2026-05-17T22:47:00 - INFO: Slick 0.0.8a11

🟢 Starting Calibration Pipeline

=== Processing MDC044_W038_2026-03-10 ===
2026-05-17T22:47:00 - INFO: Camera ID: 6393994
2026-05-17T22:47:00 - INFO: Wand ID: 
2026-05-17T22:47:00 - INFO: Recorded At: 2026-03-10T14:27:08Z

-------------------------------------------------------------------
                        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 2 las0.zip files to process
Processing Rigs:   0%|          | 0/2 [00:00<?, ?it/s][INFO] Filtered 1200 stationary frames, 201 remain

→ 500 (201 images) Phase 1:   0%|          | 0/201 [00:00<?, ?it/s][A
→ 500 (201 images) Phase 1:   0%|          | 1/201 [00:00<01:20,  2.49it/s][A
→ 500 (201 images) Phase 1:   1%|          | 2/201 [00:00<00:50,  3.92it/s][A
→ 500 (201 images) Phase 1:   6%|▋         | 13/201 [00:00<00:06, 30.12it/s][A
→ 500 (201 images) Phase 1:  16%|█▋        | 33/201 [00:00<00:02, 63.85it/s][A
→ 500 (201 images) Phase 1:  21%|██        | 42/201 [00:01<00:03, 48.76it/s][A
→ 500 (201 images) Phase 1:  25%|██▌       | 51/201 [00:01<00:02, 55.93it/s][A
→ 500 (201 images) Phase 1:  33%|███▎      | 66/201 [00:01<00:02, 61.57it/s][A
→ 500 (201 images) Phase 1:  37%|███▋      | 74/201 [00:01<00:02, 61.62it/s][A
→ 500 (201 images) Phase 1:  41%|████      | 82/201 [00:01<00:01, 64.89it/s][A
→ 500 (201 images) Phase 1:  49%|████▉     | 98/201 [00:01<00:01, 71.21it/s][A
→ 500 (201 images) Phase 1:  53%|█████▎    | 106/201 [00:01<00:01, 68.80it/s][A
→ 500 (201 images) Phase 1:  57%|█████▋    | 114/201 [00:02<00:01, 69.33it/s][A
→ 500 (201 images) Phase 1:  65%|██████▍   | 130/201 [00:02<00:00, 74.41it/s][A
→ 500 (201 images) Phase 1:  69%|██████▊   | 138/201 [00:02<00:00, 70.88it/s][A
→ 500 (201 images) Phase 1:  73%|███████▎  | 146/201 [00:02<00:00, 71.05it/s][A
→ 500 (201 images) Phase 1:  81%|████████  | 162/201 [00:02<00:00, 74.56it/s][A
→ 500 (201 images) Phase 1:  85%|████████▍ | 170/201 [00:02<00:00, 71.67it/s][A
→ 500 (201 images) Phase 1:  89%|████████▊ | 178/201 [00:02<00:00, 72.56it/s][A
→ 500 (201 images) Phase 1:  97%|█████████▋| 195/201 [00:03<00:00, 85.21it/s][A
                                                                             [A
→ 500 Phase 2: corners:   0%|          | 0/201 [00:00<?, ?it/s][A
→ 500 Phase 2: corners:   0%|          | 1/201 [00:00<00:35,  5.64it/s][A
→ 500 Phase 2: corners:   7%|▋         | 14/201 [00:00<00:03, 58.73it/s][A
→ 500 Phase 2: corners:  12%|█▏        | 24/201 [00:00<00:02, 69.26it/s][A
→ 500 Phase 2: corners:  19%|█▉        | 38/201 [00:00<00:01, 90.93it/s][A
→ 500 Phase 2: corners:  27%|██▋       | 54/201 [00:00<00:01, 111.37it/s][A
→ 500 Phase 2: corners:  33%|███▎      | 67/201 [00:00<00:01, 113.23it/s][A
→ 500 Phase 2: corners:  41%|████▏     | 83/201 [00:00<00:00, 126.92it/s][A
→ 500 Phase 2: corners:  48%|████▊     | 97/201 [00:00<00:00, 129.96it/s][A
→ 500 Phase 2: corners:  55%|█████▌    | 111/201 [00:01<00:00, 129.52it/s][A
→ 500 Phase 2: corners:  62%|██████▏   | 125/201 [00:01<00:00, 123.47it/s][A
→ 500 Phase 2: corners:  70%|██████▉   | 140/201 [00:01<00:00, 130.26it/s][A
→ 500 Phase 2: corners:  77%|███████▋  | 154/201 [00:01<00:00, 124.65it/s][A
→ 500 Phase 2: corners:  84%|████████▎ | 168/201 [00:01<00:00, 128.39it/s][A
→ 500 Phase 2: corners:  91%|█████████ | 182/201 [00:01<00:00, 131.43it/s][A
                                                                          [A[PASS2] Summary: 0 frames fixed, 0 untrusted, 201 total

