: : 794iter [00:23, 38.02iter/s]Best score: 0.1792: : 795iter [00:23, 38.02iter/s]Best score: 0.1792: : 796iter [00:23, 38.45iter/s]Best score: 0.1792: : 796iter [00:23, 38.45iter/s]Best score: 0.1792: : 797iter [00:23, 38.45iter/s]Best score: 0.1792: : 798iter [00:23, 38.45iter/s]
[ITER 800] Best: 0.1786
[PARAMS] Current best parameters:
  fx: 567.7536
  fy: 567.5143
  px: 981.7311
  py: 752.0788
  k1: -0.05065954
  k2: 0.02154279
  k3: -0.00592651
  k4: -0.00003343
  p1: -0.00072574
  p2: -0.00400646
  p3: 0.02115755
  p4: -0.01061917
  s1: -0.0170
  s2: 0.0100
  s3: -0.0219
  s4: 0.0103
  tilt_x: -0.0137
  tilt_y: -0.0076
  scale: 3.0018
  rotation: -0.8530
Best score: 0.1786: : 799iter [00:23, 38.45iter/s]Best score: 0.1786: : 800iter [00:23, 38.01iter/s]Best score: 0.1786: : 800iter [00:23, 38.01iter/s]Best score: 0.1786: : 801iter [00:23, 38.01iter/s]Best score: 0.1786: : 802iter [00:23, 38.01iter/s]Best score: 0.1786: : 803iter [00:24, 38.01iter/s]Best score: 0.1786: : 804iter [00:24, 31.12iter/s]Best score: 0.1786: : 804iter [00:24, 31.12iter/s]Best score: 0.1786: : 805iter [00:24, 31.12iter/s]Best score: 0.1786: : 806iter [00:24, 31.12iter/s]Best score: 0.1786: : 807iter [00:24, 31.12iter/s]Best score: 0.1786: : 808iter [00:24, 33.12iter/s]Best score: 0.1786: : 808iter [00:24, 33.12iter/s]Best score: 0.1768: : 809iter [00:24, 33.12iter/s]Best score: 0.1768: : 810iter [00:24, 33.12iter/s]Best score: 0.1768: : 811iter [00:24, 33.12iter/s]Best score: 0.1768: : 812iter [00:24, 34.51iter/s]Best score: 0.1768: : 812iter [00:24, 34.51iter/s]Best score: 0.1768: : 813iter [00:24, 34.51iter/s]Best score: 0.1768: : 814iter [00:24, 34.51iter/s]Best score: 0.1768: : 815iter [00:24, 34.51iter/s]Best score: 0.1768: : 816iter [00:24, 35.69iter/s]Best score: 0.1768: : 816iter [00:24, 35.69iter/s]Best score: 0.1768: : 817iter [00:24, 35.69iter/s]Best score: 0.1768: : 818iter [00:24, 35.69iter/s]Best score: 0.1767: : 819iter [00:24, 35.69iter/s]Best score: 0.1767: : 820iter [00:24, 36.39iter/s]Best score: 0.1767: : 820iter [00:24, 36.39iter/s]Best score: 0.1767: : 821iter [00:24, 36.39iter/s]Best score: 0.1767: : 822iter [00:24, 36.39iter/s]Best score: 0.1767: : 823iter [00:24, 36.39iter/s]Best score: 0.1767: : 824iter [00:24, 37.19iter/s]Best score: 0.1767: : 824iter [00:24, 37.19iter/s]Best score: 0.1767: : 825iter [00:24, 37.19iter/s]Best score: 0.1767: : 826iter [00:24, 37.19iter/s]Best score: 0.1767: : 827iter [00:24, 37.19iter/s]Best score: 0.1767: : 828iter [00:24, 37.74iter/s]Best score: 0.1767: : 828iter [00:24, 37.74iter/s]Best score: 0.1767: : 829iter [00:24, 37.74iter/s]Best score: 0.1767: : 830iter [00:24, 37.74iter/s]Best score: 0.1767: : 831iter [00:24, 37.74iter/s]Best score: 0.1767: : 832iter [00:24, 37.93iter/s]Best score: 0.1767: : 832iter [00:24, 37.93iter/s]Best score: 0.1767: : 833iter [00:24, 37.93iter/s]Best score: 0.1767: : 834iter [00:24, 37.93iter/s]Best score: 0.1767: : 835iter [00:24, 37.93iter/s]Best score: 0.1767: : 836iter [00:24, 38.28iter/s]Best score: 0.1767: : 836iter [00:24, 38.28iter/s]Best score: 0.1767: : 837iter [00:24, 38.28iter/s]Best score: 0.1767: : 838iter [00:24, 38.28iter/s]Best score: 0.1767: : 839iter [00:24, 38.28iter/s]Best score: 0.1767: : 840iter [00:24, 38.41iter/s]Best score: 0.1767: : 840iter [00:24, 38.41iter/s]Best score: 0.1767: : 841iter [00:25, 38.41iter/s]Best score: 0.1767: : 842iter [00:25, 38.41iter/s]Best score: 0.1767: : 843iter [00:25, 38.41iter/s]Best score: 0.1767: : 844iter [00:25, 38.54iter/s]Best score: 0.1767: : 844iter [00:25, 38.54iter/s]Best score: 0.1767: : 845iter [00:25, 38.54iter/s]Best score: 0.1767: : 846iter [00:25, 38.54iter/s]Best score: 0.1767: : 847iter [00:25, 38.54iter/s]Best score: 0.1767: : 848iter [00:25, 38.76iter/s]Best score: 0.1767: : 848iter [00:25, 38.76iter/s]
