2026-10-02T04:58:05 - INFO: Slick 0.0.8a13

🟢 Starting Calibration Pipeline

=== Processing MDC101_W036_2026-10-01 ===
2026-10-02T04:58:05 - INFO: Camera ID: 14409211
2026-10-02T04:58:05 - INFO: Wand ID: 
2026-10-02T04:58:05 - INFO: Recorded At: 2026-10-01T18:06:38Z

-------------------------------------------------------------------
                        Step 1: Digitization                       
-------------------------------------------------------------------

[🔄] Full PTD mode: Processing ALL images then creating calibration subset
[📸] Digitizing ALL images...
[📸] Full dataset mode: Processing ALL images (no debug visualizations)
[INFO] Found 1 las0.zip files to process
Processing Rigs:   0%|          | 0/1 [00:00<?, ?it/s][INFO] Filtered 642 stationary frames, 544 remain

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                                                                           [A[PASS2] Frame 0000307: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000308: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000309: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000310: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000316: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000317: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000318: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000319: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000427: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000430: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000433: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000436: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000439: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000440: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000447: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000448: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000451: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000452: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000453: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000462: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000463: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000464: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000465: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000466: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000467: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000531: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000532: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000533: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000534: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000537: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000538: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000539: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000540: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000544: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000545: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000546: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000547: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000548: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000549: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000550: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000551: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000552: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000554: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000555: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000556: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000557: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000560: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000561: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000562: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000563: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000564: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000976: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0000988: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000989: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000990: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000991: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000992: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000993: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001010: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001011: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001012: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001013: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001186: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001187: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001188: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001189: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001193: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001194: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001195: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001196: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001215: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001216: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001217: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001218: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000309: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000318: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000433: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000439: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000451: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000452: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000464: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000466: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000533: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000539: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000546: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000549: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000551: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000556: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000562: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000563: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000990: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000991: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000992: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001012: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001188: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001195: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001217: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 43 frames fixed, 35 untrusted, 544 total

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                                                                           [A
[TIMING] 1000 — 544 frames
  Phase 1  radial detect   (parallel)  :   9.61s  (17.7 ms/frame)
  Phase 2a corner detect   (parallel)  :   5.00s  (9.2 ms/frame)
  Phase 2b corner fix      (sequential):   2.28s
  Phase 3  finalize        (sequential):  12.91s  (23.7 ms/frame)
    decode + undistort                 :   6.17s  (11.3 ms/frame)
    corner apply + refinement          :   3.22s  (5.9 ms/frame)
    segment                            :   2.91s  (5.4 ms/frame)
    smooth                             :   0.38s  (0.7 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  29.81s

Processing Rigs: 100%|██████████| 1/1 [00:36<00:00, 36.20s/it]Processing Rigs: 100%|██████████| 1/1 [00:36<00:00, 36.20s/it]
[💾] Saved RigFrameDataset to /working/MDC101_W036_2026-10-01/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 544 frames from 1 rigs to /working/MDC101_W036_2026-10-01/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDC101_W036_2026-10-01/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 1000: 100 frames selected from 544
[💾] Saved RigFrameDataset to /working/MDC101_W036_2026-10-01/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDC101_W036_2026-10-01/calibration/debug/1_digitized/rig_frames.json

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

-> Calculating the casing center ...
[INFO] Using 20 total sampled bright frames
Computing max image from bright frames:   0%|          | 0/20 [00:00<?, ?it/s]Computing max image from bright frames:   5%|▌         | 1/20 [00:04<01:30,  4.78s/it]Computing max image from bright frames:  10%|█         | 2/20 [00:05<00:40,  2.28s/it]Computing max image from bright frames:  25%|██▌       | 5/20 [00:05<00:10,  1.43it/s]Computing max image from bright frames:  35%|███▌      | 7/20 [00:05<00:05,  2.29it/s]Computing max image from bright frames:  45%|████▌     | 9/20 [00:05<00:03,  3.23it/s]Computing max image from bright frames:  55%|█████▌    | 11/20 [00:06<00:02,  4.05it/s]Computing max image from bright frames:  70%|███████   | 14/20 [00:06<00:00,  6.09it/s]Computing max image from bright frames:  80%|████████  | 16/20 [00:06<00:00,  7.58it/s]Computing max image from bright frames:  95%|█████████▌| 19/20 [00:06<00:00,  9.97it/s]                                                                                       [✅] Casing detection complete: cx=999.0, cy=761.0