→ 500 Phase 3: finalize:   0%|          | 0/201 [00:00<?, ?it/s][A
→ 500 Phase 3: finalize:   2%|▏         | 5/201 [00:00<00:04, 45.75it/s][A
→ 500 Phase 3: finalize:   5%|▌         | 11/201 [00:00<00:03, 49.04it/s][A
→ 500 Phase 3: finalize:   8%|▊         | 17/201 [00:00<00:03, 50.46it/s][A
→ 500 Phase 3: finalize:  11%|█▏        | 23/201 [00:00<00:03, 51.15it/s][A
→ 500 Phase 3: finalize:  14%|█▍        | 29/201 [00:00<00:03, 51.43it/s][A
→ 500 Phase 3: finalize:  17%|█▋        | 35/201 [00:00<00:03, 51.81it/s][A
→ 500 Phase 3: finalize:  20%|██        | 41/201 [00:00<00:03, 51.96it/s][A
→ 500 Phase 3: finalize:  23%|██▎       | 47/201 [00:00<00:02, 51.69it/s][A
→ 500 Phase 3: finalize:  26%|██▋       | 53/201 [00:01<00:02, 51.41it/s][A
→ 500 Phase 3: finalize:  29%|██▉       | 59/201 [00:01<00:02, 51.24it/s][A
→ 500 Phase 3: finalize:  32%|███▏      | 65/201 [00:01<00:02, 50.76it/s][A
→ 500 Phase 3: finalize:  35%|███▌      | 71/201 [00:01<00:02, 50.04it/s][A
→ 500 Phase 3: finalize:  38%|███▊      | 77/201 [00:01<00:02, 50.41it/s][A
→ 500 Phase 3: finalize:  41%|████▏     | 83/201 [00:01<00:02, 50.79it/s][A
→ 500 Phase 3: finalize:  44%|████▍     | 89/201 [00:01<00:02, 51.22it/s][A
→ 500 Phase 3: finalize:  47%|████▋     | 95/201 [00:01<00:02, 51.79it/s][A
→ 500 Phase 3: finalize:  50%|█████     | 101/201 [00:01<00:01, 52.28it/s][A
→ 500 Phase 3: finalize:  53%|█████▎    | 107/201 [00:02<00:01, 52.53it/s][A
→ 500 Phase 3: finalize:  56%|█████▌    | 113/201 [00:02<00:01, 52.56it/s][A
→ 500 Phase 3: finalize:  59%|█████▉    | 119/201 [00:02<00:01, 52.54it/s][A
→ 500 Phase 3: finalize:  62%|██████▏   | 125/201 [00:02<00:01, 52.17it/s][A
→ 500 Phase 3: finalize:  65%|██████▌   | 131/201 [00:02<00:01, 52.35it/s][A
→ 500 Phase 3: finalize:  68%|██████▊   | 137/201 [00:02<00:01, 52.56it/s][A
→ 500 Phase 3: finalize:  71%|███████   | 143/201 [00:02<00:01, 52.78it/s][A
→ 500 Phase 3: finalize:  74%|███████▍  | 149/201 [00:02<00:00, 52.85it/s][A
→ 500 Phase 3: finalize:  77%|███████▋  | 155/201 [00:02<00:00, 52.95it/s][A
→ 500 Phase 3: finalize:  80%|████████  | 161/201 [00:03<00:00, 52.99it/s][A
→ 500 Phase 3: finalize:  83%|████████▎ | 167/201 [00:03<00:00, 53.16it/s][A
→ 500 Phase 3: finalize:  86%|████████▌ | 173/201 [00:03<00:00, 52.78it/s][A
→ 500 Phase 3: finalize:  89%|████████▉ | 179/201 [00:03<00:00, 52.88it/s][A
→ 500 Phase 3: finalize:  92%|█████████▏| 185/201 [00:03<00:00, 53.03it/s][A
→ 500 Phase 3: finalize:  95%|█████████▌| 191/201 [00:03<00:00, 53.11it/s][A
→ 500 Phase 3: finalize:  98%|█████████▊| 197/201 [00:03<00:00, 53.05it/s][A
                                                                          [A
[TIMING] 500 — 201 frames
  Phase 1  radial detect   (parallel)  :   3.25s  (16.2 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.67s  (8.3 ms/frame)
  Phase 2b corner fix      (sequential):   0.04s
  Phase 3  finalize        (sequential):   3.86s  (19.2 ms/frame)
    decode + undistort                 :   2.06s  (10.2 ms/frame)
    corner apply + refinement          :   0.81s  (4.0 ms/frame)
    segment                            :   0.82s  (4.1 ms/frame)
    smooth                             :   0.12s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :   8.83s