[ITER 850] Best: 0.1767
[PARAMS] Current best parameters:
  fx: 566.0456
  fy: 565.7701
  px: 982.0221
  py: 751.0093
  k1: -0.05140731
  k2: 0.02438930
  k3: -0.00722540
  k4: 0.00014690
  p1: -0.00133442
  p2: -0.00472445
  p3: 0.02191176
  p4: -0.01010607
  s1: -0.0167
  s2: 0.0096
  s3: -0.0230
  s4: 0.0097
  tilt_x: -0.0180
  tilt_y: -0.0107
  scale: 3.0075
  rotation: -0.8526
Best score: 0.1767: : 849iter [00:25, 38.76iter/s]Best score: 0.1767: : 850iter [00:25, 38.76iter/s]Best score: 0.1767: : 851iter [00:25, 38.76iter/s]Best score: 0.1767: : 852iter [00:25, 31.62iter/s]Best score: 0.1767: : 852iter [00:25, 31.62iter/s]Best score: 0.1767: : 853iter [00:25, 31.62iter/s]Best score: 0.1767: : 854iter [00:25, 31.62iter/s]Best score: 0.1767: : 855iter [00:25, 31.62iter/s]Best score: 0.1767: : 856iter [00:25, 33.63iter/s]Best score: 0.1767: : 856iter [00:25, 33.63iter/s]Best score: 0.1767: : 857iter [00:25, 33.63iter/s]Best score: 0.1767: : 858iter [00:25, 33.63iter/s]Best score: 0.1767: : 859iter [00:25, 33.63iter/s]Best score: 0.1767: : 860iter [00:25, 34.94iter/s]Best score: 0.1767: : 860iter [00:25, 34.94iter/s]Best score: 0.1767: : 861iter [00:25, 34.94iter/s]Best score: 0.1767: : 862iter [00:25, 34.94iter/s]Best score: 0.1767: : 863iter [00:25, 34.94iter/s]Best score: 0.1767: : 864iter [00:25, 36.10iter/s]Best score: 0.1767: : 864iter [00:25, 36.10iter/s]Best score: 0.1767: : 865iter [00:25, 36.10iter/s]Best score: 0.1767: : 866iter [00:25, 36.10iter/s]Best score: 0.1767: : 867iter [00:25, 36.10iter/s]Best score: 0.1767: : 868iter [00:25, 37.12iter/s]Best score: 0.1767: : 868iter [00:25, 37.12iter/s]Best score: 0.1761: : 869iter [00:25, 37.12iter/s]Best score: 0.1761: : 870iter [00:25, 37.12iter/s]Best score: 0.1761: : 871iter [00:25, 37.12iter/s]Best score: 0.1761: : 872iter [00:25, 37.40iter/s]Best score: 0.1761: : 872iter [00:25, 37.40iter/s]Best score: 0.1761: : 873iter [00:25, 37.40iter/s]Best score: 0.1761: : 874iter [00:25, 37.40iter/s]Best score: 0.1761: : 875iter [00:25, 37.40iter/s]Best score: 0.1761: : 876iter [00:25, 38.10iter/s]Best score: 0.1761: : 876iter [00:25, 38.10iter/s]Best score: 0.1761: : 877iter [00:25, 38.10iter/s]Best score: 0.1761: : 878iter [00:26, 38.10iter/s]Best score: 0.1751: : 879iter [00:26, 38.10iter/s]Best score: 0.1751: : 880iter [00:26, 38.36iter/s]Best score: 0.1751: : 880iter [00:26, 38.36iter/s]Best score: 0.1751: : 881iter [00:26, 38.36iter/s]Best score: 0.1751: : 882iter [00:26, 38.36iter/s]Best score: 0.1751: : 883iter [00:26, 38.36iter/s]Best score: 0.1751: : 884iter [00:26, 38.76iter/s]Best score: 0.1751: : 884iter [00:26, 38.76iter/s]Best score: 0.1751: : 885iter [00:26, 38.76iter/s]Best score: 0.1751: : 886iter [00:26, 38.76iter/s]Best score: 0.1751: : 887iter [00:26, 38.76iter/s]Best score: 0.1751: : 888iter [00:26, 39.03iter/s]Best score: 0.1751: : 888iter [00:26, 39.03iter/s]Best score: 0.1736: : 889iter [00:26, 39.03iter/s]Best score: 0.1736: : 890iter [00:26, 39.03iter/s]Best score: 0.1736: : 891iter [00:26, 39.03iter/s]Best score: 0.1736: : 892iter [00:26, 38.81iter/s]Best score: 0.1736: : 892iter [00:26, 38.81iter/s]Best score: 0.1736: : 893iter [00:26, 38.81iter/s]Best score: 0.1736: : 894iter [00:26, 38.81iter/s]Best score: 0.1736: : 895iter [00:26, 38.81iter/s]Best score: 0.1736: : 896iter [00:26, 38.87iter/s]Best score: 0.1736: : 896iter [00:26, 38.87iter/s]Best score: 0.1736: : 897iter [00:26, 38.87iter/s]Best score: 0.1736: : 898iter [00:26, 38.87iter/s]
[ITER 900] Best: 0.1733
[PARAMS] Current best parameters:
  fx: 565.0674
  fy: 564.7961
  px: 981.8784
  py: 750.5815
  k1: -0.04689319
  k2: 0.01862089
  k3: -0.00408385
  k4: -0.00044344
  p1: -0.00128318
  p2: -0.00348704
  p3: 0.02062001
  p4: -0.00945876
  s1: -0.0168
  s2: 0.0088
  s3: -0.0225
  s4: 0.0094
  tilt_x: -0.0204
  tilt_y: -0.0077
  scale: 3.0051
  rotation: -0.8581
Best score: 0.1733: : 899iter [00:26, 38.87iter/s]Best score: 0.1733: : 900iter [00:26, 38.88iter/s]Best score: 0.1733: : 900iter [00:26, 38.88iter/s]Best score: 0.1733: : 901iter [00:26, 38.88iter/s]Best score: 0.1733: : 902iter [00:26, 38.88iter/s]Best score: 0.1733: : 903iter [00:26, 38.88iter/s]Best score: 0.1733: : 904iter [00:26, 31.54iter/s]Best score: 0.1733: : 904iter [00:26, 31.54iter/s]Best score: 0.1733: : 905iter [00:26, 31.54iter/s]Best score: 0.1733: : 906iter [00:26, 31.54iter/s]Best score: 0.1733: : 907iter [00:26, 31.54iter/s]Best score: 0.1733: : 908iter [00:26, 33.56iter/s]Best score: 0.1733: : 908iter [00:26, 33.56iter/s]Best score: 0.1727: : 909iter [00:26, 33.56iter/s]Best score: 0.1727: : 910iter [00:26, 33.56iter/s]Best score: 0.1727: : 911iter [00:26, 33.56iter/s]Best score: 0.1727: : 912iter [00:26, 34.85iter/s]Best score: 0.1727: : 912iter [00:26, 34.85iter/s]Best score: 0.1727: : 913iter [00:27, 34.85iter/s]Best score: 0.1727: : 914iter [00:27, 34.85iter/s]Best score: 0.1727: : 915iter [00:27, 34.85iter/s]Best score: 0.1727: : 916iter [00:27, 36.18iter/s]Best score: 0.1727: : 916iter [00:27, 36.18iter/s]Best score: 0.1727: : 917iter [00:27, 36.18iter/s]Best score: 0.1727: : 918iter [00:27, 36.18iter/s]Best score: 0.1709: : 919iter [00:27, 36.18iter/s]Best score: 0.1709: : 920iter [00:27, 36.76iter/s]Best score: 0.1709: : 920iter [00:27, 36.76iter/s]Best score: 0.1709: : 921iter [00:27, 36.76iter/s]Best score: 0.1709: : 922iter [00:27, 36.76iter/s]Best score: 0.1709: : 923iter [00:27, 36.76iter/s]Best score: 0.1709: : 924iter [00:27, 37.51iter/s]Best score: 0.1709: : 924iter [00:27, 37.51iter/s]Best score: 0.1709: : 925iter [00:27, 37.51iter/s]Best score: 0.1709: : 926iter [00:27, 37.51iter/s]Best score: 0.1709: : 927iter [00:27, 37.51iter/s]Best score: 0.1709: : 928iter [00:27, 37.44iter/s]Best score: 0.1709: : 928iter [00:27, 37.44iter/s]Best score: 0.1698: : 929iter [00:27, 37.44iter/s]Best score: 0.1698: : 930iter [00:27, 37.44iter/s]Best score: 0.1698: : 931iter [00:27, 37.44iter/s]Best score: 0.1698: : 932iter [00:27, 37.71iter/s]Best score: 0.1698: : 932iter [00:27, 37.71iter/s]Best score: 0.1698: : 933iter [00:27, 37.71iter/s]Best score: 0.1698: : 934iter [00:27, 37.71iter/s]Best score: 0.1698: : 935iter [00:27, 37.71iter/s]Best score: 0.1698: : 936iter [00:27, 38.08iter/s]Best score: 0.1698: : 936iter [00:27, 38.08iter/s]Best score: 0.1698: : 937iter [00:27, 38.08iter/s]Best score: 0.1698: : 938iter [00:27, 38.08iter/s]Best score: 0.1676: : 939iter [00:27, 38.08iter/s]Best score: 0.1676: : 940iter [00:27, 38.13iter/s]Best score: 0.1676: : 940iter [00:27, 38.13iter/s]Best score: 0.1676: : 941iter [00:27, 38.13iter/s]Best score: 0.1676: : 942iter [00:27, 38.13iter/s]Best score: 0.1676: : 943iter [00:27, 38.13iter/s]Best score: 0.1676: : 944iter [00:27, 38.64iter/s]Best score: 0.1676: : 944iter [00:27, 38.64iter/s]Best score: 0.1676: : 945iter [00:27, 38.64iter/s]Best score: 0.1676: : 946iter [00:27, 38.64iter/s]Best score: 0.1676: : 947iter [00:27, 38.64iter/s]Best score: 0.1676: : 948iter [00:27, 38.97iter/s]Best score: 0.1676: : 948iter [00:27, 38.97iter/s]
[ITER 950] Best: 0.1672
[PARAMS] Current best parameters:
  fx: 564.5534
  fy: 564.3376
  px: 982.2754
  py: 750.5936
  k1: -0.03632151
  k2: 0.00690869
  k3: 0.00067663
  k4: -0.00113446