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

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500.0} (0.004) | Current: 0.000 | Best: {'fx': 483.838} (0.000):  26%|██▌       | 26/100 [00:00<00:00, 76.66it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.007 | Best: {'fx': 505.051} (0.007):  27%|██▋       | 27/100 [00:00<00:00, 76.66it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.001 | Best: {'fx': 505.051} (0.007):  28%|██▊       | 28/100 [00:00<00:00, 76.66it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.004 | Best: {'fx': 505.051} (0.007):  29%|██▉       | 29/100 [00:00<00:00, 76.66it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 512.121} (0.012):  30%|███       | 30/100 [00:00<00:00, 76.66it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.016 | Best: {'fx': 519.192} (0.016):  31%|███       | 31/100 [00:00<00:00, 76.66it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.016 | Best: {'fx': 519.192} (0.016):  32%|███▏      | 32/100 [00:00<00:01, 49.86it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.033 | Best: {'fx': 526.263} (0.033):  32%|███▏      | 32/100 [00:00<00:01, 49.86it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.036 | Best: {'fx': 540.404} (0.036):  33%|███▎      | 33/100 [00:00<00:01, 49.86it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.027 | Best: {'fx': 540.404} (0.036):  34%|███▍      | 34/100 [00:00<00:01, 49.86it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.056 | Best: {'fx': 533.333} (0.056):  35%|███▌      | 35/100 [00:00<00:01, 49.86it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.017 | Best: {'fx': 533.333} (0.056):  36%|███▌      | 36/100 [00:00<00:01, 49.86it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.019 | Best: {'fx': 533.333} (0.056):  37%|███▋      | 37/100 [00:00<00:01, 49.86it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.021 | Best: {'fx': 533.333} (0.056):  38%|███▊      | 38/100 [00:00<00:01, 49.86it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.016 | Best: {'fx': 533.333} (0.056):  39%|███▉      | 39/100 [00:00<00:01, 49.86it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.023 | Best: {'fx': 533.333} (0.056):  40%|████      | 40/100 [00:00<00:01, 49.86it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 533.333} (0.056):  41%|████      | 41/100 [00:00<00:01, 49.86it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 533.333} (0.056):  42%|████▏     | 42/100 [00:00<00:00, 61.70it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.015 | Best: {'fx': 533.333} (0.056):  42%|████▏     | 42/100 [00:00<00:00, 61.70it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 533.333} (0.056):  43%|████▎     | 43/100 [00:00<00:00, 61.70it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.013 | Best: {'fx': 533.333} (0.056):  44%|████▍     | 44/100 [00:00<00:00, 61.70it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.014 | Best: {'fx': 533.333} (0.056):  45%|████▌     | 45/100 [00:00<00:00, 61.70it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 533.333} (0.056):  46%|████▌     | 46/100 [00:00<00:00, 61.70it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.013 | Best: {'fx': 533.333} (0.056):  47%|████▋     | 47/100 [00:00<00:00, 61.70it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.056):  48%|████▊     | 48/100 [00:00<00:00, 61.70it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.056):  49%|████▉     | 49/100 [00:00<00:00, 61.70it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.056):  50%|█████     | 50/100 [00:00<00:00, 61.70it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  51%|█████     | 51/100 [00:00<00:00, 61.70it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  52%|█████▏    | 52/100 [00:00<00:00, 61.70it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.056):  53%|█████▎    | 53/100 [00:00<00:00, 61.70it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  54%|█████▍    | 54/100 [00:00<00:00, 61.70it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  55%|█████▌    | 55/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.056):  55%|█████▌    | 55/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.056):  56%|█████▌    | 56/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  57%|█████▋    | 57/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.056):  58%|█████▊    | 58/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  59%|█████▉    | 59/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  60%|██████    | 60/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.056):  61%|██████    | 61/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  62%|██████▏   | 62/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  63%|██████▎   | 63/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.056):  64%|██████▍   | 64/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.056):  65%|██████▌   | 65/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  66%|██████▌   | 66/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  67%|██████▋   | 67/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.056):  68%|██████▊   | 68/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  69%|██████▉   | 69/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.056):  70%|███████   | 70/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  71%|███████   | 71/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  72%|███████▏  | 72/100 [00:00<00:00, 78.13it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  73%|███████▎  | 73/100 [00:00<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  73%|███████▎  | 73/100 [00:00<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  74%|███████▍  | 74/100 [00:00<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.056):  75%|███████▌  | 75/100 [00:00<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  76%|███████▌  | 76/100 [00:00<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  77%|███████▋  | 77/100 [00:00<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  78%|███████▊  | 78/100 [00:00<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  79%|███████▉  | 79/100 [00:00<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  80%|████████  | 80/100 [00:00<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  81%|████████  | 81/100 [00:00<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  82%|████████▏ | 82/100 [00:00<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  83%|████████▎ | 83/100 [00:00<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  84%|████████▍ | 84/100 [00:00<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  85%|████████▌ | 85/100 [00:00<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  86%|████████▌ | 86/100 [00:01<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  87%|████████▋ | 87/100 [00:01<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  88%|████████▊ | 88/100 [00:01<00:00, 105.01it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  89%|████████▉ | 89/100 [00:01<00:00, 116.95it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  89%|████████▉ | 89/100 [00:01<00:00, 116.95it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  90%|█████████ | 90/100 [00:01<00:00, 116.95it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  91%|█████████ | 91/100 [00:01<00:00, 116.95it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  92%|█████████▏| 92/100 [00:01<00:00, 116.95it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  93%|█████████▎| 93/100 [00:01<00:00, 116.95it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  94%|█████████▍| 94/100 [00:01<00:00, 116.95it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  95%|█████████▌| 95/100 [00:01<00:00, 116.95it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  96%|█████████▌| 96/100 [00:01<00:00, 116.95it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  97%|█████████▋| 97/100 [00:01<00:00, 116.95it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  98%|█████████▊| 98/100 [00:01<00:00, 116.95it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.056):  99%|█████████▉| 99/100 [00:01<00:00, 116.95it/s]                                                                                                                                          0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.009 | Best: {'fx': 508.333} (0.009):   0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.009 | Best: {'fx': 508.333} (0.009):   2%|▏         | 1/50 [00:00<00:12,  3.83it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.012 | Best: {'fx': 510.374} (0.012):   2%|▏         | 1/50 [00:00<00:12,  3.83it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.011 | Best: {'fx': 510.374} (0.012):   4%|▍         | 2/50 [00:00<00:12,  3.83it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.012 | Best: {'fx': 512.415} (0.012):   6%|▌         | 3/50 [00:00<00:12,  3.83it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.012 | Best: {'fx': 512.415} (0.012):   8%|▊         | 4/50 [00:00<00:12,  3.83it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.013 | Best: {'fx': 513.435} (0.013):  10%|█         | 5/50 [00:00<00:11,  3.83it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.013 | Best: {'fx': 514.456} (0.013):  12%|█▏        | 6/50 [00:00<00:11,  3.83it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.013 | Best: {'fx': 515.476} (0.013):  14%|█▍        | 7/50 [00:00<00:11,  3.83it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.013 | Best: {'fx': 515.476} (0.013):  16%|█▌        | 8/50 [00:00<00:01, 26.61it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.014 | Best: {'fx': 516.497} (0.014):  16%|█▌        | 8/50 [00:00<00:01, 26.61it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.016 | Best: {'fx': 518.537} (0.016):  18%|█▊        | 9/50 [00:00<00:01, 26.61it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.014 | Best: {'fx': 518.537} (0.016):  20%|██        | 10/50 [00:00<00:01, 26.61it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.017 | Best: {'fx': 519.558} (0.017):  22%|██▏       | 11/50 [00:00<00:01, 26.61it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.019 | Best: {'fx': 520.578} (0.019):  24%|██▍       | 12/50 [00:00<00:01, 26.61it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.022 | Best: {'fx': 521.599} (0.022):  26%|██▌       | 13/50 [00:00<00:01, 26.61it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.025 | Best: {'fx': 523.639} (0.025):  28%|██▊       | 14/50 [00:00<00:01, 26.61it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.023 | Best: {'fx': 523.639} (0.025):  30%|███       | 15/50 [00:00<00:01, 26.61it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.034 | Best: {'fx': 525.68} (0.034):  32%|███▏      | 16/50 [00:00<00:01, 26.61it/s] Brute | Start: {'fx': 533.333} (0.056) | Current: 0.028 | Best: {'fx': 525.68} (0.034):  34%|███▍      | 17/50 [00:00<00:01, 26.61it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.028 | Best: {'fx': 525.68} (0.034):  36%|███▌      | 18/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.035 | Best: {'fx': 526.701} (0.035):  36%|███▌      | 18/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.038 | Best: {'fx': 539.966} (0.038):  38%|███▊      | 19/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.035 | Best: {'fx': 539.966} (0.038):  40%|████      | 20/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.046 | Best: {'fx': 529.762} (0.046):  42%|████▏     | 21/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.037 | Best: {'fx': 529.762} (0.046):  44%|████▍     | 22/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.042 | Best: {'fx': 529.762} (0.046):  46%|████▌     | 23/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.033 | Best: {'fx': 529.762} (0.046):  48%|████▊     | 24/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.031 | Best: {'fx': 529.762} (0.046):  50%|█████     | 25/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.030 | Best: {'fx': 529.762} (0.046):  52%|█████▏    | 26/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.053 | Best: {'fx': 531.803} (0.053):  54%|█████▍    | 27/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.050 | Best: {'fx': 531.803} (0.053):  56%|█████▌    | 28/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.027 | Best: {'fx': 531.803} (0.053):  58%|█████▊    | 29/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.029 | Best: {'fx': 531.803} (0.053):  60%|██████    | 30/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.028 | Best: {'fx': 531.803} (0.053):  62%|██████▏   | 31/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.053 | Best: {'fx': 531.803} (0.053):  64%|██████▍   | 32/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.025 | Best: {'fx': 531.803} (0.053):  66%|██████▌   | 33/50 [00:00<00:00, 49.23it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.025 | Best: {'fx': 531.803} (0.053):  68%|██████▊   | 34/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.058 | Best: {'fx': 533.844} (0.058):  68%|██████▊   | 34/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.027 | Best: {'fx': 533.844} (0.058):  70%|███████   | 35/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.046 | Best: {'fx': 533.844} (0.058):  72%|███████▏  | 36/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.054 | Best: {'fx': 533.844} (0.058):  74%|███████▍  | 37/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.025 | Best: {'fx': 533.844} (0.058):  76%|███████▌  | 38/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.052 | Best: {'fx': 533.844} (0.058):  78%|███████▊  | 39/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.025 | Best: {'fx': 533.844} (0.058):  80%|████████  | 40/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.023 | Best: {'fx': 533.844} (0.058):  82%|████████▏ | 41/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.039 | Best: {'fx': 533.844} (0.058):  84%|████████▍ | 42/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.024 | Best: {'fx': 533.844} (0.058):  86%|████████▌ | 43/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.043 | Best: {'fx': 533.844} (0.058):  88%|████████▊ | 44/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.024 | Best: {'fx': 533.844} (0.058):  90%|█████████ | 45/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.023 | Best: {'fx': 533.844} (0.058):  92%|█████████▏| 46/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.022 | Best: {'fx': 533.844} (0.058):  94%|█████████▍| 47/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.023 | Best: {'fx': 533.844} (0.058):  96%|█████████▌| 48/50 [00:00<00:00, 82.85it/s]Brute | Start: {'fx': 533.333} (0.056) | Current: 0.022 | Best: {'fx': 533.844} (0.058):  98%|█████████▊| 49/50 [00:00<00:00, 82.85it/s]                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 533.843537414966
    px: 999.0
    py: 761.0
    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: 377.2777: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 377.2777, picklable_objective(x0) = 377.3420
Best score: 377.3420: : 0iter [00:02, ?iter/s] Best score: 377.3420: : 1iter [00:02,  2.21s/iter]Best score: 377.3420: : 1iter [00:02,  2.21s/iter]Best score: 377.3420: : 2iter [00:02,  2.21s/iter]Best score: 377.3420: : 3iter [00:02,  2.21s/iter]Best score: 377.3420: : 4iter [00:02,  2.24iter/s]Best score: 377.3420: : 4iter [00:02,  2.24iter/s]Best score: 377.3420: : 5iter [00:02,  2.24iter/s]Best score: 377.3420: : 6iter [00:02,  2.24iter/s]Best score: 377.3420: : 7iter [00:02,  4.44iter/s]Best score: 377.3420: : 7iter [00:02,  4.44iter/s]Best score: 377.3420: : 8iter [00:02,  4.44iter/s]Best score: 377.3420: : 9iter [00:02,  4.44iter/s]Best score: 377.3420: : 10iter [00:02,  6.96iter/s]Best score: 377.3420: : 10iter [00:02,  6.96iter/s]Best score: 377.3420: : 11iter [00:02,  6.96iter/s]Best score: 377.3420: : 12iter [00:02,  6.96iter/s]Best score: 377.3420: : 13iter [00:02,  9.78iter/s]Best score: 377.3420: : 13iter [00:02,  9.78iter/s]Best score: 377.3420: : 14iter [00:02,  9.78iter/s]Best score: 377.3420: : 15iter [00:02,  9.78iter/s]Best score: 377.3420: : 16iter [00:02, 12.82iter/s]Best score: 377.3420: : 16iter [00:02, 12.82iter/s]Best score: 377.3420: : 17iter [00:02, 12.82iter/s]Best score: 377.3420: : 18iter [00:02, 12.82iter/s]Best score: 377.3420: : 19iter [00:02, 15.61iter/s]Best score: 377.3420: : 19iter [00:02, 15.61iter/s]Best score: 377.3420: : 20iter [00:02, 15.61iter/s]Best score: 377.3420: : 21iter [00:02, 15.61iter/s]Best score: 377.3420: : 22iter [00:02, 18.08iter/s]Best score: 377.3420: : 22iter [00:02, 18.08iter/s]Best score: 377.3420: : 23iter [00:03, 18.08iter/s]Best score: 377.3420: : 24iter [00:03, 18.08iter/s]Best score: 377.3420: : 25iter [00:03, 20.68iter/s]Best score: 377.3420: : 25iter [00:03, 20.68iter/s]Best score: 377.3420: : 26iter [00:03, 20.68iter/s]Best score: 377.3420: : 27iter [00:03, 20.68iter/s]Best score: 377.3420: : 28iter [00:03, 22.46iter/s]Best score: 377.3420: : 28iter [00:03, 22.46iter/s]Best score: 377.3420: : 29iter [00:03, 22.46iter/s]Best score: 377.3420: : 30iter [00:03, 22.46iter/s]Best score: 377.3420: : 31iter [00:03, 23.61iter/s]Best score: 377.3420: : 31iter [00:03, 23.61iter/s]Best score: 377.3420: : 32iter [00:03, 23.61iter/s]Best score: 377.3420: : 33iter [00:03, 23.61iter/s]Best score: 377.3420: : 34iter [00:03, 24.23iter/s]Best score: 377.3420: : 34iter [00:03, 24.23iter/s]Best score: 377.3420: : 35iter [00:03, 24.23iter/s]Best score: 377.3420: : 36iter [00:03, 24.23iter/s]Best score: 377.3420: : 37iter [00:03, 25.34iter/s]Best score: 377.3420: : 37iter [00:03, 25.34iter/s]Best score: 377.3420: : 38iter [00:03, 25.34iter/s]Best score: 377.3420: : 39iter [00:03, 25.34iter/s]Best score: 377.3420: : 40iter [00:03, 26.38iter/s]Best score: 377.3420: : 40iter [00:03, 26.38iter/s]Best score: 377.3420: : 41iter [00:03, 26.38iter/s]Best score: 377.3420: : 42iter [00:03, 26.38iter/s]Best score: 377.3420: : 43iter [00:03, 26.60iter/s]Best score: 377.3420: : 43iter [00:03, 26.60iter/s]Best score: 377.3420: : 44iter [00:03, 26.60iter/s]Best score: 377.3420: : 45iter [00:03, 26.60iter/s]Best score: 377.3420: : 46iter [00:03, 25.87iter/s]Best score: 377.3420: : 46iter [00:03, 25.87iter/s]Best score: 377.3420: : 47iter [00:03, 25.87iter/s]Best score: 377.3420: : 48iter [00:03, 25.87iter/s]Best score: 377.3420: : 49iter [00:03, 25.63iter/s]
[ITER 50] Best: 377.3420
[PARAMS] Current best parameters:
  fx: 533.8435
  fy: 533.8435
  px: 999.0000
  py: 761.0000