  p1: 0.00289868
  p2: 0.00084960
  p3: 0.01210265
  p4: -0.01109883
  s1: -0.0122
  s2: 0.0103
  s3: -0.0189
  s4: 0.0113
  tilt_x: -0.0285
  tilt_y: -0.0012
  scale: 2.9880
  rotation: -0.8658
Best score: 0.1672: : 949iter [00:27, 38.97iter/s]Best score: 0.1672: : 950iter [00:28, 38.97iter/s]Best score: 0.1672: : 951iter [00:28, 38.97iter/s]Best score: 0.1672: : 952iter [00:28, 31.58iter/s]Best score: 0.1672: : 952iter [00:28, 31.58iter/s]Best score: 0.1672: : 953iter [00:28, 31.58iter/s]Best score: 0.1672: : 954iter [00:28, 31.58iter/s]Best score: 0.1672: : 955iter [00:28, 31.58iter/s]Best score: 0.1672: : 956iter [00:28, 33.56iter/s]Best score: 0.1672: : 956iter [00:28, 33.56iter/s]Best score: 0.1672: : 957iter [00:28, 33.56iter/s]Best score: 0.1672: : 958iter [00:28, 33.56iter/s]Best score: 0.1648: : 959iter [00:28, 33.56iter/s]Best score: 0.1648: : 960iter [00:28, 34.98iter/s]Best score: 0.1648: : 960iter [00:28, 34.98iter/s]Best score: 0.1648: : 961iter [00:28, 34.98iter/s]Best score: 0.1648: : 962iter [00:28, 34.98iter/s]Best score: 0.1648: : 963iter [00:28, 34.98iter/s]Best score: 0.1648: : 964iter [00:28, 36.16iter/s]Best score: 0.1648: : 964iter [00:28, 36.16iter/s]Best score: 0.1648: : 965iter [00:28, 36.16iter/s]Best score: 0.1648: : 966iter [00:28, 36.16iter/s]Best score: 0.1648: : 967iter [00:28, 36.16iter/s]Best score: 0.1648: : 968iter [00:28, 37.13iter/s]Best score: 0.1648: : 968iter [00:28, 37.13iter/s]Best score: 0.1617: : 969iter [00:28, 37.13iter/s]Best score: 0.1617: : 970iter [00:28, 37.13iter/s]Best score: 0.1617: : 971iter [00:28, 37.13iter/s]Best score: 0.1617: : 972iter [00:28, 37.60iter/s]Best score: 0.1617: : 972iter [00:28, 37.60iter/s]Best score: 0.1617: : 973iter [00:28, 37.60iter/s]Best score: 0.1617: : 974iter [00:28, 37.60iter/s]Best score: 0.1617: : 975iter [00:28, 37.60iter/s]Best score: 0.1617: : 976iter [00:28, 38.26iter/s]Best score: 0.1617: : 976iter [00:28, 38.26iter/s]Best score: 0.1617: : 977iter [00:28, 38.26iter/s]Best score: 0.1617: : 978iter [00:28, 38.26iter/s]Best score: 0.1600: : 979iter [00:28, 38.26iter/s]Best score: 0.1600: : 980iter [00:28, 38.44iter/s]Best score: 0.1600: : 980iter [00:28, 38.44iter/s]Best score: 0.1600: : 981iter [00:28, 38.44iter/s]Best score: 0.1600: : 982iter [00:28, 38.44iter/s]Best score: 0.1600: : 983iter [00:28, 38.44iter/s]Best score: 0.1600: : 984iter [00:28, 38.71iter/s]Best score: 0.1600: : 984iter [00:28, 38.71iter/s]Best score: 0.1600: : 985iter [00:28, 38.71iter/s]Best score: 0.1600: : 986iter [00:28, 38.71iter/s]Best score: 0.1600: : 987iter [00:28, 38.71iter/s]Best score: 0.1600: : 988iter [00:28, 38.73iter/s]Best score: 0.1600: : 988iter [00:29, 38.73iter/s]Best score: 0.1568: : 989iter [00:29, 38.73iter/s]Best score: 0.1568: : 990iter [00:29, 38.73iter/s]Best score: 0.1568: : 991iter [00:29, 38.73iter/s]Best score: 0.1568: : 992iter [00:29, 38.66iter/s]Best score: 0.1568: : 992iter [00:29, 38.66iter/s]Best score: 0.1568: : 993iter [00:29, 38.66iter/s]Best score: 0.1568: : 994iter [00:29, 38.66iter/s]Best score: 0.1568: : 995iter [00:29, 38.66iter/s]Best score: 0.1568: : 996iter [00:29, 38.89iter/s]Best score: 0.1568: : 996iter [00:29, 38.89iter/s]Best score: 0.1568: : 997iter [00:29, 38.89iter/s]Best score: 0.1568: : 998iter [00:29, 38.89iter/s]
[ITER 1000] Best: 0.1568
[PARAMS] Current best parameters:
  fx: 563.9980
  fy: 563.9524
  px: 982.9712
  py: 749.4720
  k1: -0.02599788
  k2: -0.00839439
  k3: 0.00890999
  k4: -0.00263883
  p1: 0.01232063
  p2: 0.00971557
  p3: -0.00090501
  p4: -0.01057778
  s1: -0.0074
  s2: 0.0097
  s3: -0.0159
  s4: 0.0106
  tilt_x: -0.0533
  tilt_y: 0.0128
  scale: 2.9840
  rotation: -0.8891