  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: 377.3420: : 49iter [00:03, 25.63iter/s]Best score: 377.3420: : 50iter [00:04, 25.63iter/s]Best score: 377.3420: : 51iter [00:04, 25.63iter/s]Best score: 377.3420: : 52iter [00:04, 25.48iter/s]Best score: 377.3420: : 52iter [00:04, 25.48iter/s]Best score: 377.3420: : 53iter [00:04, 25.48iter/s]Best score: 377.3420: : 54iter [00:04, 25.48iter/s]Best score: 377.3420: : 55iter [00:04, 25.94iter/s]Best score: 377.3420: : 55iter [00:04, 25.94iter/s]Best score: 377.3420: : 56iter [00:04, 25.94iter/s]Best score: 377.3420: : 57iter [00:04, 25.94iter/s]Best score: 377.3420: : 58iter [00:04, 25.60iter/s]Best score: 377.3420: : 58iter [00:04, 25.60iter/s]Best score: 377.3420: : 59iter [00:04, 25.60iter/s]Best score: 377.3420: : 60iter [00:04, 25.60iter/s]Best score: 377.3420: : 61iter [00:04, 25.87iter/s]Best score: 377.3420: : 61iter [00:04, 25.87iter/s]Best score: 377.3420: : 62iter [00:04, 25.87iter/s]Best score: 377.3420: : 63iter [00:04, 25.87iter/s]Best score: 377.3420: : 64iter [00:04, 26.47iter/s]Best score: 377.3420: : 64iter [00:04, 26.47iter/s]Best score: 377.3420: : 65iter [00:04, 26.47iter/s]Best score: 377.3420: : 66iter [00:04, 26.47iter/s]Best score: 377.3420: : 67iter [00:04, 26.49iter/s]Best score: 377.3420: : 67iter [00:04, 26.49iter/s]Best score: 377.3420: : 68iter [00:04, 26.49iter/s]Best score: 377.3420: : 69iter [00:04, 26.49iter/s]Best score: 377.3420: : 70iter [00:04, 26.54iter/s]Best score: 377.3420: : 70iter [00:04, 26.54iter/s]Best score: 377.3420: : 71iter [00:04, 26.54iter/s]Best score: 377.3420: : 72iter [00:04, 26.54iter/s]Best score: 377.3420: : 73iter [00:04, 26.89iter/s]Best score: 377.3420: : 73iter [00:04, 26.89iter/s]Best score: 377.3420: : 74iter [00:04, 26.89iter/s]Best score: 377.3420: : 75iter [00:04, 26.89iter/s]Best score: 377.3420: : 76iter [00:04, 27.36iter/s]Best score: 377.3420: : 76iter [00:05, 27.36iter/s]Best score: 377.3420: : 77iter [00:05, 27.36iter/s]Best score: 377.3420: : 78iter [00:05, 27.36iter/s]Best score: 377.3420: : 79iter [00:05, 21.76iter/s]Best score: 377.3420: : 79iter [00:05, 21.76iter/s]Best score: 377.3420: : 80iter [00:05, 21.76iter/s]Best score: 377.3420: : 81iter [00:05, 21.76iter/s]Best score: 377.3420: : 82iter [00:05, 23.36iter/s]Best score: 377.3420: : 82iter [00:05, 23.36iter/s]Best score: 377.3420: : 83iter [00:05, 23.36iter/s]Best score: 377.3420: : 84iter [00:05, 23.36iter/s]Best score: 377.3420: : 85iter [00:05, 24.24iter/s]Best score: 377.3420: : 85iter [00:05, 24.24iter/s]Best score: 377.3420: : 86iter [00:05, 24.24iter/s]Best score: 377.3420: : 87iter [00:05, 24.24iter/s]Best score: 377.3420: : 88iter [00:05, 24.39iter/s]Best score: 377.3420: : 88iter [00:05, 24.39iter/s]Best score: 227.2315: : 89iter [00:05, 24.39iter/s]Best score: 227.2315: : 90iter [00:05, 24.39iter/s]Best score: 227.2315: : 91iter [00:05, 24.95iter/s]Best score: 227.2315: : 91iter [00:05, 24.95iter/s]Best score: 227.2315: : 92iter [00:05, 24.95iter/s]Best score: 227.2315: : 93iter [00:05, 24.95iter/s]Best score: 227.2315: : 94iter [00:05, 25.37iter/s]Best score: 227.2315: : 94iter [00:05, 25.37iter/s]Best score: 227.2315: : 95iter [00:05, 25.37iter/s]Best score: 227.2315: : 96iter [00:05, 25.37iter/s]Best score: 227.2315: : 97iter [00:05, 25.86iter/s]Best score: 227.2315: : 97iter [00:05, 25.86iter/s]Best score: 227.2315: : 98iter [00:05, 25.86iter/s]
[ITER 100] Best: 185.4951Best score: 185.4951: : 99iter [00:05, 25.86iter/s]Best score: 185.4951: : 100iter [00:05, 25.70iter/s]
[PARAMS] Current best parameters:
  fx: 546.3876
  fy: 541.4233
  px: 1004.3890
  py: 779.9833
  k1: -0.09778540
  k2: 0.02992816
  k3: 0.03251446
  k4: -0.01301804
  p1: 0.01150292
  p2: 0.02848919
  p3: -0.00284642
  p4: 0.00359046
  s1: -0.0015
  s2: 0.0092
  s3: -0.0149
  s4: 0.0155
  tilt_x: 0.0028
  tilt_y: 0.0158
  scale: 3.2085
  rotation: -2.3931
Best score: 185.4951: : 100iter [00:06, 25.70iter/s]Best score: 185.4951: : 101iter [00:06, 25.70iter/s]Best score: 185.4951: : 102iter [00:06, 25.70iter/s]Best score: 185.4951: : 103iter [00:06, 24.31iter/s]Best score: 185.4951: : 103iter [00:06, 24.31iter/s]Best score: 185.4951: : 104iter [00:06, 24.31iter/s]Best score: 185.4951: : 105iter [00:06, 24.31iter/s]Best score: 185.4951: : 106iter [00:06, 24.85iter/s]Best score: 185.4951: : 106iter [00:06, 24.85iter/s]Best score: 185.4951: : 107iter [00:06, 24.85iter/s]Best score: 185.4951: : 108iter [00:06, 24.85iter/s]Best score: 185.4951: : 109iter [00:06, 26.06iter/s]Best score: 185.4951: : 109iter [00:06, 26.06iter/s]Best score: 185.4951: : 110iter [00:06, 26.06iter/s]Best score: 185.4951: : 111iter [00:06, 26.06iter/s]Best score: 185.4951: : 112iter [00:06, 25.91iter/s]Best score: 185.4951: : 112iter [00:06, 25.91iter/s]Best score: 185.4951: : 113iter [00:06, 25.91iter/s]Best score: 185.4951: : 114iter [00:06, 25.91iter/s]Best score: 185.4951: : 115iter [00:06, 26.74iter/s]Best score: 185.4951: : 115iter [00:06, 26.74iter/s]Best score: 185.4951: : 116iter [00:06, 26.74iter/s]Best score: 185.4951: : 117iter [00:06, 26.74iter/s]Best score: 185.4951: : 118iter [00:06, 26.56iter/s]Best score: 185.4951: : 118iter [00:06, 26.56iter/s]Best score: 185.4951: : 119iter [00:06, 26.56iter/s]Best score: 185.4951: : 120iter [00:06, 26.56iter/s]Best score: 185.4951: : 121iter [00:06, 26.59iter/s]Best score: 185.4951: : 121iter [00:06, 26.59iter/s]Best score: 185.4951: : 122iter [00:06, 26.59iter/s]Best score: 185.4951: : 123iter [00:06, 26.59iter/s]Best score: 185.4951: : 124iter [00:06, 26.90iter/s]Best score: 185.4951: : 124iter [00:06, 26.90iter/s]Best score: 185.4951: : 125iter [00:06, 26.90iter/s]Best score: 185.4951: : 126iter [00:06, 26.90iter/s]Best score: 185.4951: : 127iter [00:06, 27.17iter/s]Best score: 185.4951: : 127iter [00:07, 27.17iter/s]Best score: 185.4951: : 128iter [00:07, 27.17iter/s]Best score: 185.4951: : 129iter [00:07, 27.17iter/s]Best score: 185.4951: : 130iter [00:07, 27.24iter/s]Best score: 185.4951: : 130iter [00:07, 27.24iter/s]Best score: 185.4951: : 131iter [00:07, 27.24iter/s]Best score: 185.4951: : 132iter [00:07, 27.24iter/s]Best score: 185.4951: : 133iter [00:07, 26.98iter/s]Best score: 185.4951: : 133iter [00:07, 26.98iter/s]Best score: 185.4951: : 134iter [00:07, 26.98iter/s]Best score: 185.4951: : 135iter [00:07, 26.98iter/s]Best score: 185.4951: : 136iter [00:07, 27.53iter/s]Best score: 185.4951: : 136iter [00:07, 27.53iter/s]Best score: 185.4951: : 137iter [00:07, 27.53iter/s]Best score: 185.4951: : 138iter [00:07, 27.53iter/s]Best score: 185.4951: : 139iter [00:07, 27.36iter/s]Best score: 185.4951: : 139iter [00:07, 27.36iter/s]Best score: 185.4951: : 140iter [00:07, 27.36iter/s]Best score: 185.4951: : 141iter [00:07, 27.36iter/s]Best score: 185.4951: : 142iter [00:07, 27.56iter/s]Best score: 185.4951: : 142iter [00:07, 27.56iter/s]Best score: 185.4951: : 143iter [00:07, 27.56iter/s]Best score: 185.4951: : 144iter [00:07, 27.56iter/s]Best score: 185.4951: : 145iter [00:07, 26.97iter/s]Best score: 185.4951: : 145iter [00:07, 26.97iter/s]Best score: 185.4951: : 146iter [00:07, 26.97iter/s]Best score: 185.4951: : 147iter [00:07, 26.97iter/s]Best score: 185.4951: : 148iter [00:07, 26.52iter/s]Best score: 185.4951: : 148iter [00:07, 26.52iter/s]
[ITER 150] Best: 185.4951
[PARAMS] Current best parameters:
  fx: 546.3876
  fy: 541.4233
  px: 1004.3890
  py: 779.9833
  k1: -0.09778540
  k2: 0.02992816
  k3: 0.03251446
  k4: -0.01301804
  p1: 0.01150292
  p2: 0.02848919
  p3: -0.00284642
  p4: 0.00359046
  s1: -0.0015
  s2: 0.0092
  s3: -0.0149
  s4: 0.0155
  tilt_x: 0.0028
  tilt_y: 0.0158
  scale: 3.2085
  rotation: -2.3931
Best score: 185.4951: : 149iter [00:07, 26.52iter/s]Best score: 185.4951: : 150iter [00:07, 26.52iter/s]Best score: 185.4951: : 151iter [00:07, 20.87iter/s]Best score: 185.4951: : 151iter [00:08, 20.87iter/s]Best score: 185.4951: : 152iter [00:08, 20.87iter/s]Best score: 185.4951: : 153iter [00:08, 20.87iter/s]Best score: 185.4951: : 154iter [00:08, 22.33iter/s]Best score: 185.4951: : 154iter [00:08, 22.33iter/s]Best score: 185.4951: : 155iter [00:08, 22.33iter/s]Best score: 185.4951: : 156iter [00:08, 22.33iter/s]Best score: 185.4951: : 157iter [00:08, 23.06iter/s]Best score: 185.4951: : 157iter [00:08, 23.06iter/s]Best score: 185.4951: : 158iter [00:08, 23.06iter/s]Best score: 143.5964: : 159iter [00:08, 23.06iter/s]Best score: 143.5964: : 160iter [00:08, 23.53iter/s]Best score: 143.5964: : 160iter [00:08, 23.53iter/s]Best score: 143.5964: : 161iter [00:08, 23.53iter/s]Best score: 143.5964: : 162iter [00:08, 23.53iter/s]Best score: 143.5964: : 163iter [00:08, 24.16iter/s]Best score: 143.5964: : 163iter [00:08, 24.16iter/s]Best score: 143.5964: : 164iter [00:08, 24.16iter/s]Best score: 143.5964: : 165iter [00:08, 24.16iter/s]Best score: 143.5964: : 166iter [00:08, 24.53iter/s]Best score: 143.5964: : 166iter [00:08, 24.53iter/s]Best score: 143.5964: : 167iter [00:08, 24.53iter/s]Best score: 143.5964: : 168iter [00:08, 24.53iter/s]Best score: 143.5964: : 169iter [00:08, 25.01iter/s]Best score: 143.5964: : 169iter [00:08, 25.01iter/s]Best score: 143.5964: : 170iter [00:08, 25.01iter/s]Best score: 143.5964: : 171iter [00:08, 25.01iter/s]Best score: 143.5964: : 172iter [00:08, 25.47iter/s]Best score: 143.5964: : 172iter [00:08, 25.47iter/s]Best score: 143.5964: : 173iter [00:08, 25.47iter/s]Best score: 143.5964: : 174iter [00:08, 25.47iter/s]Best score: 143.5964: : 175iter [00:08, 25.86iter/s]Best score: 143.5964: : 175iter [00:08, 25.86iter/s]Best score: 143.5964: : 176iter [00:08, 25.86iter/s]Best score: 143.5964: : 177iter [00:09, 25.86iter/s]Best score: 143.5964: : 178iter [00:09, 25.93iter/s]Best score: 143.5964: : 178iter [00:09, 25.93iter/s]Best score: 143.5964: : 179iter [00:09, 25.93iter/s]Best score: 143.5964: : 180iter [00:09, 25.93iter/s]Best score: 143.5964: : 181iter [00:09, 26.39iter/s]Best score: 143.5964: : 181iter [00:09, 26.39iter/s]Best score: 143.5964: : 182iter [00:09, 26.39iter/s]Best score: 143.5964: : 183iter [00:09, 26.39iter/s]Best score: 143.5964: : 184iter [00:09, 26.76iter/s]Best score: 143.5964: : 184iter [00:09, 26.76iter/s]Best score: 143.5964: : 185iter [00:09, 26.76iter/s]Best score: 143.5964: : 186iter [00:09, 26.76iter/s]Best score: 143.5964: : 187iter [00:09, 26.39iter/s]Best score: 143.5964: : 187iter [00:09, 26.39iter/s]Best score: 143.5964: : 188iter [00:09, 26.39iter/s]Best score: 71.5936: : 189iter [00:09, 26.39iter/s] Best score: 71.5936: : 190iter [00:09, 26.75iter/s]Best score: 71.5936: : 190iter [00:09, 26.75iter/s]Best score: 71.5936: : 191iter [00:09, 26.75iter/s]Best score: 71.5936: : 192iter [00:09, 26.75iter/s]Best score: 71.5936: : 193iter [00:09, 26.93iter/s]Best score: 71.5936: : 193iter [00:09, 26.93iter/s]Best score: 71.5936: : 194iter [00:09, 26.93iter/s]Best score: 71.5936: : 195iter [00:09, 26.93iter/s]Best score: 71.5936: : 196iter [00:09, 26.61iter/s]Best score: 71.5936: : 196iter [00:09, 26.61iter/s]Best score: 71.5936: : 197iter [00:09, 26.61iter/s]Best score: 71.5936: : 198iter [00:09, 26.61iter/s]Best score: 71.5936: : 199iter [00:09, 26.84iter/s]
[ITER 200] Best: 63.7669
[PARAMS] Current best parameters:
  fx: 578.1514
  fy: 580.2562
  px: 1005.5955
  py: 767.8086
  k1: -0.06026642
  k2: -0.02058874
  k3: 0.04372555
  k4: -0.01434281
  p1: 0.01451469
  p2: 0.03640465
  p3: -0.00774268
  p4: 0.00184105
  s1: -0.0402
  s2: -0.0104
  s3: -0.0211
  s4: 0.0098
  tilt_x: -0.0762
  tilt_y: -0.0819
  scale: 3.0042
  rotation: 0.0177
Best score: 63.7669: : 199iter [00:09, 26.84iter/s]Best score: 63.7669: : 200iter [00:09, 26.84iter/s]Best score: 63.7669: : 201iter [00:10, 26.84iter/s]Best score: 63.7669: : 202iter [00:10, 21.49iter/s]Best score: 63.7669: : 202iter [00:10, 21.49iter/s]Best score: 63.7669: : 203iter [00:10, 21.49iter/s]Best score: 63.7669: : 204iter [00:10, 21.49iter/s]Best score: 63.7669: : 205iter [00:10, 23.04iter/s]Best score: 63.7669: : 205iter [00:10, 23.04iter/s]Best score: 63.7669: : 206iter [00:10, 23.04iter/s]Best score: 63.7669: : 207iter [00:10, 23.04iter/s]Best score: 63.7669: : 208iter [00:10, 24.55iter/s]Best score: 63.7669: : 208iter [00:10, 24.55iter/s]Best score: 62.1045: : 209iter [00:10, 24.55iter/s]Best score: 62.1045: : 210iter [00:10, 24.55iter/s]Best score: 62.1045: : 211iter [00:10, 25.00iter/s]Best score: 62.1045: : 211iter [00:10, 25.00iter/s]Best score: 62.1045: : 212iter [00:10, 25.00iter/s]Best score: 62.1045: : 213iter [00:10, 25.00iter/s]Best score: 62.1045: : 214iter [00:10, 25.68iter/s]Best score: 62.1045: : 214iter [00:10, 25.68iter/s]Best score: 62.1045: : 215iter [00:10, 25.68iter/s]Best score: 62.1045: : 216iter [00:10, 25.68iter/s]Best score: 62.1045: : 217iter [00:10, 26.07iter/s]Best score: 62.1045: : 217iter [00:10, 26.07iter/s]Best score: 62.1045: : 218iter [00:10, 26.07iter/s]Best score: 41.2557: : 219iter [00:10, 26.07iter/s]Best score: 41.2557: : 220iter [00:10, 26.37iter/s]Best score: 41.2557: : 220iter [00:10, 26.37iter/s]Best score: 41.2557: : 221iter [00:10, 26.37iter/s]Best score: 41.2557: : 222iter [00:10, 26.37iter/s]Best score: 41.2557: : 223iter [00:10, 26.66iter/s]Best score: 41.2557: : 223iter [00:10, 26.66iter/s]Best score: 41.2557: : 224iter [00:10, 26.66iter/s]Best score: 41.2557: : 225iter [00:10, 26.66iter/s]Best score: 41.2557: : 226iter [00:10, 27.35iter/s]Best score: 41.2557: : 226iter [00:10, 27.35iter/s]Best score: 41.2557: : 227iter [00:10, 27.35iter/s]Best score: 41.2557: : 228iter [00:10, 27.35iter/s]Best score: 41.2557: : 229iter [00:10, 27.43iter/s]Best score: 41.2557: : 229iter [00:11, 27.43iter/s]Best score: 41.2557: : 230iter [00:11, 27.43iter/s]Best score: 41.2557: : 231iter [00:11, 27.43iter/s]Best score: 41.2557: : 232iter [00:11, 26.90iter/s]Best score: 41.2557: : 232iter [00:11, 26.90iter/s]Best score: 41.2557: : 233iter [00:11, 26.90iter/s]Best score: 41.2557: : 234iter [00:11, 26.90iter/s]Best score: 41.2557: : 235iter [00:11, 27.57iter/s]Best score: 41.2557: : 235iter [00:11, 27.57iter/s]Best score: 41.2557: : 236iter [00:11, 27.57iter/s]Best score: 41.2557: : 237iter [00:11, 27.57iter/s]Best score: 41.2557: : 238iter [00:11, 26.84iter/s]Best score: 41.2557: : 238iter [00:11, 26.84iter/s]Best score: 41.2557: : 239iter [00:11, 26.84iter/s]Best score: 41.2557: : 240iter [00:11, 26.84iter/s]Best score: 41.2557: : 241iter [00:11, 26.22iter/s]Best score: 41.2557: : 241iter [00:11, 26.22iter/s]Best score: 41.2557: : 242iter [00:11, 26.22iter/s]Best score: 41.2557: : 243iter [00:11, 26.22iter/s]Best score: 41.2557: : 244iter [00:11, 25.74iter/s]Best score: 41.2557: : 244iter [00:11, 25.74iter/s]Best score: 41.2557: : 245iter [00:11, 25.74iter/s]Best score: 41.2557: : 246iter [00:11, 25.74iter/s]Best score: 41.2557: : 247iter [00:11, 26.54iter/s]Best score: 41.2557: : 247iter [00:11, 26.54iter/s]Best score: 41.2557: : 248iter [00:11, 26.54iter/s]Best score: 18.1170: : 249iter [00:11, 26.54iter/s]Best score: 18.1170: : 250iter [00:11, 26.21iter/s]
[ITER 250] Best: 18.1170
[PARAMS] Current best parameters:
  fx: 609.7050
  fy: 608.1754
  px: 994.9669
  py: 771.4481
  k1: -0.04560606
  k2: -0.07014426
  k3: 0.04607368
  k4: -0.00710640
  p1: 0.01599850
  p2: 0.01522225
  p3: 0.00881938
  p4: 0.00511932
  s1: -0.0404
  s2: -0.0075
  s3: -0.0220
  s4: 0.0043
  tilt_x: -0.0455
  tilt_y: -0.0442
  scale: 3.0783
  rotation: -0.3307
Best score: 18.1170: : 250iter [00:11, 26.21iter/s]Best score: 18.1170: : 251iter [00:11, 26.21iter/s]Best score: 18.1170: : 252iter [00:12, 26.21iter/s]Best score: 18.1170: : 253iter [00:12, 20.84iter/s]Best score: 18.1170: : 253iter [00:12, 20.84iter/s]Best score: 18.1170: : 254iter [00:12, 20.84iter/s]Best score: 18.1170: : 255iter [00:12, 20.84iter/s]Best score: 18.1170: : 256iter [00:12, 22.41iter/s]Best score: 18.1170: : 256iter [00:12, 22.41iter/s]Best score: 18.1170: : 257iter [00:12, 22.41iter/s]Best score: 18.1170: : 258iter [00:12, 22.41iter/s]Best score: 18.1170: : 259iter [00:12, 24.03iter/s]Best score: 9.4252: : 259iter [00:12, 24.03iter/s] Best score: 9.4252: : 260iter [00:12, 24.03iter/s]Best score: 9.4252: : 261iter [00:12, 24.03iter/s]Best score: 9.4252: : 262iter [00:12, 24.58iter/s]Best score: 9.4252: : 262iter [00:12, 24.58iter/s]Best score: 9.4252: : 263iter [00:12, 24.58iter/s]Best score: 9.4252: : 264iter [00:12, 24.58iter/s]Best score: 9.4252: : 265iter [00:12, 25.41iter/s]Best score: 9.4252: : 265iter [00:12, 25.41iter/s]Best score: 9.4252: : 266iter [00:12, 25.41iter/s]Best score: 9.4252: : 267iter [00:12, 25.41iter/s]Best score: 9.4252: : 268iter [00:12, 25.94iter/s]Best score: 9.4252: : 268iter [00:12, 25.94iter/s]Best score: 9.4252: : 269iter [00:12, 25.94iter/s]Best score: 9.4252: : 270iter [00:12, 25.94iter/s]Best score: 9.4252: : 271iter [00:12, 26.37iter/s]Best score: 9.4252: : 271iter [00:12, 26.37iter/s]Best score: 9.4252: : 272iter [00:12, 26.37iter/s]Best score: 9.4252: : 273iter [00:12, 26.37iter/s]Best score: 9.4252: : 274iter [00:12, 26.85iter/s]Best score: 9.4252: : 274iter [00:12, 26.85iter/s]Best score: 9.4252: : 275iter [00:12, 26.85iter/s]Best score: 9.4252: : 276iter [00:12, 26.85iter/s]Best score: 9.4252: : 277iter [00:12, 27.17iter/s]Best score: 9.4252: : 277iter [00:12, 27.17iter/s]Best score: 9.4252: : 278iter [00:12, 27.17iter/s]Best score: 9.4252: : 279iter [00:12, 27.17iter/s]Best score: 9.4252: : 280iter [00:12, 27.16iter/s]Best score: 9.4252: : 280iter [00:13, 27.16iter/s]Best score: 9.4252: : 281iter [00:13, 27.16iter/s]Best score: 9.4252: : 282iter [00:13, 27.16iter/s]Best score: 9.4252: : 283iter [00:13, 27.56iter/s]Best score: 9.4252: : 283iter [00:13, 27.56iter/s]Best score: 9.4252: : 284iter [00:13, 27.56iter/s]Best score: 9.4252: : 285iter [00:13, 27.56iter/s]Best score: 9.4252: : 286iter [00:13, 27.43iter/s]Best score: 9.4252: : 286iter [00:13, 27.43iter/s]Best score: 9.4252: : 287iter [00:13, 27.43iter/s]Best score: 9.4252: : 288iter [00:13, 27.43iter/s]Best score: 9.4252: : 289iter [00:13, 26.75iter/s]Best score: 9.4252: : 289iter [00:13, 26.75iter/s]Best score: 9.4252: : 290iter [00:13, 26.75iter/s]Best score: 9.4252: : 291iter [00:13, 26.75iter/s]Best score: 9.4252: : 292iter [00:13, 26.34iter/s]Best score: 9.4252: : 292iter [00:13, 26.34iter/s]Best score: 9.4252: : 293iter [00:13, 26.34iter/s]Best score: 9.4252: : 294iter [00:13, 26.34iter/s]Best score: 9.4252: : 295iter [00:13, 26.55iter/s]Best score: 9.4252: : 295iter [00:13, 26.55iter/s]Best score: 9.4252: : 296iter [00:13, 26.55iter/s]Best score: 9.4252: : 297iter [00:13, 26.55iter/s]Best score: 9.4252: : 298iter [00:13, 26.77iter/s]Best score: 9.4252: : 298iter [00:13, 26.77iter/s]
[ITER 300] Best: 9.4252
[PARAMS] Current best parameters:
  fx: 600.8608
  fy: 602.0168
  px: 987.1548
  py: 762.1193
  k1: -0.00155780
  k2: -0.06826540
  k3: 0.02064366
  k4: 0.00124759
  p1: 0.01415971
  p2: 0.00739241
  p3: 0.00014232
  p4: -0.00158000
  s1: -0.0020
  s2: -0.0128
  s3: -0.0334
  s4: 0.0110
  tilt_x: -0.0715
  tilt_y: -0.0118
  scale: 2.8596
  rotation: -0.1590