Best score: 0.1568: : 999iter [00:29, 38.89iter/s]Best score: 0.1568: : 1000iter [00:29, 38.70iter/s]Best score: 0.1568: : 1000iter [00:29, 38.70iter/s]Best score: 0.1568: : 1001iter [00:29, 38.70iter/s]Best score: 0.1568: : 1002iter [00:29, 38.70iter/s]Best score: 0.1568: : 1003iter [00:29, 38.70iter/s]Best score: 0.1568: : 1004iter [00:29, 31.32iter/s]Best score: 0.1568: : 1004iter [00:29, 31.32iter/s]Best score: 0.1568: : 1005iter [00:29, 31.32iter/s]Best score: 0.1568: : 1006iter [00:29, 31.32iter/s]Best score: 0.1568: : 1007iter [00:29, 31.32iter/s]Best score: 0.1568: : 1008iter [00:29, 33.37iter/s]Best score: 0.1568: : 1008iter [00:29, 33.37iter/s]Best score: 0.1568: : 1009iter [00:29, 33.37iter/s]Best score: 0.1568: : 1010iter [00:29, 33.37iter/s]Best score: 0.1568: : 1011iter [00:29, 33.37iter/s]Best score: 0.1568: : 1012iter [00:29, 34.75iter/s]Best score: 0.1568: : 1012iter [00:29, 34.75iter/s]Best score: 0.1568: : 1013iter [00:29, 34.75iter/s]Best score: 0.1568: : 1014iter [00:29, 34.75iter/s]Best score: 0.1568: : 1015iter [00:29, 34.75iter/s]Best score: 0.1568: : 1016iter [00:29, 36.12iter/s]Best score: 0.1568: : 1016iter [00:29, 36.12iter/s]Best score: 0.1568: : 1017iter [00:29, 36.12iter/s]Best score: 0.1568: : 1018iter [00:29, 36.12iter/s]Best score: 0.1561: : 1019iter [00:29, 36.12iter/s]Best score: 0.1561: : 1020iter [00:29, 36.76iter/s]Best score: 0.1561: : 1020iter [00:29, 36.76iter/s]Best score: 0.1561: : 1021iter [00:29, 36.76iter/s]Best score: 0.1561: : 1022iter [00:29, 36.76iter/s]Best score: 0.1561: : 1023iter [00:29, 36.76iter/s]Best score: 0.1561: : 1024iter [00:29, 37.58iter/s]Best score: 0.1561: : 1024iter [00:30, 37.58iter/s]Best score: 0.1561: : 1025iter [00:30, 37.58iter/s]Best score: 0.1561: : 1026iter [00:30, 37.58iter/s]Best score: 0.1561: : 1027iter [00:30, 37.58iter/s]Best score: 0.1561: : 1028iter [00:30, 38.15iter/s]Best score: 0.1561: : 1028iter [00:30, 38.15iter/s]Best score: 0.1547: : 1029iter [00:30, 38.15iter/s]Best score: 0.1547: : 1030iter [00:30, 38.15iter/s]Best score: 0.1547: : 1031iter [00:30, 38.15iter/s]Best score: 0.1547: : 1032iter [00:30, 29.05iter/s]Best score: 0.1547: : 1032iter [00:30, 29.05iter/s]Best score: 0.1547: : 1033iter [00:30, 29.05iter/s]Best score: 0.1547: : 1034iter [00:30, 29.05iter/s]Best score: 0.1547: : 1035iter [00:30, 29.05iter/s]Best score: 0.1547: : 1036iter [00:30, 31.48iter/s]Best score: 0.1547: : 1036iter [00:30, 31.48iter/s]Best score: 0.1547: : 1037iter [00:30, 31.48iter/s]Best score: 0.1547: : 1038iter [00:30, 31.48iter/s]Best score: 0.1537: : 1039iter [00:30, 31.48iter/s]Best score: 0.1537: : 1040iter [00:30, 33.36iter/s]Best score: 0.1537: : 1040iter [00:30, 33.36iter/s]Best score: 0.1537: : 1041iter [00:30, 33.36iter/s]Best score: 0.1537: : 1042iter [00:30, 33.36iter/s]Best score: 0.1537: : 1043iter [00:30, 33.36iter/s]Best score: 0.1537: : 1044iter [00:30, 34.90iter/s]Best score: 0.1537: : 1044iter [00:30, 34.90iter/s]Best score: 0.1537: : 1045iter [00:30, 34.90iter/s]Best score: 0.1537: : 1046iter [00:30, 34.90iter/s]Best score: 0.1537: : 1047iter [00:30, 34.90iter/s]Best score: 0.1537: : 1048iter [00:30, 36.21iter/s]Best score: 0.1537: : 1048iter [00:30, 36.21iter/s]
[ITER 1050] Best: 0.1529
[PARAMS] Current best parameters:
  fx: 564.9777
  fy: 564.9553
  px: 983.0214
  py: 748.7741
  k1: -0.02715781
  k2: -0.00813758
  k3: 0.00903004
  k4: -0.00271610
  p1: 0.01152793
  p2: 0.00932653
  p3: -0.00148509
  p4: -0.00897942
  s1: -0.0060
  s2: 0.0080
  s3: -0.0151
  s4: 0.0089
  tilt_x: -0.0552
  tilt_y: 0.0118
  scale: 2.9828
  rotation: -0.8883
Best score: 0.1529: : 1049iter [00:30, 36.21iter/s]Best score: 0.1529: : 1050iter [00:30, 36.21iter/s]Best score: 0.1529: : 1051iter [00:30, 36.21iter/s]Best score: 0.1529: : 1052iter [00:30, 29.92iter/s]Best score: 0.1529: : 1052iter [00:30, 29.92iter/s]Best score: 0.1529: : 1053iter [00:30, 29.92iter/s]Best score: 0.1529: : 1054iter [00:30, 29.92iter/s]Best score: 0.1529: : 1055iter [00:30, 29.92iter/s]Best score: 0.1529: : 1056iter [00:30, 32.29iter/s]Best score: 0.1529: : 1056iter [00:31, 32.29iter/s]Best score: 0.1529: : 1057iter [00:31, 32.29iter/s]Best score: 0.1529: : 1058iter [00:31, 32.29iter/s]Best score: 0.1525: : 1059iter [00:31, 32.29iter/s]Best score: 0.1525: : 1060iter [00:31, 33.93iter/s]Best score: 0.1525: : 1060iter [00:31, 33.93iter/s]Best score: 0.1525: : 1061iter [00:31, 33.93iter/s]Best score: 0.1525: : 1062iter [00:31, 33.93iter/s]Best score: 0.1525: : 1063iter [00:31, 33.93iter/s]Best score: 0.1525: : 1064iter [00:31, 35.44iter/s]Best score: 0.1525: : 1064iter [00:31, 35.44iter/s]Best score: 0.1525: : 1065iter [00:31, 35.44iter/s]Best score: 0.1525: : 1066iter [00:31, 35.44iter/s]Best score: 0.1525: : 1067iter [00:31, 35.44iter/s]Best score: 0.1525: : 1068iter [00:31, 36.57iter/s]Best score: 0.1525: : 1068iter [00:31, 36.57iter/s]Best score: 0.1515: : 1069iter [00:31, 36.57iter/s]Best score: 0.1515: : 1070iter [00:31, 36.57iter/s]Best score: 0.1515: : 1071iter [00:31, 36.57iter/s]Best score: 0.1515: : 1072iter [00:31, 37.12iter/s]Best score: 0.1515: : 1072iter [00:31, 37.12iter/s]Best score: 0.1515: : 1073iter [00:31, 37.12iter/s]Best score: 0.1515: : 1074iter [00:31, 37.12iter/s]Best score: 0.1515: : 1075iter [00:31, 37.12iter/s]Best score: 0.1515: : 1076iter [00:31, 37.76iter/s]Best score: 0.1515: : 1076iter [00:31, 37.76iter/s]Best score: 0.1515: : 1077iter [00:31, 37.76iter/s]Best score: 0.1515: : 1078iter [00:31, 37.76iter/s]Best score: 0.1515: : 1079iter [00:31, 37.76iter/s]Best score: 0.1515: : 1080iter [00:31, 38.02iter/s]Best score: 0.1515: : 1080iter [00:31, 38.02iter/s]Best score: 0.1515: : 1081iter [00:31, 38.02iter/s]Best score: 0.1515: : 1082iter [00:31, 38.02iter/s]Best score: 0.1515: : 1083iter [00:31, 38.02iter/s]Best score: 0.1515: : 1084iter [00:31, 38.49iter/s]Best score: 0.1515: : 1084iter [00:31, 38.49iter/s]Best score: 0.1515: : 1085iter [00:31, 38.49iter/s]Best score: 0.1515: : 1086iter [00:31, 38.49iter/s]Best score: 0.1515: : 1087iter [00:31, 38.49iter/s]Best score: 0.1515: : 1088iter [00:31, 38.83iter/s]Best score: 0.1515: : 1088iter [00:31, 38.83iter/s]Best score: 0.1510: : 1089iter [00:31, 38.83iter/s]Best score: 0.1510: : 1090iter [00:31, 38.83iter/s]Best score: 0.1510: : 1091iter [00:31, 38.83iter/s]Best score: 0.1510: : 1092iter [00:31, 38.80iter/s]Best score: 0.1510: : 1092iter [00:31, 38.80iter/s]Best score: 0.1510: : 1093iter [00:31, 38.80iter/s]Best score: 0.1510: : 1094iter [00:31, 38.80iter/s]Best score: 0.1510: : 1095iter [00:32, 38.80iter/s]Best score: 0.1510: : 1096iter [00:32, 39.03iter/s]Best score: 0.1510: : 1096iter [00:32, 39.03iter/s]Best score: 0.1510: : 1097iter [00:32, 39.03iter/s]Best score: 0.1510: : 1098iter [00:32, 39.03iter/s]
[ITER 1100] Best: 0.1506
[PARAMS] Current best parameters:
  fx: 565.3203
  fy: 565.3451
  px: 982.8207
  py: 748.5422
  k1: -0.02471994
  k2: -0.01291809
  k3: 0.01193234
  k4: -0.00331790
  p1: 0.01241668
  p2: 0.01130832
  p3: -0.00564103
  p4: -0.00818858
  s1: -0.0043
  s2: 0.0075
  s3: -0.0119
  s4: 0.0080
  tilt_x: -0.0582
  tilt_y: 0.0167
  scale: 2.9820
  rotation: -0.8947
Best score: 0.1506: : 1099iter [00:32, 39.03iter/s]Best score: 0.1506: : 1100iter [00:32, 38.80iter/s]Best score: 0.1506: : 1100iter [00:32, 34.16iter/s]

[📈] Running L-BFGS-B polish after 1100 DE iterations...