Best score: 9.4252: : 299iter [00:13, 26.77iter/s]Best score: 9.4252: : 300iter [00:13, 26.77iter/s]Best score: 9.4252: : 301iter [00:13, 21.62iter/s]Best score: 9.4252: : 301iter [00:13, 21.62iter/s]Best score: 9.4252: : 302iter [00:13, 21.62iter/s]Best score: 9.4252: : 303iter [00:13, 21.62iter/s]Best score: 9.4252: : 304iter [00:13, 23.13iter/s]Best score: 9.4252: : 304iter [00:14, 23.13iter/s]Best score: 9.4252: : 305iter [00:14, 23.13iter/s]Best score: 9.4252: : 306iter [00:14, 23.13iter/s]Best score: 9.4252: : 307iter [00:14, 24.06iter/s]Best score: 9.4252: : 307iter [00:14, 24.06iter/s]Best score: 9.4252: : 308iter [00:14, 24.06iter/s]Best score: 6.4113: : 309iter [00:14, 24.06iter/s]Best score: 6.4113: : 310iter [00:14, 24.48iter/s]Best score: 6.4113: : 310iter [00:14, 24.48iter/s]Best score: 6.4113: : 311iter [00:14, 24.48iter/s]Best score: 6.4113: : 312iter [00:14, 24.48iter/s]Best score: 6.4113: : 313iter [00:14, 25.63iter/s]Best score: 6.4113: : 313iter [00:14, 25.63iter/s]Best score: 6.4113: : 314iter [00:14, 25.63iter/s]Best score: 6.4113: : 315iter [00:14, 25.63iter/s]Best score: 6.4113: : 316iter [00:14, 26.60iter/s]Best score: 6.4113: : 316iter [00:14, 26.60iter/s]Best score: 6.4113: : 317iter [00:14, 26.60iter/s]Best score: 6.4113: : 318iter [00:14, 26.60iter/s]Best score: 5.1648: : 319iter [00:14, 26.60iter/s]Best score: 5.1648: : 320iter [00:14, 22.79iter/s]Best score: 5.1648: : 320iter [00:14, 22.79iter/s]Best score: 5.1648: : 321iter [00:14, 22.79iter/s]Best score: 5.1648: : 322iter [00:14, 22.79iter/s]Best score: 5.1648: : 323iter [00:14, 22.79iter/s]Best score: 5.1648: : 324iter [00:14, 25.11iter/s]Best score: 5.1648: : 324iter [00:14, 25.11iter/s]Best score: 5.1648: : 325iter [00:14, 25.11iter/s]Best score: 5.1648: : 326iter [00:14, 25.11iter/s]Best score: 5.1648: : 327iter [00:14, 26.14iter/s]Best score: 5.1648: : 327iter [00:14, 26.14iter/s]Best score: 5.1648: : 328iter [00:14, 26.14iter/s]Best score: 4.4558: : 329iter [00:14, 26.14iter/s]Best score: 4.4558: : 330iter [00:14, 26.14iter/s]Best score: 4.4558: : 331iter [00:14, 27.38iter/s]Best score: 4.4558: : 331iter [00:15, 27.38iter/s]Best score: 4.4558: : 332iter [00:15, 27.38iter/s]Best score: 4.4558: : 333iter [00:15, 27.38iter/s]Best score: 4.4558: : 334iter [00:15, 27.84iter/s]Best score: 4.4558: : 334iter [00:15, 27.84iter/s]Best score: 4.4558: : 335iter [00:15, 27.84iter/s]Best score: 4.4558: : 336iter [00:15, 27.84iter/s]Best score: 4.4558: : 337iter [00:15, 27.95iter/s]Best score: 4.4558: : 337iter [00:15, 27.95iter/s]Best score: 4.4558: : 338iter [00:15, 27.95iter/s]Best score: 3.2733: : 339iter [00:15, 27.95iter/s]Best score: 3.2733: : 340iter [00:15, 27.95iter/s]Best score: 3.2733: : 341iter [00:15, 29.11iter/s]Best score: 3.2733: : 341iter [00:15, 29.11iter/s]Best score: 3.2733: : 342iter [00:15, 29.11iter/s]Best score: 3.2733: : 343iter [00:15, 29.11iter/s]Best score: 3.2733: : 344iter [00:15, 29.22iter/s]Best score: 3.2733: : 344iter [00:15, 29.22iter/s]Best score: 3.2733: : 345iter [00:15, 29.22iter/s]Best score: 3.2733: : 346iter [00:15, 29.22iter/s]Best score: 3.2733: : 347iter [00:15, 29.22iter/s]Best score: 3.2733: : 348iter [00:15, 29.40iter/s]Best score: 3.2733: : 348iter [00:15, 29.40iter/s]
[ITER 350] Best: 3.2733
[PARAMS] Current best parameters:
  fx: 646.5106
  fy: 648.4109
  px: 988.6037
  py: 765.5967
  k1: -0.06428591
  k2: -0.05958958
  k3: 0.04124069
  k4: -0.00781713
  p1: 0.00337970
  p2: 0.01182387
  p3: -0.00175186
  p4: 0.00749859
  s1: -0.0098
  s2: -0.0144
  s3: -0.0259
  s4: 0.0151
  tilt_x: -0.0491
  tilt_y: -0.0166
  scale: 2.8348
  rotation: -0.0415
Best score: 3.2733: : 349iter [00:15, 29.40iter/s]Best score: 3.2733: : 350iter [00:15, 29.40iter/s]Best score: 3.2733: : 351iter [00:15, 24.24iter/s]Best score: 3.2733: : 351iter [00:15, 24.24iter/s]Best score: 3.2733: : 352iter [00:15, 24.24iter/s]Best score: 3.2733: : 353iter [00:15, 24.24iter/s]Best score: 3.2733: : 354iter [00:15, 25.26iter/s]Best score: 3.2733: : 354iter [00:15, 25.26iter/s]Best score: 3.2733: : 355iter [00:15, 25.26iter/s]Best score: 3.2733: : 356iter [00:15, 25.26iter/s]Best score: 3.2733: : 357iter [00:15, 25.59iter/s]Best score: 3.2733: : 357iter [00:16, 25.59iter/s]Best score: 3.2733: : 358iter [00:16, 25.59iter/s]Best score: 2.5058: : 359iter [00:16, 25.59iter/s]Best score: 2.5058: : 360iter [00:16, 25.24iter/s]Best score: 2.5058: : 360iter [00:16, 25.24iter/s]Best score: 2.5058: : 361iter [00:16, 25.24iter/s]Best score: 2.5058: : 362iter [00:16, 25.24iter/s]Best score: 2.5058: : 363iter [00:16, 25.51iter/s]Best score: 2.5058: : 363iter [00:16, 25.51iter/s]Best score: 2.5058: : 364iter [00:16, 25.51iter/s]Best score: 2.5058: : 365iter [00:16, 25.51iter/s]Best score: 2.5058: : 366iter [00:16, 25.83iter/s]Best score: 2.5058: : 366iter [00:16, 25.83iter/s]Best score: 2.5058: : 367iter [00:16, 25.83iter/s]Best score: 2.5058: : 368iter [00:16, 25.83iter/s]Best score: 2.5058: : 369iter [00:16, 25.48iter/s]Best score: 2.2096: : 369iter [00:16, 25.48iter/s]Best score: 2.2096: : 370iter [00:16, 25.48iter/s]Best score: 2.2096: : 371iter [00:16, 25.48iter/s]Best score: 2.2096: : 372iter [00:16, 25.03iter/s]Best score: 2.2096: : 372iter [00:16, 25.03iter/s]Best score: 2.2096: : 373iter [00:16, 25.03iter/s]Best score: 2.2096: : 374iter [00:16, 25.03iter/s]Best score: 2.2096: : 375iter [00:16, 25.56iter/s]Best score: 2.2096: : 375iter [00:16, 25.56iter/s]Best score: 2.2096: : 376iter [00:16, 25.56iter/s]Best score: 2.2096: : 377iter [00:16, 25.56iter/s]Best score: 2.2096: : 378iter [00:16, 25.82iter/s]Best score: 2.2096: : 378iter [00:16, 25.82iter/s]Best score: 2.2096: : 379iter [00:16, 25.82iter/s]Best score: 2.2096: : 380iter [00:16, 25.82iter/s]Best score: 2.2096: : 381iter [00:16, 25.46iter/s]Best score: 2.2096: : 381iter [00:16, 25.46iter/s]Best score: 2.2096: : 382iter [00:16, 25.46iter/s]Best score: 2.2096: : 383iter [00:17, 25.46iter/s]Best score: 2.2096: : 384iter [00:17, 26.04iter/s]Best score: 2.2096: : 384iter [00:17, 26.04iter/s]Best score: 2.2096: : 385iter [00:17, 26.04iter/s]Best score: 2.2096: : 386iter [00:17, 26.04iter/s]Best score: 2.2096: : 387iter [00:17, 25.75iter/s]Best score: 2.2096: : 387iter [00:17, 25.75iter/s]Best score: 2.2096: : 388iter [00:17, 25.75iter/s]Best score: 2.2032: : 389iter [00:17, 25.75iter/s]Best score: 2.2032: : 390iter [00:17, 25.63iter/s]Best score: 2.2032: : 390iter [00:17, 25.63iter/s]Best score: 2.2032: : 391iter [00:17, 25.63iter/s]Best score: 2.2032: : 392iter [00:17, 25.63iter/s]Best score: 2.2032: : 393iter [00:17, 25.41iter/s]Best score: 2.2032: : 393iter [00:17, 25.41iter/s]Best score: 2.2032: : 394iter [00:17, 25.41iter/s]Best score: 2.2032: : 395iter [00:17, 25.41iter/s]Best score: 2.2032: : 396iter [00:17, 25.59iter/s]Best score: 2.2032: : 396iter [00:17, 25.59iter/s]Best score: 2.2032: : 397iter [00:17, 25.59iter/s]Best score: 2.2032: : 398iter [00:17, 25.59iter/s]Best score: 2.2032: : 399iter [00:17, 25.57iter/s]
[ITER 400] Best: 2.2032
[PARAMS] Current best parameters:
  fx: 650.6171
  fy: 651.2523
  px: 989.5401
  py: 764.7986
  k1: -0.06605538
  k2: -0.05427615
  k3: 0.03345551
  k4: -0.00497404
  p1: 0.00147501
  p2: 0.00652464
  p3: 0.00340321
  p4: 0.00872305
  s1: -0.0083
  s2: -0.0152
  s3: -0.0256
  s4: 0.0076
  tilt_x: -0.0513
  tilt_y: -0.0303
  scale: 2.8168
  rotation: -0.3529
Best score: 2.2032: : 399iter [00:17, 25.57iter/s]Best score: 2.2032: : 400iter [00:17, 25.57iter/s]Best score: 2.2032: : 401iter [00:17, 25.57iter/s]Best score: 2.2032: : 402iter [00:17, 20.37iter/s]Best score: 2.2032: : 402iter [00:17, 20.37iter/s]Best score: 2.2032: : 403iter [00:17, 20.37iter/s]Best score: 2.2032: : 404iter [00:17, 20.37iter/s]Best score: 2.2032: : 405iter [00:17, 22.25iter/s]Best score: 2.2032: : 405iter [00:17, 22.25iter/s]Best score: 2.2032: : 406iter [00:17, 22.25iter/s]Best score: 2.2032: : 407iter [00:18, 22.25iter/s]Best score: 2.2032: : 408iter [00:18, 23.83iter/s]Best score: 2.2032: : 408iter [00:18, 23.83iter/s]Best score: 1.9758: : 409iter [00:18, 23.83iter/s]Best score: 1.9758: : 410iter [00:18, 23.83iter/s]Best score: 1.9758: : 411iter [00:18, 24.36iter/s]Best score: 1.9758: : 411iter [00:18, 24.36iter/s]Best score: 1.9758: : 412iter [00:18, 24.36iter/s]Best score: 1.9758: : 413iter [00:18, 24.36iter/s]Best score: 1.9758: : 414iter [00:18, 25.00iter/s]Best score: 1.9758: : 414iter [00:18, 25.00iter/s]Best score: 1.9758: : 415iter [00:18, 25.00iter/s]Best score: 1.9758: : 416iter [00:18, 25.00iter/s]Best score: 1.9758: : 417iter [00:18, 25.01iter/s]Best score: 1.9758: : 417iter [00:18, 25.01iter/s]Best score: 1.9758: : 418iter [00:18, 25.01iter/s]Best score: 1.7939: : 419iter [00:18, 25.01iter/s]Best score: 1.7939: : 420iter [00:18, 25.14iter/s]Best score: 1.7939: : 420iter [00:18, 25.14iter/s]Best score: 1.7939: : 421iter [00:18, 25.14iter/s]Best score: 1.7939: : 422iter [00:18, 25.14iter/s]Best score: 1.7939: : 423iter [00:18, 25.77iter/s]Best score: 1.7939: : 423iter [00:18, 25.77iter/s]Best score: 1.7939: : 424iter [00:18, 25.77iter/s]Best score: 1.7939: : 425iter [00:18, 25.77iter/s]Best score: 1.7939: : 426iter [00:18, 26.23iter/s]Best score: 1.7939: : 426iter [00:18, 26.23iter/s]Best score: 1.7939: : 427iter [00:18, 26.23iter/s]Best score: 1.7939: : 428iter [00:18, 26.23iter/s]Best score: 1.7939: : 429iter [00:18, 26.41iter/s]Best score: 1.6923: : 429iter [00:18, 26.41iter/s]Best score: 1.6923: : 430iter [00:18, 26.41iter/s]Best score: 1.6923: : 431iter [00:18, 26.41iter/s]Best score: 1.6923: : 432iter [00:18, 26.72iter/s]Best score: 1.6923: : 432iter [00:18, 26.72iter/s]Best score: 1.6923: : 433iter [00:19, 26.72iter/s]Best score: 1.6923: : 434iter [00:19, 26.72iter/s]Best score: 1.6923: : 435iter [00:19, 27.33iter/s]Best score: 1.6923: : 435iter [00:19, 27.33iter/s]Best score: 1.6923: : 436iter [00:19, 27.33iter/s]Best score: 1.6923: : 437iter [00:19, 27.33iter/s]Best score: 1.6923: : 438iter [00:19, 27.42iter/s]Best score: 1.6923: : 438iter [00:19, 27.42iter/s]Best score: 1.5668: : 439iter [00:19, 27.42iter/s]Best score: 1.5668: : 440iter [00:19, 27.42iter/s]Best score: 1.5668: : 441iter [00:19, 27.02iter/s]Best score: 1.5668: : 441iter [00:19, 27.02iter/s]Best score: 1.5668: : 442iter [00:19, 27.02iter/s]Best score: 1.5668: : 443iter [00:19, 27.02iter/s]Best score: 1.5668: : 444iter [00:19, 27.02iter/s]Best score: 1.5668: : 444iter [00:19, 27.02iter/s]Best score: 1.5668: : 445iter [00:19, 27.02iter/s]Best score: 1.5668: : 446iter [00:19, 27.02iter/s]Best score: 1.5668: : 447iter [00:19, 27.21iter/s]Best score: 1.5668: : 447iter [00:19, 27.21iter/s]Best score: 1.5668: : 448iter [00:19, 27.21iter/s]
[ITER 450] Best: 1.3995
[PARAMS] Current best parameters:
  fx: 654.1830
  fy: 654.8468
  px: 988.5885
  py: 764.5001
  k1: -0.06087300
  k2: -0.07766612
  k3: 0.05386934
  k4: -0.01059974
  p1: 0.00237565
  p2: 0.01021099
  p3: 0.00094297
  p4: 0.00764729
  s1: -0.0132
  s2: -0.0117
  s3: -0.0112
  s4: -0.0001
  tilt_x: -0.0529
  tilt_y: -0.0155
  scale: 2.8195
  rotation: -0.4069
Best score: 1.3995: : 449iter [00:19, 27.21iter/s]Best score: 1.3995: : 450iter [00:19, 26.58iter/s]Best score: 1.3995: : 450iter [00:19, 26.58iter/s]Best score: 1.3995: : 451iter [00:19, 26.58iter/s]Best score: 1.3995: : 452iter [00:19, 26.58iter/s]Best score: 1.3995: : 453iter [00:19, 21.46iter/s]Best score: 1.3995: : 453iter [00:19, 21.46iter/s]Best score: 1.3995: : 454iter [00:19, 21.46iter/s]Best score: 1.3995: : 455iter [00:19, 21.46iter/s]Best score: 1.3995: : 456iter [00:19, 23.07iter/s]Best score: 1.3995: : 456iter [00:19, 23.07iter/s]Best score: 1.3995: : 457iter [00:19, 23.07iter/s]Best score: 1.3995: : 458iter [00:20, 23.07iter/s]Best score: 1.3995: : 459iter [00:20, 24.44iter/s]Best score: 0.9720: : 459iter [00:20, 24.44iter/s]Best score: 0.9720: : 460iter [00:20, 24.44iter/s]Best score: 0.9720: : 461iter [00:20, 24.44iter/s]Best score: 0.9720: : 462iter [00:20, 25.36iter/s]Best score: 0.9720: : 462iter [00:20, 25.36iter/s]Best score: 0.9720: : 463iter [00:20, 25.36iter/s]Best score: 0.9720: : 464iter [00:20, 25.36iter/s]Best score: 0.9720: : 465iter [00:20, 26.53iter/s]Best score: 0.9720: : 465iter [00:20, 26.53iter/s]Best score: 0.9720: : 466iter [00:20, 26.53iter/s]Best score: 0.9720: : 467iter [00:20, 26.53iter/s]Best score: 0.9720: : 468iter [00:20, 26.83iter/s]Best score: 0.9720: : 468iter [00:20, 26.83iter/s]Best score: 0.8971: : 469iter [00:20, 26.83iter/s]Best score: 0.8971: : 470iter [00:20, 26.83iter/s]Best score: 0.8971: : 471iter [00:20, 26.52iter/s]Best score: 0.8971: : 471iter [00:20, 26.52iter/s]Best score: 0.8971: : 472iter [00:20, 26.52iter/s]Best score: 0.8971: : 473iter [00:20, 26.52iter/s]Best score: 0.8971: : 474iter [00:20, 26.39iter/s]Best score: 0.8971: : 474iter [00:20, 26.39iter/s]Best score: 0.8971: : 475iter [00:20, 26.39iter/s]Best score: 0.8971: : 476iter [00:20, 26.39iter/s]Best score: 0.8971: : 477iter [00:20, 26.60iter/s]Best score: 0.8971: : 477iter [00:20, 26.60iter/s]Best score: 0.8971: : 478iter [00:20, 26.60iter/s]Best score: 0.7817: : 479iter [00:20, 26.60iter/s]Best score: 0.7817: : 480iter [00:20, 27.03iter/s]Best score: 0.7817: : 480iter [00:20, 27.03iter/s]Best score: 0.7817: : 481iter [00:20, 27.03iter/s]Best score: 0.7817: : 482iter [00:20, 27.03iter/s]Best score: 0.7817: : 483iter [00:20, 27.03iter/s]Best score: 0.7817: : 484iter [00:20, 28.25iter/s]Best score: 0.7817: : 484iter [00:20, 28.25iter/s]Best score: 0.7817: : 485iter [00:20, 28.25iter/s]Best score: 0.7817: : 486iter [00:21, 28.25iter/s]Best score: 0.7817: : 487iter [00:21, 28.41iter/s]Best score: 0.7817: : 487iter [00:21, 28.41iter/s]Best score: 0.7817: : 488iter [00:21, 28.41iter/s]Best score: 0.6807: : 489iter [00:21, 28.41iter/s]Best score: 0.6807: : 490iter [00:21, 28.30iter/s]Best score: 0.6807: : 490iter [00:21, 28.30iter/s]Best score: 0.6807: : 491iter [00:21, 28.30iter/s]Best score: 0.6807: : 492iter [00:21, 28.30iter/s]Best score: 0.6807: : 493iter [00:21, 28.64iter/s]Best score: 0.6807: : 493iter [00:21, 28.64iter/s]Best score: 0.6807: : 494iter [00:21, 28.64iter/s]Best score: 0.6807: : 495iter [00:21, 28.64iter/s]Best score: 0.6807: : 496iter [00:21, 28.64iter/s]Best score: 0.6807: : 497iter [00:21, 28.91iter/s]Best score: 0.6807: : 497iter [00:21, 28.91iter/s]Best score: 0.6807: : 498iter [00:21, 28.91iter/s]Best score: 0.6807: : 499iter [00:21, 28.91iter/s]Best score: 0.6807: : 500iter [00:21, 29.01iter/s]
[ITER 500] Best: 0.6807
[PARAMS] Current best parameters:
  fx: 641.2823
  fy: 641.5742
  px: 991.4707
  py: 769.9782
  k1: -0.05714244
  k2: -0.08643245
  k3: 0.06913742
  k4: -0.01594591
  p1: 0.01024502
  p2: 0.01626179
  p3: -0.01698411
  p4: 0.00056732
  s1: -0.0127
  s2: 0.0055
  s3: 0.0110
  s4: 0.0017
  tilt_x: -0.0383
  tilt_y: -0.0228
  scale: 2.8773
  rotation: -0.3747
Best score: 0.6807: : 500iter [00:21, 29.01iter/s]Best score: 0.6807: : 501iter [00:21, 29.01iter/s]Best score: 0.6807: : 502iter [00:21, 29.01iter/s]Best score: 0.6807: : 503iter [00:21, 22.86iter/s]Best score: 0.6807: : 503iter [00:21, 22.86iter/s]Best score: 0.6807: : 504iter [00:21, 22.86iter/s]Best score: 0.6807: : 505iter [00:21, 22.86iter/s]Best score: 0.6807: : 506iter [00:21, 23.90iter/s]Best score: 0.6807: : 506iter [00:21, 23.90iter/s]Best score: 0.6807: : 507iter [00:21, 23.90iter/s]Best score: 0.6807: : 508iter [00:21, 23.90iter/s]Best score: 0.6807: : 509iter [00:21, 25.15iter/s]Best score: 0.6807: : 509iter [00:21, 25.15iter/s]Best score: 0.6807: : 510iter [00:21, 25.15iter/s]Best score: 0.6807: : 511iter [00:21, 25.15iter/s]Best score: 0.6807: : 512iter [00:21, 26.22iter/s]Best score: 0.6807: : 512iter [00:22, 26.22iter/s]Best score: 0.6807: : 513iter [00:22, 26.22iter/s]Best score: 0.6807: : 514iter [00:22, 26.22iter/s]Best score: 0.6807: : 515iter [00:22, 26.22iter/s]Best score: 0.6807: : 516iter [00:22, 27.76iter/s]Best score: 0.6807: : 516iter [00:22, 27.76iter/s]Best score: 0.6807: : 517iter [00:22, 27.76iter/s]Best score: 0.6807: : 518iter [00:22, 27.76iter/s]Best score: 0.6807: : 519iter [00:22, 28.13iter/s]Best score: 0.6807: : 519iter [00:22, 28.13iter/s]Best score: 0.6807: : 520iter [00:22, 28.13iter/s]Best score: 0.6807: : 521iter [00:22, 28.13iter/s]Best score: 0.6807: : 522iter [00:22, 28.25iter/s]Best score: 0.6807: : 522iter [00:22, 28.25iter/s]Best score: 0.6807: : 523iter [00:22, 28.25iter/s]Best score: 0.6807: : 524iter [00:22, 28.25iter/s]Best score: 0.6807: : 525iter [00:22, 28.25iter/s]Best score: 0.6807: : 526iter [00:22, 28.99iter/s]Best score: 0.6807: : 526iter [00:22, 28.99iter/s]Best score: 0.6807: : 527iter [00:22, 28.99iter/s]Best score: 0.6807: : 528iter [00:22, 28.99iter/s]Best score: 0.5781: : 529iter [00:22, 28.99iter/s]Best score: 0.5781: : 530iter [00:22, 29.31iter/s]Best score: 0.5781: : 530iter [00:22, 29.31iter/s]Best score: 0.5781: : 531iter [00:22, 29.31iter/s]Best score: 0.5781: : 532iter [00:22, 29.31iter/s]Best score: 0.5781: : 533iter [00:22, 29.31iter/s]Best score: 0.5781: : 534iter [00:22, 29.71iter/s]Best score: 0.5781: : 534iter [00:22, 29.71iter/s]Best score: 0.5781: : 535iter [00:22, 29.71iter/s]Best score: 0.5781: : 536iter [00:22, 29.71iter/s]Best score: 0.5781: : 537iter [00:22, 29.71iter/s]Best score: 0.5781: : 538iter [00:22, 30.16iter/s]Best score: 0.5781: : 538iter [00:22, 30.16iter/s]Best score: 0.5456: : 539iter [00:22, 30.16iter/s]Best score: 0.5456: : 540iter [00:22, 30.16iter/s]Best score: 0.5456: : 541iter [00:22, 30.16iter/s]Best score: 0.5456: : 542iter [00:22, 29.58iter/s]Best score: 0.5456: : 542iter [00:23, 29.58iter/s]Best score: 0.5456: : 543iter [00:23, 29.58iter/s]Best score: 0.5456: : 544iter [00:23, 29.58iter/s]Best score: 0.5456: : 545iter [00:23, 28.15iter/s]Best score: 0.5456: : 545iter [00:23, 28.15iter/s]Best score: 0.5456: : 546iter [00:23, 28.15iter/s]Best score: 0.5456: : 547iter [00:23, 28.15iter/s]Best score: 0.5456: : 548iter [00:23, 27.34iter/s]Best score: 0.5456: : 548iter [00:23, 27.34iter/s]
[ITER 550] Best: 0.4820
[PARAMS] Current best parameters:
  fx: 629.8940
  fy: 630.3124
  px: 991.9176
  py: 769.5382
  k1: -0.04057359
  k2: -0.09103813
  k3: 0.06838936
  k4: -0.01569060
  p1: 0.01266971
  p2: 0.02101167
  p3: -0.01513856
  p4: -0.00526376
  s1: -0.0136
  s2: 0.0069
  s3: 0.0136
  s4: 0.0028
  tilt_x: -0.0447
  tilt_y: -0.0160
  scale: 2.8668
  rotation: -0.2959
Best score: 0.4820: : 549iter [00:23, 27.34iter/s]Best score: 0.4820: : 550iter [00:23, 27.34iter/s]Best score: 0.4820: : 551iter [00:23, 21.57iter/s]Best score: 0.4820: : 551iter [00:23, 21.57iter/s]Best score: 0.4820: : 552iter [00:23, 21.57iter/s]Best score: 0.4820: : 553iter [00:23, 21.57iter/s]Best score: 0.4820: : 554iter [00:23, 22.87iter/s]Best score: 0.4820: : 554iter [00:23, 22.87iter/s]Best score: 0.4820: : 555iter [00:23, 22.87iter/s]Best score: 0.4820: : 556iter [00:23, 22.87iter/s]Best score: 0.4820: : 557iter [00:23, 24.25iter/s]Best score: 0.4820: : 557iter [00:23, 24.25iter/s]Best score: 0.4820: : 558iter [00:23, 24.25iter/s]Best score: 0.4820: : 559iter [00:23, 24.25iter/s]Best score: 0.4820: : 560iter [00:23, 24.65iter/s]Best score: 0.4820: : 560iter [00:23, 24.65iter/s]Best score: 0.4820: : 561iter [00:23, 24.65iter/s]Best score: 0.4820: : 562iter [00:23, 24.65iter/s]Best score: 0.4820: : 563iter [00:23, 25.89iter/s]Best score: 0.4820: : 563iter [00:23, 25.89iter/s]Best score: 0.4820: : 564iter [00:23, 25.89iter/s]Best score: 0.4820: : 565iter [00:24, 25.89iter/s]Best score: 0.4820: : 566iter [00:24, 22.77iter/s]Best score: 0.4820: : 566iter [00:24, 22.77iter/s]Best score: 0.4820: : 567iter [00:24, 22.77iter/s]Best score: 0.4820: : 568iter [00:24, 22.77iter/s]Best score: 0.4820: : 569iter [00:24, 24.41iter/s]Best score: 0.4764: : 569iter [00:24, 24.41iter/s]Best score: 0.4764: : 570iter [00:24, 24.41iter/s]Best score: 0.4764: : 571iter [00:24, 24.41iter/s]Best score: 0.4764: : 572iter [00:24, 25.43iter/s]Best score: 0.4764: : 572iter [00:24, 25.43iter/s]Best score: 0.4764: : 573iter [00:24, 25.43iter/s]Best score: 0.4764: : 574iter [00:24, 25.43iter/s]Best score: 0.4764: : 575iter [00:24, 26.23iter/s]Best score: 0.4764: : 575iter [00:24, 26.23iter/s]Best score: 0.4764: : 576iter [00:24, 26.23iter/s]Best score: 0.4764: : 577iter [00:24, 26.23iter/s]Best score: 0.4764: : 578iter [00:24, 26.23iter/s]Best score: 0.4764: : 579iter [00:24, 27.32iter/s]Best score: 0.4764: : 579iter [00:24, 27.32iter/s]Best score: 0.4764: : 580iter [00:24, 27.32iter/s]Best score: 0.4764: : 581iter [00:24, 27.32iter/s]Best score: 0.4764: : 582iter [00:24, 27.35iter/s]Best score: 0.4764: : 582iter [00:24, 27.35iter/s]Best score: 0.4764: : 583iter [00:24, 27.35iter/s]Best score: 0.4764: : 584iter [00:24, 27.35iter/s]Best score: 0.4764: : 585iter [00:24, 27.14iter/s]Best score: 0.4764: : 585iter [00:24, 27.14iter/s]Best score: 0.4764: : 586iter [00:24, 27.14iter/s]Best score: 0.4764: : 587iter [00:24, 27.14iter/s]Best score: 0.4764: : 588iter [00:24, 26.56iter/s]Best score: 0.4764: : 588iter [00:24, 26.56iter/s]Best score: 0.4673: : 589iter [00:24, 26.56iter/s]Best score: 0.4673: : 590iter [00:24, 26.56iter/s]Best score: 0.4673: : 591iter [00:24, 26.73iter/s]Best score: 0.4673: : 591iter [00:24, 26.73iter/s]Best score: 0.4673: : 592iter [00:25, 26.73iter/s]Best score: 0.4673: : 593iter [00:25, 26.73iter/s]Best score: 0.4673: : 594iter [00:25, 27.19iter/s]Best score: 0.4673: : 594iter [00:25, 27.19iter/s]Best score: 0.4673: : 595iter [00:25, 27.19iter/s]Best score: 0.4673: : 596iter [00:25, 27.19iter/s]Best score: 0.4673: : 597iter [00:25, 27.19iter/s]Best score: 0.4673: : 598iter [00:25, 28.37iter/s]Best score: 0.4673: : 598iter [00:25, 28.37iter/s]