  Polish improved score: 0.150558 -> 0.150423

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 25,938 → 25,938 within 3500mm ring
  Ring polish improved score: 0.150423 -> 0.150120
  Success: True
  Tangential distortion: p1=0.012414, p2=0.011316, p3=-0.005637, p4=-0.008188
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.1501
[✅] Parameters copied to: /working/MDC046_W048_2026-09-29/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 565.3203384385749
    fy: 565.3450549499012
    px: 982.8207313940856
    py: 748.5421967554818
    k1: -0.024715657898670928
    k2: -0.01291580876904443
    k3: 0.011930173467071196
    k4: -0.003318013683258492
    p1: 0.01241428550111286
    p2: 0.011316308043458411
    p3: -0.00563717673633376
    p4: -0.008188260248205686
    scale: 2.9820269898726286
    rotation: -0.8947499548480157
    mmpp: 1.2775738074912113

[🔄] Converting 1460 frames to PTD, creating debug images for 200 calibration frames...
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   🔄 500:  88%|████████▊ | 569/648 [00:03<00:00, 174.66frame/s][A
   🔄 500:  91%|█████████ | 587/648 [00:03<00:00, 174.62frame/s][A
   🔄 500:  93%|█████████▎| 605/648 [00:03<00:00, 174.41frame/s][A
   🔄 500:  96%|█████████▌| 623/648 [00:03<00:00, 174.40frame/s][A
   🔄 500:  99%|█████████▉| 641/648 [00:03<00:00, 174.09frame/s][A
                                                                [A📁 Rigs: 100%|██████████| 2/2 [00:15<00:00,  7.66s/rig]📁 Rigs: 100%|██████████| 2/2 [00:15<00:00,  7.83s/rig]
[✅] Saved PTDs: /working/MDC046_W048_2026-09-29/calibration/debug/4_undistorted/output/ptd
📁 Rigs:   0%|          | 0/2 [00:00<?, ?rig/s]
   🔄 1000:   0%|          | 0/100 [00:00<?, ?frame/s][A
   🔄 1000:  15%|█▌        | 15/100 [00:00<00:00, 145.32frame/s][A
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   🔄 1000:  76%|███████▌  | 76/100 [00:00<00:00, 137.23frame/s][A
   🔄 1000:  90%|█████████ | 90/100 [00:00<00:00, 135.99frame/s][A
                                                                [A📁 Rigs:  50%|█████     | 1/2 [00:01<00:01,  1.26s/rig]
   🔄 500:   0%|          | 0/100 [00:00<?, ?frame/s][A
   🔄 500:  13%|█▎        | 13/100 [00:00<00:00, 122.29frame/s][A
   🔄 500:  27%|██▋       | 27/100 [00:00<00:00, 125.44frame/s][A
   🔄 500:  41%|████      | 41/100 [00:00<00:00, 131.15frame/s][A
   🔄 500:  58%|█████▊    | 58/100 [00:00<00:00, 141.52frame/s][A
   🔄 500:  73%|███████▎  | 73/100 [00:00<00:00, 130.62frame/s][A
   🔄 500:  89%|████████▉ | 89/100 [00:00<00:00, 138.30frame/s][A
                                                               [A📁 Rigs: 100%|██████████| 2/2 [00:02<00:00,  1.29s/rig]📁 Rigs: 100%|██████████| 2/2 [00:02<00:00,  1.28s/rig]
[✅] Saved PTDs: /working/MDC046_W048_2026-09-29/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%|▎         | 81402/3080448 [00:00<00:03, 814016.89px/s]📤 Writing LUT:   5%|▌         | 162804/3080448 [00:00<00:03, 791555.78px/s]📤 Writing LUT:   8%|▊         | 242003/3080448 [00:00<00:03, 755132.15px/s]📤 Writing LUT:  10%|█         | 317682/3080448 [00:00<00:03, 731450.04px/s]📤 Writing LUT:  13%|█▎        | 390957/3080448 [00:00<00:03, 692319.77px/s]📤 Writing LUT:  15%|█▌        | 468987/3080448 [00:00<00:03, 720260.24px/s]📤 Writing LUT:  18%|█▊        | 551473/3080448 [00:00<00:03, 752903.13px/s]📤 Writing LUT:  20%|██        | 627177/3080448 [00:00<00:03, 725671.38px/s]📤 Writing LUT:  23%|██▎       | 700814/3080448 [00:00<00:03, 728850.74px/s]📤 Writing LUT:  25%|██▌       | 773999/3080448 [00:01<00:03, 721429.74px/s]📤 Writing LUT:  27%|██▋       | 846344/3080448 [00:01<00:03, 697970.39px/s]📤 Writing LUT:  30%|███       | 924785/3080448 [00:01<00:02, 723076.85px/s]📤 Writing LUT:  32%|███▏      | 997380/3080448 [00:01<00:02, 714204.14px/s]📤 Writing LUT:  35%|███▍      | 1069000/3080448 [00:01<00:03, 617269.08px/s]📤 Writing LUT:  37%|███▋      | 1133033/3080448 [00:01<00:03, 581111.94px/s]📤 Writing LUT:  39%|███▉      | 1197334/3080448 [00:01<00:03, 597263.75px/s]📤 Writing LUT:  41%|████      | 1267790/3080448 [00:01<00:02, 626399.49px/s]📤 Writing LUT:  44%|████▎     | 1342665/3080448 [00:01<00:02, 660592.51px/s]📤 Writing LUT:  46%|████▌     | 1409925/3080448 [00:02<00:02, 611654.62px/s]📤 Writing LUT:  48%|████▊     | 1472523/3080448 [00:02<00:02, 613386.48px/s]📤 Writing LUT:  50%|█████     | 1545821/3080448 [00:02<00:02, 646854.36px/s]📤 Writing LUT:  52%|█████▏    | 1611937/3080448 [00:02<00:02, 650923.48px/s]📤 Writing LUT:  54%|█████▍    | 1677719/3080448 [00:02<00:02, 637254.52px/s]📤 Writing LUT:  57%|█████▋    | 1741957/3080448 [00:02<00:02, 566604.61px/s]📤 Writing LUT:  59%|█████▊    | 1807132/3080448 [00:02<00:02, 589356.75px/s]📤 Writing LUT:  61%|██████    | 1881780/3080448 [00:02<00:01, 632764.07px/s]📤 Writing LUT:  63%|██████▎   | 1946917/3080448 [00:02<00:01, 638029.11px/s]📤 Writing LUT:  65%|██████▌   | 2017524/3080448 [00:03<00:01, 657616.02px/s]📤 Writing LUT:  68%|██████▊   | 2084069/3080448 [00:03<00:01, 651203.51px/s]📤 Writing LUT:  70%|███████   | 2158981/3080448 [00:03<00:01, 679714.53px/s]📤 Writing LUT:  72%|███████▏  | 2228123/3080448 [00:03<00:01, 683152.12px/s]📤 Writing LUT:  75%|███████▍  | 2304882/3080448 [00:03<00:01, 708111.26px/s]📤 Writing LUT:  77%|███████▋  | 2385150/3080448 [00:03<00:00, 736190.20px/s]📤 Writing LUT:  80%|███████▉  | 2458990/3080448 [00:03<00:00, 703249.55px/s]📤 Writing LUT:  82%|████████▏ | 2529768/3080448 [00:03<00:00, 665256.32px/s]📤 Writing LUT:  85%|████████▍ | 2603430/3080448 [00:03<00:00, 685259.53px/s]📤 Writing LUT:  87%|████████▋ | 2674761/3080448 [00:03<00:00, 693278.86px/s]📤 Writing LUT:  89%|████████▉ | 2744543/3080448 [00:04<00:00, 649310.15px/s]📤 Writing LUT:  92%|█████████▏| 2819468/3080448 [00:04<00:00, 677210.52px/s]📤 Writing LUT:  94%|█████████▍| 2901036/3080448 [00:04<00:00, 716688.89px/s]📤 Writing LUT:  97%|█████████▋| 2973445/3080448 [00:04<00:00, 705895.69px/s]📤 Writing LUT:  99%|█████████▉| 3051596/3080448 [00:04<00:00, 727730.99px/s][✅] LUT written to: /working/MDC046_W048_2026-09-29/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'MDC046_W048_2026-09-29' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
📤 Writing LUT: 100%|██████████| 3080448/3080448 [00:04<00:00, 676517.49px/s]
[✅] LUT copied to: /working/MDC046_W048_2026-09-29/calibration/MDC046_W048_2026-09-29_unknown.lut

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

[ℹ️] Detected device type: MD (rigs: [500, 1000]mm)
📁 Rigs (heatmap):   0%|          | 0/2 [00:00<?, ?rig/s]
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                                                                [A[✅] 1000: /working/MDC046_W048_2026-09-29/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDC046_W048_2026-09-29/calibration/debug/5_heatmap/1000_heatmap_fitted.png
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                                                               [A[✅] 500: /working/MDC046_W048_2026-09-29/calibration/debug/5_heatmap/500_heatmap.png
[✅] 500 (fitted): /working/MDC046_W048_2026-09-29/calibration/debug/5_heatmap/500_heatmap_fitted.png
📁 Rigs (heatmap): 100%|██████████| 2/2 [00:29<00:00, 14.28s/rig]📁 Rigs (heatmap): 100%|██████████| 2/2 [00:29<00:00, 14.66s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MDC046_W048_2026-09-29/calibration/debug/5_heatmap
[🏁] Finished processing MDC046_W048_2026-09-29


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