[ITER 600] Best: 0.4245
[PARAMS] Current best parameters:
  fx: 626.0422
  fy: 626.6598
  px: 991.3470
  py: 768.9406
  k1: -0.03812756
  k2: -0.08750365
  k3: 0.06519112
  k4: -0.01500959
  p1: 0.01205340
  p2: 0.02339370
  p3: -0.01091096
  p4: -0.00437370
  s1: -0.0181
  s2: 0.0044
  s3: 0.0077
  s4: 0.0023
  tilt_x: -0.0473
  tilt_y: -0.0068
  scale: 2.8659
  rotation: -0.2896
Best score: 0.4245: : 599iter [00:25, 28.37iter/s]Best score: 0.4245: : 600iter [00:25, 28.37iter/s]Best score: 0.4245: : 601iter [00:25, 21.78iter/s]Best score: 0.4245: : 601iter [00:25, 21.78iter/s]Best score: 0.4245: : 602iter [00:25, 21.78iter/s]Best score: 0.4245: : 603iter [00:25, 21.78iter/s]Best score: 0.4245: : 604iter [00:25, 22.62iter/s]Best score: 0.4245: : 604iter [00:25, 22.62iter/s]Best score: 0.4245: : 605iter [00:25, 22.62iter/s]Best score: 0.4245: : 606iter [00:25, 22.62iter/s]Best score: 0.4245: : 607iter [00:25, 23.70iter/s]Best score: 0.4245: : 607iter [00:25, 23.70iter/s]Best score: 0.4245: : 608iter [00:25, 23.70iter/s]Best score: 0.4127: : 609iter [00:25, 23.70iter/s]Best score: 0.4127: : 610iter [00:25, 24.56iter/s]Best score: 0.4127: : 610iter [00:25, 24.56iter/s]Best score: 0.4127: : 611iter [00:25, 24.56iter/s]Best score: 0.4127: : 612iter [00:25, 24.56iter/s]Best score: 0.4127: : 613iter [00:25, 25.80iter/s]Best score: 0.4127: : 613iter [00:25, 25.80iter/s]Best score: 0.4127: : 614iter [00:25, 25.80iter/s]Best score: 0.4127: : 615iter [00:25, 25.80iter/s]Best score: 0.4127: : 616iter [00:25, 26.57iter/s]Best score: 0.4127: : 616iter [00:25, 26.57iter/s]Best score: 0.4127: : 617iter [00:26, 26.57iter/s]Best score: 0.4127: : 618iter [00:26, 26.57iter/s]Best score: 0.4127: : 619iter [00:26, 26.57iter/s]Best score: 0.4127: : 620iter [00:26, 27.81iter/s]Best score: 0.4127: : 620iter [00:26, 27.81iter/s]Best score: 0.4127: : 621iter [00:26, 27.81iter/s]Best score: 0.4127: : 622iter [00:26, 27.81iter/s]Best score: 0.4127: : 623iter [00:26, 28.24iter/s]Best score: 0.4127: : 623iter [00:26, 28.24iter/s]Best score: 0.4127: : 624iter [00:26, 28.24iter/s]Best score: 0.4127: : 625iter [00:26, 28.24iter/s]Best score: 0.4127: : 626iter [00:26, 28.24iter/s]Best score: 0.4127: : 627iter [00:26, 28.97iter/s]Best score: 0.4127: : 627iter [00:26, 28.97iter/s]Best score: 0.4127: : 628iter [00:26, 28.97iter/s]Best score: 0.4127: : 629iter [00:26, 28.97iter/s]Best score: 0.4127: : 630iter [00:26, 28.84iter/s]Best score: 0.4127: : 630iter [00:26, 28.84iter/s]Best score: 0.4127: : 631iter [00:26, 28.84iter/s]Best score: 0.4127: : 632iter [00:26, 28.84iter/s]Best score: 0.4127: : 633iter [00:26, 28.61iter/s]Best score: 0.4127: : 633iter [00:26, 28.61iter/s]Best score: 0.4127: : 634iter [00:26, 28.61iter/s]Best score: 0.4127: : 635iter [00:26, 28.61iter/s]Best score: 0.4127: : 636iter [00:26, 28.91iter/s]Best score: 0.4127: : 636iter [00:26, 28.91iter/s]Best score: 0.4127: : 637iter [00:26, 28.91iter/s]Best score: 0.4127: : 638iter [00:26, 28.91iter/s]Best score: 0.4127: : 639iter [00:26, 29.19iter/s]Best score: 0.4127: : 639iter [00:26, 29.19iter/s]Best score: 0.4127: : 640iter [00:26, 29.19iter/s]Best score: 0.4127: : 641iter [00:26, 29.19iter/s]Best score: 0.4127: : 642iter [00:26, 28.73iter/s]Best score: 0.4127: : 642iter [00:26, 28.73iter/s]Best score: 0.4127: : 643iter [00:26, 28.73iter/s]Best score: 0.4127: : 644iter [00:26, 28.73iter/s]Best score: 0.4127: : 645iter [00:26, 28.51iter/s]Best score: 0.4127: : 645iter [00:26, 28.51iter/s]Best score: 0.4127: : 646iter [00:27, 28.51iter/s]Best score: 0.4127: : 647iter [00:27, 28.51iter/s]Best score: 0.4127: : 648iter [00:27, 28.48iter/s]Best score: 0.4127: : 648iter [00:27, 28.48iter/s]
[ITER 650] Best: 0.3992
[PARAMS] Current best parameters:
  fx: 628.0065
  fy: 628.5369
  px: 993.4757
  py: 768.9446
  k1: -0.03539280
  k2: -0.09577281
  k3: 0.07054814
  k4: -0.01611221
  p1: 0.01211727
  p2: 0.02624098
  p3: -0.02009079
  p4: -0.00622697
  s1: -0.0101
  s2: 0.0075
  s3: 0.0182
  s4: 0.0049
  tilt_x: -0.0495
  tilt_y: -0.0127
  scale: 2.8633
  rotation: -0.2989
Best score: 0.3992: : 649iter [00:27, 28.48iter/s]Best score: 0.3992: : 650iter [00:27, 28.48iter/s]Best score: 0.3992: : 651iter [00:27, 23.21iter/s]Best score: 0.3992: : 651iter [00:27, 23.21iter/s]Best score: 0.3992: : 652iter [00:27, 23.21iter/s]Best score: 0.3992: : 653iter [00:27, 23.21iter/s]Best score: 0.3992: : 654iter [00:27, 24.74iter/s]Best score: 0.3992: : 654iter [00:27, 24.74iter/s]Best score: 0.3992: : 655iter [00:27, 24.74iter/s]Best score: 0.3992: : 656iter [00:27, 24.74iter/s]Best score: 0.3992: : 657iter [00:27, 26.04iter/s]Best score: 0.3992: : 657iter [00:27, 26.04iter/s]Best score: 0.3992: : 658iter [00:27, 26.04iter/s]Best score: 0.3568: : 659iter [00:27, 26.04iter/s]Best score: 0.3568: : 660iter [00:27, 25.55iter/s]Best score: 0.3568: : 660iter [00:27, 25.55iter/s]Best score: 0.3568: : 661iter [00:27, 25.55iter/s]Best score: 0.3568: : 662iter [00:27, 25.55iter/s]Best score: 0.3568: : 663iter [00:27, 26.15iter/s]Best score: 0.3568: : 663iter [00:27, 26.15iter/s]Best score: 0.3568: : 664iter [00:27, 26.15iter/s]Best score: 0.3568: : 665iter [00:27, 26.15iter/s]Best score: 0.3568: : 666iter [00:27, 26.30iter/s]Best score: 0.3568: : 666iter [00:27, 26.30iter/s]Best score: 0.3568: : 667iter [00:27, 26.30iter/s]Best score: 0.3568: : 668iter [00:27, 26.30iter/s]Best score: 0.3568: : 669iter [00:27, 27.16iter/s]Best score: 0.3266: : 669iter [00:27, 27.16iter/s]Best score: 0.3266: : 670iter [00:27, 27.16iter/s]Best score: 0.3266: : 671iter [00:28, 27.16iter/s]Best score: 0.3266: : 672iter [00:28, 27.44iter/s]Best score: 0.3266: : 672iter [00:28, 27.44iter/s]Best score: 0.3266: : 673iter [00:28, 27.44iter/s]Best score: 0.3266: : 674iter [00:28, 27.44iter/s]Best score: 0.3266: : 675iter [00:28, 28.03iter/s]Best score: 0.3266: : 675iter [00:28, 28.03iter/s]Best score: 0.3266: : 676iter [00:28, 28.03iter/s]Best score: 0.3266: : 677iter [00:28, 28.03iter/s]Best score: 0.3266: : 678iter [00:28, 28.19iter/s]Best score: 0.3266: : 678iter [00:28, 28.19iter/s]Best score: 0.3266: : 679iter [00:28, 28.19iter/s]Best score: 0.3266: : 680iter [00:28, 28.19iter/s]Best score: 0.3266: : 681iter [00:28, 27.76iter/s]Best score: 0.3266: : 681iter [00:28, 27.76iter/s]Best score: 0.3266: : 682iter [00:28, 27.76iter/s]Best score: 0.3266: : 683iter [00:28, 27.76iter/s]Best score: 0.3266: : 684iter [00:28, 27.30iter/s]Best score: 0.3266: : 684iter [00:28, 27.30iter/s]Best score: 0.3266: : 685iter [00:28, 27.30iter/s]Best score: 0.3266: : 686iter [00:28, 27.30iter/s]Best score: 0.3266: : 687iter [00:28, 27.50iter/s]Best score: 0.3266: : 687iter [00:28, 27.50iter/s]Best score: 0.3266: : 688iter [00:28, 27.50iter/s]Best score: 0.3266: : 689iter [00:28, 27.50iter/s]Best score: 0.3266: : 690iter [00:28, 28.07iter/s]Best score: 0.3266: : 690iter [00:28, 28.07iter/s]Best score: 0.3266: : 691iter [00:28, 28.07iter/s]Best score: 0.3266: : 692iter [00:28, 28.07iter/s]Best score: 0.3266: : 693iter [00:28, 28.10iter/s]Best score: 0.3266: : 693iter [00:28, 28.10iter/s]Best score: 0.3266: : 694iter [00:28, 28.10iter/s]Best score: 0.3266: : 695iter [00:28, 28.10iter/s]Best score: 0.3266: : 696iter [00:28, 28.54iter/s]Best score: 0.3266: : 696iter [00:28, 28.54iter/s]Best score: 0.3266: : 697iter [00:28, 28.54iter/s]Best score: 0.3266: : 698iter [00:28, 28.54iter/s]
[ITER 700] Best: 0.3145
[PARAMS] Current best parameters:
  fx: 619.5075
  fy: 620.5301
  px: 992.9385
  py: 763.8986
  k1: -0.03408606
  k2: -0.08750938
  k3: 0.06479053
  k4: -0.01474973
  p1: 0.00805349
  p2: 0.02483412
  p3: -0.01972367
  p4: -0.00447949
  s1: -0.0075
  s2: 0.0042
  s3: 0.0140
  s4: 0.0042
  tilt_x: -0.0688
  tilt_y: -0.0119
  scale: 2.8890
  rotation: -0.2776
Best score: 0.3145: : 699iter [00:28, 28.54iter/s]Best score: 0.3145: : 700iter [00:28, 28.97iter/s]Best score: 0.3145: : 700iter [00:29, 28.97iter/s]Best score: 0.3145: : 701iter [00:29, 28.97iter/s]Best score: 0.3145: : 702iter [00:29, 28.97iter/s]Best score: 0.3145: : 703iter [00:29, 23.66iter/s]Best score: 0.3145: : 703iter [00:29, 23.66iter/s]Best score: 0.3145: : 704iter [00:29, 23.66iter/s]Best score: 0.3145: : 705iter [00:29, 23.66iter/s]Best score: 0.3145: : 706iter [00:29, 24.79iter/s]Best score: 0.3145: : 706iter [00:29, 24.79iter/s]Best score: 0.3145: : 707iter [00:29, 24.79iter/s]Best score: 0.3145: : 708iter [00:29, 24.79iter/s]Best score: 0.3145: : 709iter [00:29, 24.79iter/s]Best score: 0.3145: : 710iter [00:29, 26.19iter/s]Best score: 0.3145: : 710iter [00:29, 26.19iter/s]Best score: 0.3145: : 711iter [00:29, 26.19iter/s]Best score: 0.3145: : 712iter [00:29, 26.19iter/s]Best score: 0.3145: : 713iter [00:29, 26.97iter/s]Best score: 0.3145: : 713iter [00:29, 26.97iter/s]Best score: 0.3145: : 714iter [00:29, 26.97iter/s]Best score: 0.3145: : 715iter [00:29, 26.97iter/s]Best score: 0.3145: : 716iter [00:29, 27.72iter/s]Best score: 0.3145: : 716iter [00:29, 27.72iter/s]Best score: 0.3145: : 717iter [00:29, 27.72iter/s]Best score: 0.3145: : 718iter [00:29, 27.72iter/s]Best score: 0.3145: : 719iter [00:29, 28.04iter/s]Best score: 0.3145: : 719iter [00:29, 28.04iter/s]Best score: 0.3145: : 720iter [00:29, 28.04iter/s]Best score: 0.3145: : 721iter [00:29, 28.04iter/s]Best score: 0.3145: : 722iter [00:29, 28.25iter/s]Best score: 0.3145: : 722iter [00:29, 28.25iter/s]Best score: 0.3145: : 723iter [00:29, 28.25iter/s]Best score: 0.3145: : 724iter [00:29, 28.25iter/s]Best score: 0.3145: : 725iter [00:29, 28.43iter/s]Best score: 0.3145: : 725iter [00:29, 28.43iter/s]Best score: 0.3145: : 726iter [00:30, 28.43iter/s]Best score: 0.3145: : 727iter [00:30, 28.43iter/s]Best score: 0.3145: : 728iter [00:30, 27.80iter/s]Best score: 0.3145: : 728iter [00:30, 27.80iter/s]Best score: 0.3095: : 729iter [00:30, 27.80iter/s]Best score: 0.3095: : 730iter [00:30, 27.80iter/s]Best score: 0.3095: : 731iter [00:30, 27.28iter/s]Best score: 0.3095: : 731iter [00:30, 27.28iter/s]Best score: 0.3095: : 732iter [00:30, 27.28iter/s]Best score: 0.3095: : 733iter [00:30, 27.28iter/s]Best score: 0.3095: : 734iter [00:30, 27.93iter/s]Best score: 0.3095: : 734iter [00:30, 27.93iter/s]Best score: 0.3095: : 735iter [00:30, 27.93iter/s]Best score: 0.3095: : 736iter [00:30, 27.93iter/s]Best score: 0.3095: : 737iter [00:30, 28.07iter/s]Best score: 0.3095: : 737iter [00:30, 28.07iter/s]Best score: 0.3095: : 738iter [00:30, 28.07iter/s]Best score: 0.3048: : 739iter [00:30, 28.07iter/s]Best score: 0.3048: : 740iter [00:30, 28.14iter/s]Best score: 0.3048: : 740iter [00:30, 28.14iter/s]Best score: 0.3048: : 741iter [00:30, 28.14iter/s]Best score: 0.3048: : 742iter [00:30, 28.14iter/s]Best score: 0.3048: : 743iter [00:30, 28.53iter/s]Best score: 0.3048: : 743iter [00:30, 28.53iter/s]Best score: 0.3048: : 744iter [00:30, 28.53iter/s]Best score: 0.3048: : 745iter [00:30, 28.53iter/s]Best score: 0.3048: : 746iter [00:30, 28.55iter/s]Best score: 0.3048: : 746iter [00:30, 28.55iter/s]Best score: 0.3048: : 747iter [00:30, 28.55iter/s]Best score: 0.3048: : 748iter [00:30, 28.55iter/s]Best score: 0.3048: : 749iter [00:30, 28.77iter/s]
[ITER 750] Best: 0.3048
[PARAMS] Current best parameters:
  fx: 621.3153
  fy: 622.1343
  px: 993.9838
  py: 763.4838
  k1: -0.03202559
  k2: -0.09362309
  k3: 0.06876946
  k4: -0.01561420
  p1: 0.00729803
  p2: 0.02447339
  p3: -0.02279121
  p4: -0.00474265
  s1: -0.0036
  s2: 0.0051
  s3: 0.0182
  s4: 0.0041
  tilt_x: -0.0699
  tilt_y: -0.0186
  scale: 2.8841
  rotation: -0.2695
Best score: 0.3048: : 749iter [00:30, 28.77iter/s]Best score: 0.3048: : 750iter [00:30, 28.77iter/s]Best score: 0.3048: : 751iter [00:30, 28.77iter/s]Best score: 0.3048: : 752iter [00:30, 22.88iter/s]Best score: 0.3048: : 752iter [00:31, 22.88iter/s]Best score: 0.3048: : 753iter [00:31, 22.88iter/s]Best score: 0.3048: : 754iter [00:31, 22.88iter/s]Best score: 0.3048: : 755iter [00:31, 24.47iter/s]Best score: 0.3048: : 755iter [00:31, 24.47iter/s]Best score: 0.3048: : 756iter [00:31, 24.47iter/s]Best score: 0.3048: : 757iter [00:31, 24.47iter/s]Best score: 0.3048: : 758iter [00:31, 24.47iter/s]Best score: 0.3048: : 759iter [00:31, 26.33iter/s]Best score: 0.3048: : 759iter [00:31, 26.33iter/s]Best score: 0.3048: : 760iter [00:31, 26.33iter/s]Best score: 0.3048: : 761iter [00:31, 26.33iter/s]Best score: 0.3048: : 762iter [00:31, 27.02iter/s]Best score: 0.3048: : 762iter [00:31, 27.02iter/s]Best score: 0.3048: : 763iter [00:31, 27.02iter/s]Best score: 0.3048: : 764iter [00:31, 27.02iter/s]Best score: 0.3048: : 765iter [00:31, 27.02iter/s]Best score: 0.3048: : 766iter [00:31, 28.18iter/s]Best score: 0.3048: : 766iter [00:31, 28.18iter/s]Best score: 0.3048: : 767iter [00:31, 28.18iter/s]Best score: 0.3048: : 768iter [00:31, 28.18iter/s]Best score: 0.3024: : 769iter [00:31, 28.18iter/s]Best score: 0.3024: : 770iter [00:31, 29.00iter/s]Best score: 0.3024: : 770iter [00:31, 29.00iter/s]Best score: 0.3024: : 771iter [00:31, 29.00iter/s]Best score: 0.3024: : 772iter [00:31, 29.00iter/s]Best score: 0.3024: : 773iter [00:31, 29.00iter/s]Best score: 0.3024: : 774iter [00:31, 29.82iter/s]Best score: 0.3024: : 774iter [00:31, 29.82iter/s]Best score: 0.3024: : 775iter [00:31, 29.82iter/s]Best score: 0.3024: : 776iter [00:31, 29.82iter/s]Best score: 0.3024: : 777iter [00:31, 29.82iter/s]Best score: 0.3024: : 778iter [00:31, 30.07iter/s]Best score: 0.3024: : 778iter [00:31, 30.07iter/s]Best score: 0.3004: : 779iter [00:31, 30.07iter/s]Best score: 0.3004: : 780iter [00:31, 30.07iter/s]Best score: 0.3004: : 781iter [00:31, 30.07iter/s]Best score: 0.3004: : 782iter [00:31, 30.54iter/s]Best score: 0.3004: : 782iter [00:31, 30.54iter/s]Best score: 0.3004: : 783iter [00:32, 30.54iter/s]Best score: 0.3004: : 784iter [00:32, 30.54iter/s]Best score: 0.3004: : 785iter [00:32, 30.54iter/s]Best score: 0.3004: : 786iter [00:32, 30.38iter/s]Best score: 0.3004: : 786iter [00:32, 30.38iter/s]Best score: 0.3004: : 787iter [00:32, 30.38iter/s]Best score: 0.3004: : 788iter [00:32, 30.38iter/s]Best score: 0.3004: : 789iter [00:32, 30.38iter/s]Best score: 0.3004: : 790iter [00:32, 30.59iter/s]Best score: 0.3004: : 790iter [00:32, 30.59iter/s]Best score: 0.3004: : 791iter [00:32, 30.59iter/s]Best score: 0.3004: : 792iter [00:32, 30.59iter/s]Best score: 0.3004: : 793iter [00:32, 30.59iter/s]Best score: 0.3004: : 794iter [00:32, 25.62iter/s]Best score: 0.3004: : 794iter [00:32, 25.62iter/s]Best score: 0.3004: : 795iter [00:32, 25.62iter/s]Best score: 0.3004: : 796iter [00:32, 25.62iter/s]Best score: 0.3004: : 797iter [00:32, 25.67iter/s]Best score: 0.3004: : 797iter [00:32, 25.67iter/s]Best score: 0.3004: : 798iter [00:32, 25.67iter/s]
[ITER 800] Best: 0.2952
[PARAMS] Current best parameters:
  fx: 616.7208
  fy: 617.4826
  px: 993.4312
  py: 763.2232
  k1: -0.03132972
  k2: -0.08599750
  k3: 0.06265204
  k4: -0.01412893
  p1: 0.00892596
  p2: 0.02199429
  p3: -0.02389914
  p4: -0.00559665
  s1: -0.0018
  s2: 0.0065
  s3: 0.0171
  s4: 0.0054
  tilt_x: -0.0744
  tilt_y: -0.0201
  scale: 2.8903
  rotation: -0.2533
Best score: 0.2952: : 799iter [00:32, 25.67iter/s]Best score: 0.2952: : 800iter [00:32, 25.36iter/s]Best score: 0.2952: : 800iter [00:32, 25.36iter/s]Best score: 0.2952: : 801iter [00:32, 25.36iter/s]Best score: 0.2952: : 802iter [00:32, 25.36iter/s]Best score: 0.2952: : 803iter [00:32, 20.73iter/s]Best score: 0.2952: : 803iter [00:32, 20.73iter/s]Best score: 0.2952: : 804iter [00:32, 20.73iter/s]Best score: 0.2952: : 805iter [00:32, 20.73iter/s]Best score: 0.2952: : 806iter [00:32, 22.31iter/s]Best score: 0.2952: : 806iter [00:33, 22.31iter/s]Best score: 0.2952: : 807iter [00:33, 22.31iter/s]Best score: 0.2952: : 808iter [00:33, 22.31iter/s]Best score: 0.2952: : 809iter [00:33, 23.48iter/s]Best score: 0.2952: : 809iter [00:33, 23.48iter/s]Best score: 0.2952: : 810iter [00:33, 23.48iter/s]Best score: 0.2952: : 811iter [00:33, 23.48iter/s]Best score: 0.2952: : 812iter [00:33, 24.58iter/s]Best score: 0.2952: : 812iter [00:33, 24.58iter/s]Best score: 0.2952: : 813iter [00:33, 24.58iter/s]Best score: 0.2952: : 814iter [00:33, 24.58iter/s]Best score: 0.2952: : 815iter [00:33, 25.11iter/s]Best score: 0.2952: : 815iter [00:33, 25.11iter/s]Best score: 0.2952: : 816iter [00:33, 25.11iter/s]Best score: 0.2952: : 817iter [00:33, 25.11iter/s]Best score: 0.2952: : 818iter [00:33, 25.31iter/s]Best score: 0.2952: : 818iter [00:33, 25.31iter/s]Best score: 0.2952: : 819iter [00:33, 25.31iter/s]Best score: 0.2952: : 820iter [00:33, 25.31iter/s]Best score: 0.2952: : 821iter [00:33, 25.61iter/s]Best score: 0.2952: : 821iter [00:33, 25.61iter/s]Best score: 0.2952: : 822iter [00:33, 25.61iter/s]Best score: 0.2952: : 823iter [00:33, 25.61iter/s]Best score: 0.2952: : 824iter [00:33, 26.08iter/s]Best score: 0.2952: : 824iter [00:33, 26.08iter/s]Best score: 0.2952: : 825iter [00:33, 26.08iter/s]Best score: 0.2952: : 826iter [00:33, 26.08iter/s]Best score: 0.2952: : 827iter [00:33, 26.39iter/s]Best score: 0.2952: : 827iter [00:33, 26.39iter/s]Best score: 0.2952: : 828iter [00:33, 26.39iter/s]Best score: 0.2952: : 829iter [00:33, 26.39iter/s]Best score: 0.2952: : 830iter [00:33, 26.30iter/s]Best score: 0.2952: : 830iter [00:33, 26.30iter/s]Best score: 0.2952: : 831iter [00:33, 26.30iter/s]Best score: 0.2952: : 832iter [00:34, 26.30iter/s]Best score: 0.2952: : 833iter [00:34, 25.95iter/s]Best score: 0.2952: : 833iter [00:34, 25.95iter/s]Best score: 0.2952: : 834iter [00:34, 25.95iter/s]Best score: 0.2952: : 835iter [00:34, 25.95iter/s]Best score: 0.2952: : 836iter [00:34, 26.17iter/s]Best score: 0.2952: : 836iter [00:34, 26.17iter/s]Best score: 0.2952: : 837iter [00:34, 26.17iter/s]Best score: 0.2952: : 838iter [00:34, 26.17iter/s]Best score: 0.2952: : 839iter [00:34, 26.38iter/s]Best score: 0.2951: : 839iter [00:34, 26.38iter/s]Best score: 0.2951: : 840iter [00:34, 26.38iter/s]Best score: 0.2951: : 841iter [00:34, 26.38iter/s]Best score: 0.2951: : 842iter [00:34, 26.39iter/s]Best score: 0.2951: : 842iter [00:34, 26.39iter/s]Best score: 0.2951: : 843iter [00:34, 26.39iter/s]Best score: 0.2951: : 844iter [00:34, 26.39iter/s]Best score: 0.2951: : 845iter [00:34, 26.11iter/s]Best score: 0.2951: : 845iter [00:34, 26.11iter/s]Best score: 0.2951: : 846iter [00:34, 26.11iter/s]Best score: 0.2951: : 847iter [00:34, 26.11iter/s]Best score: 0.2951: : 848iter [00:34, 25.81iter/s]Best score: 0.2951: : 848iter [00:34, 25.81iter/s]
[ITER 850] Best: 0.2940
[PARAMS] Current best parameters:
  fx: 620.7947
  fy: 621.6158
  px: 993.4414
  py: 763.2658
  k1: -0.03316224
  k2: -0.09062156
  k3: 0.06685559
  k4: -0.01521884
  p1: 0.00851953
  p2: 0.02124363
  p3: -0.02301491
  p4: -0.00451115
  s1: -0.0022
  s2: 0.0056
  s3: 0.0169
  s4: 0.0041
  tilt_x: -0.0738
  tilt_y: -0.0224
  scale: 2.8868
  rotation: -0.2637
Best score: 0.2940: : 849iter [00:34, 25.81iter/s]Best score: 0.2940: : 850iter [00:34, 25.81iter/s]Best score: 0.2940: : 851iter [00:34, 21.45iter/s]Best score: 0.2940: : 851iter [00:34, 21.45iter/s]Best score: 0.2940: : 852iter [00:34, 21.45iter/s]Best score: 0.2940: : 853iter [00:34, 21.45iter/s]Best score: 0.2940: : 854iter [00:34, 23.26iter/s]Best score: 0.2940: : 854iter [00:34, 23.26iter/s]Best score: 0.2940: : 855iter [00:34, 23.26iter/s]Best score: 0.2940: : 856iter [00:35, 23.26iter/s]Best score: 0.2940: : 857iter [00:35, 24.03iter/s]Best score: 0.2940: : 857iter [00:35, 24.03iter/s]Best score: 0.2940: : 858iter [00:35, 24.03iter/s]Best score: 0.2938: : 859iter [00:35, 24.03iter/s]Best score: 0.2938: : 860iter [00:35, 24.70iter/s]Best score: 0.2938: : 860iter [00:35, 24.70iter/s]Best score: 0.2938: : 861iter [00:35, 24.70iter/s]Best score: 0.2938: : 862iter [00:35, 24.70iter/s]Best score: 0.2938: : 863iter [00:35, 25.68iter/s]Best score: 0.2938: : 863iter [00:35, 25.68iter/s]Best score: 0.2938: : 864iter [00:35, 25.68iter/s]Best score: 0.2938: : 865iter [00:35, 25.68iter/s]Best score: 0.2938: : 866iter [00:35, 26.23iter/s]Best score: 0.2938: : 866iter [00:35, 26.23iter/s]Best score: 0.2938: : 867iter [00:35, 26.23iter/s]Best score: 0.2938: : 868iter [00:35, 26.23iter/s]Best score: 0.2938: : 869iter [00:35, 27.17iter/s]Best score: 0.2934: : 869iter [00:35, 27.17iter/s]Best score: 0.2934: : 870iter [00:35, 27.17iter/s]Best score: 0.2934: : 871iter [00:35, 27.17iter/s]Best score: 0.2934: : 872iter [00:35, 27.38iter/s]Best score: 0.2934: : 872iter [00:35, 27.38iter/s]Best score: 0.2934: : 873iter [00:35, 27.38iter/s]Best score: 0.2934: : 874iter [00:35, 27.38iter/s]Best score: 0.2934: : 875iter [00:35, 26.89iter/s]Best score: 0.2934: : 875iter [00:35, 26.89iter/s]Best score: 0.2934: : 876iter [00:35, 26.89iter/s]Best score: 0.2934: : 877iter [00:35, 26.89iter/s]Best score: 0.2934: : 878iter [00:35, 27.03iter/s]Best score: 0.2934: : 878iter [00:35, 27.03iter/s]Best score: 0.2934: : 879iter [00:35, 27.03iter/s]Best score: 0.2934: : 880iter [00:35, 27.03iter/s]Best score: 0.2934: : 881iter [00:35, 27.70iter/s]Best score: 0.2934: : 881iter [00:35, 27.70iter/s]Best score: 0.2934: : 882iter [00:35, 27.70iter/s]Best score: 0.2934: : 883iter [00:35, 27.70iter/s]Best score: 0.2934: : 884iter [00:35, 27.88iter/s]Best score: 0.2934: : 884iter [00:36, 27.88iter/s]Best score: 0.2934: : 885iter [00:36, 27.88iter/s]Best score: 0.2934: : 886iter [00:36, 27.88iter/s]Best score: 0.2934: : 887iter [00:36, 27.98iter/s]Best score: 0.2934: : 887iter [00:36, 27.98iter/s]Best score: 0.2934: : 888iter [00:36, 27.98iter/s]Best score: 0.2923: : 889iter [00:36, 27.98iter/s]Best score: 0.2923: : 890iter [00:36, 27.65iter/s]Best score: 0.2923: : 890iter [00:36, 27.65iter/s]Best score: 0.2923: : 891iter [00:36, 27.65iter/s]Best score: 0.2923: : 892iter [00:36, 27.65iter/s]Best score: 0.2923: : 893iter [00:36, 27.62iter/s]Best score: 0.2923: : 893iter [00:36, 27.62iter/s]Best score: 0.2923: : 894iter [00:36, 27.62iter/s]Best score: 0.2923: : 895iter [00:36, 27.62iter/s]Best score: 0.2923: : 896iter [00:36, 27.74iter/s]Best score: 0.2923: : 896iter [00:36, 27.74iter/s]Best score: 0.2923: : 897iter [00:36, 27.74iter/s]Best score: 0.2923: : 898iter [00:36, 27.74iter/s]Best score: 0.2923: : 899iter [00:36, 27.66iter/s]
[ITER 900] Best: 0.2920
[PARAMS] Current best parameters:
  fx: 616.7702
  fy: 617.5609
  px: 993.2695
  py: 763.0340
  k1: -0.03167883
  k2: -0.08620253
  k3: 0.06324714
  k4: -0.01435561
  p1: 0.00866890
  p2: 0.02131034
  p3: -0.02415781
  p4: -0.00570478
  s1: -0.0005
  s2: 0.0063
  s3: 0.0174
  s4: 0.0056
  tilt_x: -0.0752
  tilt_y: -0.0206
  scale: 2.8914
  rotation: -0.2541
Best score: 0.2920: : 899iter [00:36, 27.66iter/s]Best score: 0.2920: : 900iter [00:36, 27.66iter/s]Best score: 0.2920: : 901iter [00:36, 27.66iter/s]Best score: 0.2920: : 902iter [00:36, 20.95iter/s]Best score: 0.2920: : 902iter [00:36, 20.95iter/s]Best score: 0.2920: : 903iter [00:36, 20.95iter/s]Best score: 0.2920: : 904iter [00:36, 20.95iter/s]Best score: 0.2920: : 905iter [00:36, 23.00iter/s]Best score: 0.2920: : 905iter [00:36, 23.00iter/s]Best score: 0.2920: : 906iter [00:36, 23.00iter/s]Best score: 0.2920: : 907iter [00:36, 23.00iter/s]Best score: 0.2920: : 908iter [00:36, 24.14iter/s]Best score: 0.2920: : 908iter [00:36, 24.14iter/s]Best score: 0.2920: : 909iter [00:37, 24.14iter/s]Best score: 0.2920: : 910iter [00:37, 24.14iter/s]Best score: 0.2920: : 911iter [00:37, 24.43iter/s]Best score: 0.2920: : 911iter [00:37, 24.43iter/s]Best score: 0.2920: : 912iter [00:37, 24.43iter/s]Best score: 0.2920: : 913iter [00:37, 24.43iter/s]Best score: 0.2920: : 914iter [00:37, 25.08iter/s]Best score: 0.2920: : 914iter [00:37, 25.08iter/s]Best score: 0.2920: : 915iter [00:37, 25.08iter/s]Best score: 0.2920: : 916iter [00:37, 25.08iter/s]Best score: 0.2920: : 917iter [00:37, 25.45iter/s]Best score: 0.2920: : 917iter [00:37, 25.45iter/s]Best score: 0.2920: : 918iter [00:37, 25.45iter/s]Best score: 0.2919: : 919iter [00:37, 25.45iter/s]Best score: 0.2919: : 920iter [00:37, 25.24iter/s]Best score: 0.2919: : 920iter [00:37, 25.24iter/s]Best score: 0.2919: : 921iter [00:37, 25.24iter/s]Best score: 0.2919: : 922iter [00:37, 25.24iter/s]Best score: 0.2919: : 923iter [00:37, 25.87iter/s]Best score: 0.2919: : 923iter [00:37, 25.87iter/s]Best score: 0.2919: : 924iter [00:37, 25.87iter/s]Best score: 0.2919: : 925iter [00:37, 25.87iter/s]Best score: 0.2919: : 926iter [00:37, 26.80iter/s]Best score: 0.2919: : 926iter [00:37, 26.80iter/s]Best score: 0.2919: : 927iter [00:37, 26.80iter/s]Best score: 0.2919: : 928iter [00:37, 26.80iter/s]Best score: 0.2919: : 929iter [00:37, 26.94iter/s]Best score: 0.2917: : 929iter [00:37, 26.94iter/s]Best score: 0.2917: : 930iter [00:37, 26.94iter/s]Best score: 0.2917: : 931iter [00:37, 26.94iter/s]Best score: 0.2917: : 932iter [00:37, 26.94iter/s]Best score: 0.2917: : 933iter [00:37, 28.22iter/s]Best score: 0.2917: : 933iter [00:37, 28.22iter/s]Best score: 0.2917: : 934iter [00:37, 28.22iter/s]Best score: 0.2917: : 935iter [00:37, 28.22iter/s]Best score: 0.2917: : 936iter [00:37, 28.36iter/s]Best score: 0.2917: : 936iter [00:38, 28.36iter/s]Best score: 0.2917: : 937iter [00:38, 28.36iter/s]Best score: 0.2917: : 938iter [00:38, 28.36iter/s]Best score: 0.2917: : 939iter [00:38, 28.24iter/s]Best score: 0.2917: : 939iter [00:38, 28.24iter/s]Best score: 0.2917: : 940iter [00:38, 28.24iter/s]Best score: 0.2917: : 941iter [00:38, 28.24iter/s]Best score: 0.2917: : 942iter [00:38, 28.36iter/s]Best score: 0.2917: : 942iter [00:38, 28.36iter/s]Best score: 0.2917: : 943iter [00:38, 28.36iter/s]Best score: 0.2917: : 944iter [00:38, 28.36iter/s]Best score: 0.2917: : 945iter [00:38, 27.99iter/s]Best score: 0.2917: : 945iter [00:38, 27.99iter/s]Best score: 0.2917: : 946iter [00:38, 27.99iter/s]Best score: 0.2917: : 947iter [00:38, 27.99iter/s]Best score: 0.2917: : 948iter [00:38, 28.04iter/s]Best score: 0.2917: : 948iter [00:38, 28.04iter/s]
[ITER 950] Best: 0.2913
[PARAMS] Current best parameters:
  fx: 616.9132
  fy: 617.7017
  px: 993.3833
  py: 763.3066
  k1: -0.03222763
  k2: -0.08545451
  k3: 0.06269553
  k4: -0.01420634
  p1: 0.00883408
  p2: 0.02142232
  p3: -0.02301450
  p4: -0.00553499
  s1: -0.0017
  s2: 0.0062
  s3: 0.0162
  s4: 0.0054
  tilt_x: -0.0737
  tilt_y: -0.0211
  scale: 2.8920
  rotation: -0.2564
Best score: 0.2913: : 949iter [00:38, 28.04iter/s]Best score: 0.2913: : 950iter [00:38, 28.04iter/s]Best score: 0.2913: : 951iter [00:38, 22.82iter/s]Best score: 0.2913: : 951iter [00:38, 22.82iter/s]Best score: 0.2913: : 952iter [00:38, 22.82iter/s]Best score: 0.2913: : 953iter [00:38, 22.82iter/s]Best score: 0.2913: : 954iter [00:38, 24.32iter/s]Best score: 0.2913: : 954iter [00:38, 24.32iter/s]Best score: 0.2913: : 955iter [00:38, 24.32iter/s]Best score: 0.2913: : 956iter [00:38, 24.32iter/s]Best score: 0.2913: : 957iter [00:38, 24.96iter/s]Best score: 0.2913: : 957iter [00:38, 24.96iter/s]Best score: 0.2913: : 958iter [00:38, 24.96iter/s]Best score: 0.2908: : 959iter [00:38, 24.96iter/s]Best score: 0.2908: : 960iter [00:38, 24.96iter/s]Best score: 0.2908: : 960iter [00:38, 24.96iter/s]Best score: 0.2908: : 961iter [00:38, 24.96iter/s]Best score: 0.2908: : 962iter [00:39, 24.96iter/s]Best score: 0.2908: : 963iter [00:39, 25.89iter/s]Best score: 0.2908: : 963iter [00:39, 25.89iter/s]Best score: 0.2908: : 964iter [00:39, 25.89iter/s]Best score: 0.2908: : 965iter [00:39, 25.89iter/s]Best score: 0.2908: : 966iter [00:39, 26.30iter/s]Best score: 0.2908: : 966iter [00:39, 26.30iter/s]Best score: 0.2908: : 967iter [00:39, 26.30iter/s]Best score: 0.2908: : 968iter [00:39, 26.30iter/s]Best score: 0.2908: : 969iter [00:39, 26.97iter/s]Best score: 0.2907: : 969iter [00:39, 26.97iter/s]Best score: 0.2907: : 970iter [00:39, 26.97iter/s]Best score: 0.2907: : 971iter [00:39, 26.97iter/s]Best score: 0.2907: : 972iter [00:39, 26.97iter/s]Best score: 0.2907: : 973iter [00:39, 28.22iter/s]Best score: 0.2907: : 973iter [00:39, 28.22iter/s]Best score: 0.2907: : 974iter [00:39, 28.22iter/s]Best score: 0.2907: : 975iter [00:39, 28.22iter/s]Best score: 0.2907: : 976iter [00:39, 28.42iter/s]Best score: 0.2907: : 976iter [00:39, 28.42iter/s]Best score: 0.2907: : 977iter [00:39, 28.42iter/s]Best score: 0.2907: : 978iter [00:39, 28.42iter/s]Best score: 0.2907: : 979iter [00:39, 28.29iter/s]Best score: 0.2907: : 979iter [00:39, 28.29iter/s]Best score: 0.2907: : 980iter [00:39, 28.29iter/s]Best score: 0.2907: : 981iter [00:39, 28.29iter/s]Best score: 0.2907: : 982iter [00:39, 28.63iter/s]Best score: 0.2907: : 982iter [00:39, 28.63iter/s]Best score: 0.2907: : 983iter [00:39, 28.63iter/s]Best score: 0.2907: : 984iter [00:39, 28.63iter/s]Best score: 0.2907: : 985iter [00:39, 28.93iter/s]Best score: 0.2907: : 985iter [00:39, 28.93iter/s]Best score: 0.2907: : 986iter [00:39, 28.93iter/s]Best score: 0.2907: : 987iter [00:39, 28.93iter/s]Best score: 0.2907: : 988iter [00:39, 29.14iter/s]Best score: 0.2907: : 988iter [00:39, 29.14iter/s]Best score: 0.2905: : 989iter [00:39, 29.14iter/s]Best score: 0.2905: : 990iter [00:39, 29.14iter/s]Best score: 0.2905: : 991iter [00:40, 29.14iter/s]Best score: 0.2905: : 992iter [00:40, 29.03iter/s]Best score: 0.2905: : 992iter [00:40, 29.03iter/s]Best score: 0.2905: : 993iter [00:40, 29.03iter/s]Best score: 0.2905: : 994iter [00:40, 29.03iter/s]Best score: 0.2905: : 995iter [00:40, 28.58iter/s]Best score: 0.2905: : 995iter [00:40, 28.58iter/s]Best score: 0.2905: : 996iter [00:40, 28.58iter/s]Best score: 0.2905: : 997iter [00:40, 28.58iter/s]Best score: 0.2905: : 998iter [00:40, 28.88iter/s]Best score: 0.2905: : 998iter [00:40, 28.88iter/s]
[ITER 1000] Best: 0.2898
[PARAMS] Current best parameters:
  fx: 613.1878
  fy: 613.9723
  px: 992.9370
  py: 763.1444
  k1: -0.03133425
  k2: -0.08047864
  k3: 0.05884098
  k4: -0.01331810
  p1: 0.00897980
  p2: 0.02044868
  p3: -0.02288672
  p4: -0.00621256
  s1: -0.0007
  s2: 0.0064
  s3: 0.0159
  s4: 0.0060
  tilt_x: -0.0746
  tilt_y: -0.0202
  scale: 2.8967
  rotation: -0.2596
Best score: 0.2898: : 999iter [00:40, 28.88iter/s]Best score: 0.2898: : 1000iter [00:40, 28.88iter/s]Best score: 0.2898: : 1001iter [00:40, 18.84iter/s]Best score: 0.2898: : 1001iter [00:40, 18.84iter/s]Best score: 0.2898: : 1002iter [00:40, 18.84iter/s]Best score: 0.2898: : 1003iter [00:40, 18.84iter/s]Best score: 0.2898: : 1004iter [00:40, 20.67iter/s]Best score: 0.2898: : 1004iter [00:40, 20.67iter/s]Best score: 0.2898: : 1005iter [00:40, 20.67iter/s]Best score: 0.2898: : 1006iter [00:40, 20.67iter/s]Best score: 0.2898: : 1007iter [00:40, 21.98iter/s]Best score: 0.2898: : 1007iter [00:40, 21.98iter/s]Best score: 0.2898: : 1008iter [00:40, 21.98iter/s]Best score: 0.2897: : 1009iter [00:40, 21.98iter/s]Best score: 0.2897: : 1010iter [00:40, 22.97iter/s]Best score: 0.2897: : 1010iter [00:40, 22.97iter/s]Best score: 0.2897: : 1011iter [00:40, 22.97iter/s]Best score: 0.2897: : 1012iter [00:41, 22.97iter/s]Best score: 0.2897: : 1013iter [00:41, 23.65iter/s]Best score: 0.2897: : 1013iter [00:41, 23.65iter/s]Best score: 0.2897: : 1014iter [00:41, 23.65iter/s]Best score: 0.2897: : 1015iter [00:41, 23.65iter/s]Best score: 0.2897: : 1016iter [00:41, 24.01iter/s]Best score: 0.2897: : 1016iter [00:41, 24.01iter/s]Best score: 0.2897: : 1017iter [00:41, 24.01iter/s]Best score: 0.2897: : 1018iter [00:41, 24.01iter/s]Best score: 0.2897: : 1019iter [00:41, 24.27iter/s]Best score: 0.2893: : 1019iter [00:41, 24.27iter/s]Best score: 0.2893: : 1020iter [00:41, 24.27iter/s]Best score: 0.2893: : 1021iter [00:41, 24.27iter/s]Best score: 0.2893: : 1022iter [00:41, 25.44iter/s]Best score: 0.2893: : 1022iter [00:41, 25.44iter/s]Best score: 0.2893: : 1023iter [00:41, 25.44iter/s]Best score: 0.2893: : 1024iter [00:41, 25.44iter/s]Best score: 0.2893: : 1025iter [00:41, 25.87iter/s]Best score: 0.2893: : 1025iter [00:41, 25.87iter/s]Best score: 0.2893: : 1026iter [00:41, 25.87iter/s]Best score: 0.2893: : 1027iter [00:41, 25.87iter/s]Best score: 0.2893: : 1028iter [00:41, 26.58iter/s]Best score: 0.2893: : 1028iter [00:41, 26.58iter/s]Best score: 0.2893: : 1029iter [00:41, 26.58iter/s]Best score: 0.2893: : 1030iter [00:41, 26.58iter/s]Best score: 0.2893: : 1031iter [00:41, 26.79iter/s]Best score: 0.2893: : 1031iter [00:41, 26.79iter/s]Best score: 0.2893: : 1032iter [00:41, 26.79iter/s]Best score: 0.2893: : 1033iter [00:41, 26.79iter/s]Best score: 0.2893: : 1034iter [00:41, 26.60iter/s]Best score: 0.2893: : 1034iter [00:41, 26.60iter/s]Best score: 0.2893: : 1035iter [00:41, 26.60iter/s]Best score: 0.2893: : 1036iter [00:41, 26.60iter/s]Best score: 0.2893: : 1037iter [00:41, 26.45iter/s]Best score: 0.2893: : 1037iter [00:41, 26.45iter/s]Best score: 0.2893: : 1038iter [00:41, 26.45iter/s]Best score: 0.2893: : 1039iter [00:42, 26.45iter/s]Best score: 0.2893: : 1040iter [00:42, 26.26iter/s]Best score: 0.2893: : 1040iter [00:42, 26.26iter/s]Best score: 0.2893: : 1041iter [00:42, 26.26iter/s]Best score: 0.2893: : 1042iter [00:42, 26.26iter/s]Best score: 0.2893: : 1043iter [00:42, 26.77iter/s]Best score: 0.2893: : 1043iter [00:42, 26.77iter/s]Best score: 0.2893: : 1044iter [00:42, 26.77iter/s]Best score: 0.2893: : 1045iter [00:42, 26.77iter/s]Best score: 0.2893: : 1046iter [00:42, 26.88iter/s]Best score: 0.2893: : 1046iter [00:42, 26.88iter/s]Best score: 0.2893: : 1047iter [00:42, 26.88iter/s]Best score: 0.2893: : 1048iter [00:42, 26.88iter/s]Best score: 0.2893: : 1049iter [00:42, 26.96iter/s]
[ITER 1050] Best: 0.2889Best score: 0.2889: : 1049iter [00:42, 26.96iter/s]
[PARAMS] Current best parameters:
  fx: 610.7315
  fy: 611.4739
  px: 992.2946
  py: 762.9403
  k1: -0.03163849
  k2: -0.07610367
  k3: 0.05600889
  k4: -0.01276067
  p1: 0.00852325
  p2: 0.01832799
  p3: -0.02211391
  p4: -0.00675607
  s1: -0.0004
  s2: 0.0071
  s3: 0.0152
  s4: 0.0066
  tilt_x: -0.0746
  tilt_y: -0.0206
  scale: 2.9007
  rotation: -0.2586
Best score: 0.2889: : 1050iter [00:42, 26.96iter/s]Best score: 0.2889: : 1051iter [00:42, 26.96iter/s]Best score: 0.2889: : 1052iter [00:42, 21.82iter/s]Best score: 0.2889: : 1052iter [00:42, 21.82iter/s]Best score: 0.2889: : 1053iter [00:42, 21.82iter/s]Best score: 0.2889: : 1054iter [00:42, 21.82iter/s]Best score: 0.2889: : 1055iter [00:42, 23.57iter/s]Best score: 0.2889: : 1055iter [00:42, 23.57iter/s]Best score: 0.2889: : 1056iter [00:42, 23.57iter/s]Best score: 0.2889: : 1057iter [00:42, 23.57iter/s]Best score: 0.2889: : 1058iter [00:42, 24.83iter/s]Best score: 0.2889: : 1058iter [00:42, 24.83iter/s]Best score: 0.2882: : 1059iter [00:42, 24.83iter/s]Best score: 0.2882: : 1060iter [00:42, 24.83iter/s]Best score: 0.2882: : 1061iter [00:42, 26.07iter/s]Best score: 0.2882: : 1061iter [00:42, 26.07iter/s]Best score: 0.2882: : 1062iter [00:42, 26.07iter/s]Best score: 0.2882: : 1063iter [00:42, 26.07iter/s]Best score: 0.2882: : 1064iter [00:42, 26.07iter/s]Best score: 0.2882: : 1065iter [00:42, 27.66iter/s]Best score: 0.2882: : 1065iter [00:43, 27.66iter/s]Best score: 0.2882: : 1066iter [00:43, 27.66iter/s]Best score: 0.2882: : 1067iter [00:43, 27.66iter/s]Best score: 0.2882: : 1068iter [00:43, 28.23iter/s]Best score: 0.2882: : 1068iter [00:43, 28.23iter/s]Best score: 0.2882: : 1069iter [00:43, 28.23iter/s]Best score: 0.2882: : 1070iter [00:43, 28.23iter/s]Best score: 0.2882: : 1071iter [00:43, 27.90iter/s]Best score: 0.2882: : 1071iter [00:43, 27.90iter/s]Best score: 0.2882: : 1072iter [00:43, 27.90iter/s]Best score: 0.2882: : 1073iter [00:43, 27.90iter/s]Best score: 0.2882: : 1074iter [00:43, 28.21iter/s]Best score: 0.2882: : 1074iter [00:43, 28.21iter/s]Best score: 0.2882: : 1075iter [00:43, 28.21iter/s]Best score: 0.2882: : 1076iter [00:43, 28.21iter/s]Best score: 0.2882: : 1077iter [00:43, 27.34iter/s]Best score: 0.2882: : 1077iter [00:43, 27.34iter/s]Best score: 0.2882: : 1078iter [00:43, 27.34iter/s]Best score: 0.2877: : 1079iter [00:43, 27.34iter/s]Best score: 0.2877: : 1080iter [00:43, 27.07iter/s]Best score: 0.2877: : 1080iter [00:43, 27.07iter/s]Best score: 0.2877: : 1081iter [00:43, 27.07iter/s]Best score: 0.2877: : 1082iter [00:43, 27.07iter/s]Best score: 0.2877: : 1083iter [00:43, 27.64iter/s]Best score: 0.2877: : 1083iter [00:43, 27.64iter/s]Best score: 0.2877: : 1084iter [00:43, 27.64iter/s]Best score: 0.2877: : 1085iter [00:43, 27.64iter/s]Best score: 0.2877: : 1086iter [00:43, 28.04iter/s]Best score: 0.2877: : 1086iter [00:43, 28.04iter/s]Best score: 0.2877: : 1087iter [00:43, 28.04iter/s]Best score: 0.2877: : 1088iter [00:43, 28.04iter/s]Best score: 0.2877: : 1089iter [00:43, 28.32iter/s]Best score: 0.2875: : 1089iter [00:43, 28.32iter/s]Best score: 0.2875: : 1090iter [00:43, 28.32iter/s]Best score: 0.2875: : 1091iter [00:43, 28.32iter/s]Best score: 0.2875: : 1092iter [00:43, 27.91iter/s]Best score: 0.2875: : 1092iter [00:43, 27.91iter/s]Best score: 0.2875: : 1093iter [00:44, 27.91iter/s]Best score: 0.2875: : 1094iter [00:44, 27.91iter/s]Best score: 0.2875: : 1095iter [00:44, 27.93iter/s]Best score: 0.2875: : 1095iter [00:44, 27.93iter/s]Best score: 0.2875: : 1096iter [00:44, 27.93iter/s]Best score: 0.2875: : 1097iter [00:44, 27.93iter/s]Best score: 0.2875: : 1098iter [00:44, 28.05iter/s]Best score: 0.2875: : 1098iter [00:44, 28.05iter/s]
[ITER 1100] Best: 0.2872
[PARAMS] Current best parameters:
  fx: 609.6415
  fy: 610.3158
  px: 991.9020
  py: 763.2228
  k1: -0.03229841
  k2: -0.07314064
  k3: 0.05401206
  k4: -0.01232496
  p1: 0.00918922
  p2: 0.01760162
  p3: -0.02376774
  p4: -0.00753321
  s1: 0.0019
  s2: 0.0078
  s3: 0.0168
  s4: 0.0072
  tilt_x: -0.0743
  tilt_y: -0.0197
  scale: 2.9033
  rotation: -0.2631
Best score: 0.2872: : 1099iter [00:44, 28.05iter/s]Best score: 0.2872: : 1100iter [00:44, 24.82iter/s]

[📈] Running L-BFGS-B polish after 1100 DE iterations...
  Polish improved score: 0.287160 -> 0.286814

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 25,816 → 25,816 within 3500mm ring
  Ring polish improved score: 0.286814 -> 0.286049
  Success: True
  Tangential distortion: p1=0.009195, p2=0.017604, p3=-0.023812, p4=-0.007543
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.2860
[✅] Parameters copied to: /working/MDC101_W036_2026-10-01/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 609.6414528387548
    fy: 610.3157621533776
    px: 991.901956318186
    py: 763.2228371485143
    k1: -0.032320538851784625
    k2: -0.07313327729704601
    k3: 0.05403634143859957
    k4: -0.01233869906985972
    p1: 0.009194831939373177
    p2: 0.01760412480349887
    p3: -0.023812079929221255
    p4: -0.007543139159073384
    scale: 2.9033446252018145
    rotation: -0.2630932368559074
    mmpp: 1.266016256996355

[🔄] Converting 544 frames to PTD, creating debug images for 100 calibration frames...
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[✅] Saved PTDs: /working/MDC101_W036_2026-10-01/calibration/debug/4_undistorted/output/ptd
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                                                                [A📁 Rigs: 100%|██████████| 1/1 [00:01<00:00,  1.19s/rig]📁 Rigs: 100%|██████████| 1/1 [00:01<00:00,  1.19s/rig]
[✅] Saved PTDs: /working/MDC101_W036_2026-10-01/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%|▎         | 81095/3080448 [00:00<00:03, 810946.91px/s]📤 Writing LUT:   6%|▌         | 169576/3080448 [00:00<00:03, 854389.01px/s]📤 Writing LUT:   8%|▊         | 255015/3080448 [00:00<00:03, 814996.49px/s]📤 Writing LUT:  11%|█▏        | 346678/3080448 [00:00<00:03, 853979.29px/s]📤 Writing LUT:  14%|█▍        | 432314/3080448 [00:00<00:03, 818631.01px/s]📤 Writing LUT:  17%|█▋        | 520021/3080448 [00:00<00:03, 837695.16px/s]📤 Writing LUT:  20%|█▉        | 607315/3080448 [00:00<00:02, 848898.54px/s]📤 Writing LUT:  23%|██▎       | 694790/3080448 [00:00<00:02, 856969.61px/s]📤 Writing LUT:  25%|██▌       | 781422/3080448 [00:00<00:02, 859854.02px/s]📤 Writing LUT:  28%|██▊       | 867534/3080448 [00:01<00:02, 858915.34px/s]📤 Writing LUT:  31%|███       | 954677/3080448 [00:01<00:02, 862716.78px/s]📤 Writing LUT:  34%|███▍      | 1041012/3080448 [00:01<00:02, 782742.64px/s]📤 Writing LUT:  37%|███▋      | 1129565/3080448 [00:01<00:02, 811695.56px/s]📤 Writing LUT:  39%|███▉      | 1211943/3080448 [00:01<00:02, 777282.90px/s]📤 Writing LUT:  42%|████▏     | 1290709/3080448 [00:01<00:02, 731204.38px/s]📤 Writing LUT:  44%|████▍     | 1368974/3080448 [00:01<00:02, 745269.03px/s]📤 Writing LUT:  47%|████▋     | 1455614/3080448 [00:01<00:02, 779290.40px/s]📤 Writing LUT:  50%|████▉     | 1534408/3080448 [00:01<00:01, 777412.66px/s]📤 Writing LUT:  52%|█████▏    | 1612748/3080448 [00:02<00:01, 738381.10px/s]📤 Writing LUT:  55%|█████▍    | 1687316/3080448 [00:02<00:01, 736761.92px/s]📤 Writing LUT:  57%|█████▋    | 1761495/3080448 [00:02<00:01, 727469.46px/s]📤 Writing LUT:  60%|█████▉    | 1847223/3080448 [00:02<00:01, 764700.45px/s]📤 Writing LUT:  62%|██████▏   | 1924103/3080448 [00:02<00:01, 711031.69px/s]📤 Writing LUT:  65%|██████▍   | 2001570/3080448 [00:02<00:01, 728735.74px/s]📤 Writing LUT:  68%|██████▊   | 2080988/3080448 [00:02<00:01, 747348.96px/s]📤 Writing LUT:  70%|███████   | 2159597/3080448 [00:02<00:01, 758539.09px/s]📤 Writing LUT:  73%|███████▎  | 2238329/3080448 [00:02<00:01, 766945.69px/s]📤 Writing LUT:  75%|███████▌  | 2315399/3080448 [00:02<00:01, 764479.61px/s]📤 Writing LUT:  78%|███████▊  | 2396464/3080448 [00:03<00:00, 778105.72px/s]📤 Writing LUT:  81%|████████  | 2485023/3080448 [00:03<00:00, 809982.15px/s]📤 Writing LUT:  83%|████████▎ | 2566202/3080448 [00:03<00:00, 806350.17px/s]📤 Writing LUT:  86%|████████▌ | 2646965/3080448 [00:03<00:00, 774518.11px/s]📤 Writing LUT:  89%|████████▊ | 2726215/3080448 [00:03<00:00, 779723.26px/s]📤 Writing LUT:  91%|█████████ | 2804442/3080448 [00:03<00:00, 760325.85px/s]📤 Writing LUT:  94%|█████████▎| 2883967/3080448 [00:03<00:00, 770432.29px/s]📤 Writing LUT:  96%|█████████▌| 2962806/3080448 [00:03<00:00, 775681.99px/s]📤 Writing LUT:  99%|█████████▊| 3040535/3080448 [00:03<00:00, 752596.43px/s]📤 Writing LUT: 100%|██████████| 3080448/3080448 [00:03<00:00, 782987.75px/s]
[✅] LUT written to: /working/MDC101_W036_2026-10-01/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'MDC101_W036_2026-10-01' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDC101_W036_2026-10-01/calibration/MDC101_W036_2026-10-01_unknown.lut

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

[ℹ️] Detected device type: MD (rigs: [1000]mm)
📁 Rigs (heatmap):   0%|          | 0/1 [00:00<?, ?rig/s]
   🔥 1000:   0%|          | 0/544 [00:00<?, ?frame/s][A
   🔥 1000:   1%|          | 6/544 [00:00<00:09, 59.40frame/s][A
   🔥 1000:   3%|▎         | 14/544 [00:00<00:07, 70.53frame/s][A
   🔥 1000:   4%|▍         | 22/544 [00:00<00:07, 67.42frame/s][A
   🔥 1000:   5%|▌         | 29/544 [00:00<00:08, 64.33frame/s][A
   🔥 1000:   7%|▋         | 36/544 [00:00<00:07, 65.44frame/s][A
   🔥 1000:   8%|▊         | 44/544 [00:00<00:07, 68.48frame/s][A
   🔥 1000:   9%|▉         | 51/544 [00:00<00:07, 68.30frame/s][A
   🔥 1000:  11%|█         | 59/544 [00:00<00:06, 70.35frame/s][A
   🔥 1000:  12%|█▏        | 67/544 [00:00<00:06, 71.62frame/s][A
   🔥 1000:  14%|█▍        | 75/544 [00:01<00:06, 69.21frame/s][A
   🔥 1000:  15%|█▌        | 84/544 [00:01<00:06, 72.79frame/s][A
   🔥 1000:  17%|█▋        | 92/544 [00:01<00:06, 74.61frame/s][A
   🔥 1000:  18%|█▊        | 100/544 [00:01<00:06, 73.72frame/s][A
   🔥 1000:  20%|█▉        | 108/544 [00:01<00:06, 70.84frame/s][A
   🔥 1000:  21%|██▏       | 116/544 [00:01<00:06, 68.21frame/s][A
   🔥 1000:  23%|██▎       | 123/544 [00:01<00:06, 64.73frame/s][A
   🔥 1000:  24%|██▍       | 130/544 [00:01<00:06, 64.94frame/s][A
   🔥 1000:  25%|██▌       | 138/544 [00:02<00:06, 66.84frame/s][A
   🔥 1000:  27%|██▋       | 145/544 [00:02<00:06, 65.57frame/s][A
   🔥 1000:  28%|██▊       | 152/544 [00:02<00:06, 64.20frame/s][A
   🔥 1000:  29%|██▉       | 160/544 [00:02<00:05, 67.73frame/s][A
   🔥 1000:  31%|███       | 168/544 [00:02<00:05, 70.94frame/s][A
   🔥 1000:  32%|███▏      | 176/544 [00:02<00:05, 72.38frame/s][A
   🔥 1000:  34%|███▍      | 184/544 [00:02<00:04, 72.03frame/s][A
   🔥 1000:  35%|███▌      | 192/544 [00:02<00:05, 70.32frame/s][A
   🔥 1000:  37%|███▋      | 200/544 [00:02<00:04, 70.49frame/s][A
   🔥 1000:  38%|███▊      | 208/544 [00:02<00:04, 73.03frame/s][A
   🔥 1000:  40%|███▉      | 216/544 [00:03<00:04, 72.55frame/s][A
   🔥 1000:  41%|████      | 224/544 [00:03<00:04, 69.50frame/s][A
   🔥 1000:  42%|████▏     | 231/544 [00:03<00:04, 69.44frame/s][A
   🔥 1000:  44%|████▍     | 239/544 [00:03<00:04, 71.42frame/s][A
   🔥 1000:  45%|████▌     | 247/544 [00:03<00:04, 72.42frame/s][A
   🔥 1000:  47%|████▋     | 255/544 [00:03<00:04, 71.81frame/s][A
   🔥 1000:  48%|████▊     | 263/544 [00:03<00:03, 71.59frame/s][A
   🔥 1000:  50%|████▉     | 271/544 [00:03<00:03, 73.05frame/s][A
   🔥 1000:  51%|█████▏    | 280/544 [00:03<00:03, 75.34frame/s][A
   🔥 1000:  53%|█████▎    | 289/544 [00:04<00:03, 77.43frame/s][A
   🔥 1000:  55%|█████▍    | 298/544 [00:04<00:03, 79.29frame/s][A
   🔥 1000:  56%|█████▋    | 307/544 [00:04<00:02, 79.87frame/s][A
   🔥 1000:  58%|█████▊    | 315/544 [00:04<00:02, 78.67frame/s][A
   🔥 1000:  59%|█████▉    | 323/544 [00:04<00:02, 78.22frame/s][A
   🔥 1000:  61%|██████    | 331/544 [00:04<00:02, 74.36frame/s][A
   🔥 1000:  62%|██████▏   | 339/544 [00:04<00:02, 75.34frame/s][A
   🔥 1000:  64%|██████▍   | 347/544 [00:04<00:02, 76.06frame/s][A
   🔥 1000:  65%|██████▌   | 355/544 [00:04<00:02, 74.77frame/s][A
   🔥 1000:  67%|██████▋   | 363/544 [00:05<00:02, 73.97frame/s][A
   🔥 1000:  68%|██████▊   | 371/544 [00:05<00:02, 74.55frame/s][A
   🔥 1000:  70%|██████▉   | 379/544 [00:05<00:02, 73.56frame/s][A
   🔥 1000:  71%|███████   | 387/544 [00:05<00:02, 64.49frame/s][A
   🔥 1000:  72%|███████▏  | 394/544 [00:05<00:02, 63.17frame/s][A
   🔥 1000:  74%|███████▎  | 401/544 [00:05<00:02, 63.00frame/s][A
   🔥 1000:  75%|███████▌  | 408/544 [00:05<00:02, 62.83frame/s][A
   🔥 1000:  76%|███████▋  | 415/544 [00:05<00:02, 60.70frame/s][A
   🔥 1000:  78%|███████▊  | 422/544 [00:06<00:01, 61.12frame/s][A
   🔥 1000:  79%|███████▉  | 429/544 [00:06<00:01, 61.96frame/s][A
   🔥 1000:  80%|████████  | 437/544 [00:06<00:01, 66.03frame/s][A
   🔥 1000:  82%|████████▏ | 446/544 [00:06<00:01, 69.92frame/s][A
   🔥 1000:  83%|████████▎ | 454/544 [00:06<00:01, 71.21frame/s][A
   🔥 1000:  85%|████████▌ | 463/544 [00:06<00:01, 75.22frame/s][A
   🔥 1000:  87%|████████▋ | 472/544 [00:06<00:00, 77.41frame/s][A
   🔥 1000:  88%|████████▊ | 481/544 [00:06<00:00, 80.46frame/s][A
   🔥 1000:  90%|█████████ | 490/544 [00:06<00:00, 78.82frame/s][A
   🔥 1000:  92%|█████████▏| 499/544 [00:07<00:00, 79.30frame/s][A
   🔥 1000:  93%|█████████▎| 508/544 [00:07<00:00, 80.60frame/s][A
   🔥 1000:  95%|█████████▌| 517/544 [00:07<00:00, 80.97frame/s][A
   🔥 1000:  97%|█████████▋| 526/544 [00:07<00:00, 75.97frame/s][A
   🔥 1000:  98%|█████████▊| 534/544 [00:07<00:00, 72.81frame/s][A
   🔥 1000: 100%|█████████▉| 542/544 [00:07<00:00, 73.31frame/s][A
                                                                [A[✅] 1000: /working/MDC101_W036_2026-10-01/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDC101_W036_2026-10-01/calibration/debug/5_heatmap/1000_heatmap_fitted.png
📁 Rigs (heatmap): 100%|██████████| 1/1 [00:11<00:00, 11.26s/rig]📁 Rigs (heatmap): 100%|██████████| 1/1 [00:11<00:00, 11.26s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MDC101_W036_2026-10-01/calibration/debug/5_heatmap
[🏁] Finished processing MDC101_W036_2026-10-01


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