Processing Rigs:  50%|█████     | 1/2 [00:14<00:14, 14.88s/it][INFO] Filtered 659 stationary frames, 160 remain

→ 1000 (160 images) Phase 1:   0%|          | 0/160 [00:00<?, ?it/s][A
→ 1000 (160 images) Phase 1:   1%|          | 1/160 [00:00<01:32,  1.71it/s][A
→ 1000 (160 images) Phase 1:   2%|▎         | 4/160 [00:00<00:21,  7.13it/s][A
→ 1000 (160 images) Phase 1:  17%|█▋        | 27/160 [00:00<00:02, 52.43it/s][A
→ 1000 (160 images) Phase 1:  23%|██▎       | 37/160 [00:01<00:02, 42.69it/s][A
→ 1000 (160 images) Phase 1:  37%|███▋      | 59/160 [00:01<00:01, 72.33it/s][A
→ 1000 (160 images) Phase 1:  44%|████▍     | 71/160 [00:01<00:01, 56.62it/s][A
→ 1000 (160 images) Phase 1:  57%|█████▊    | 92/160 [00:01<00:00, 76.74it/s][A
→ 1000 (160 images) Phase 1:  64%|██████▍   | 103/160 [00:02<00:00, 61.41it/s][A
→ 1000 (160 images) Phase 1:  78%|███████▊  | 124/160 [00:02<00:00, 80.03it/s][A
→ 1000 (160 images) Phase 1:  84%|████████▍ | 135/160 [00:02<00:00, 63.78it/s][A
→ 1000 (160 images) Phase 1:  99%|█████████▉| 159/160 [00:02<00:00, 87.96it/s][A
                                                                              [A
→ 1000 Phase 2: corners:   0%|          | 0/160 [00:00<?, ?it/s][A
→ 1000 Phase 2: corners:   1%|          | 1/160 [00:00<00:49,  3.21it/s][A
→ 1000 Phase 2: corners:  11%|█▏        | 18/160 [00:00<00:02, 53.88it/s][A
→ 1000 Phase 2: corners:  21%|██        | 33/160 [00:00<00:01, 82.75it/s][A
→ 1000 Phase 2: corners:  29%|██▉       | 46/160 [00:00<00:01, 95.61it/s][A
→ 1000 Phase 2: corners:  38%|███▊      | 60/160 [00:00<00:00, 106.16it/s][A
→ 1000 Phase 2: corners:  47%|████▋     | 75/160 [00:00<00:00, 116.36it/s][A
→ 1000 Phase 2: corners:  55%|█████▌    | 88/160 [00:00<00:00, 116.92it/s][A
→ 1000 Phase 2: corners:  63%|██████▎   | 101/160 [00:01<00:00, 111.53it/s][A
→ 1000 Phase 2: corners:  71%|███████   | 113/160 [00:01<00:00, 112.31it/s][A
→ 1000 Phase 2: corners:  81%|████████  | 129/160 [00:01<00:00, 123.39it/s][A
→ 1000 Phase 2: corners:  89%|████████▉ | 142/160 [00:01<00:00, 124.56it/s][A
                                                                           [A[PASS2] Frame 0000331: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000333: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000334: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000337: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000339: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000342: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000343: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000345: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000346: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000445: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000447: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000448: fixed corners {1, 2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000450: fixed corners {1, 2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000453: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000466: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000468: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000469: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000471: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000585: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000586: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000588: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000604: fixed corners {1, 2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000933: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000934: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000936: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000937: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000939: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000940: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000942: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000943: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000945: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000946: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001090: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001092: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001093: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001095: fixed corners {0, 2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001096: fixed corners {1, 2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001098: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001099: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001102: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001104: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001105: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001107: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001108: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001110: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001111: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001113: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001114: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001117: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001119: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001237: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001240: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001242: fixed corners {0, 2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001243: fixed corners {2, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001245: fixed corners {1, 2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000330: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000450: fixed corners {0, 2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000451: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000586: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000604: fixed corners {1, 2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000945: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001093: fixed corners {1, 2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001095: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001096: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001098: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001104: fixed corners {0, 2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001105: fixed corners {0, 2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001245: fixed corners {1, 2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000330: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000447: fixed corners {1, 2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000448: fixed corners {1, 2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000586: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000604: fixed corners {1, 2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000940: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001095: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001096: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001098: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001104: fixed corners {0, 2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001105: fixed corners {0, 2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001245: fixed corners {1, 2, 3} (was_fixed=False, trusted=False)
[PASS2] Summary: 31 frames fixed, 81 untrusted, 160 total

→ 1000 Phase 3: finalize:   0%|          | 0/160 [00:00<?, ?it/s][A
→ 1000 Phase 3: finalize:   6%|▌         | 9/160 [00:00<00:01, 86.69it/s][A
→ 1000 Phase 3: finalize:  11%|█▏        | 18/160 [00:00<00:01, 72.63it/s][A
→ 1000 Phase 3: finalize:  16%|█▋        | 26/160 [00:00<00:01, 72.53it/s][A
→ 1000 Phase 3: finalize:  21%|██▏       | 34/160 [00:00<00:01, 69.73it/s][A
→ 1000 Phase 3: finalize:  26%|██▋       | 42/160 [00:00<00:01, 65.41it/s][A
→ 1000 Phase 3: finalize:  31%|███       | 49/160 [00:00<00:01, 63.30it/s][A
→ 1000 Phase 3: finalize:  35%|███▌      | 56/160 [00:00<00:01, 62.25it/s][A
→ 1000 Phase 3: finalize:  39%|███▉      | 63/160 [00:00<00:01, 60.37it/s][A
→ 1000 Phase 3: finalize:  44%|████▍     | 70/160 [00:01<00:01, 57.99it/s][A
→ 1000 Phase 3: finalize:  48%|████▊     | 76/160 [00:01<00:01, 55.91it/s][A
→ 1000 Phase 3: finalize:  51%|█████▏    | 82/160 [00:01<00:01, 53.50it/s][A
→ 1000 Phase 3: finalize:  55%|█████▌    | 88/160 [00:01<00:01, 51.83it/s][A
→ 1000 Phase 3: finalize:  59%|█████▉    | 94/160 [00:01<00:01, 50.45it/s][A
→ 1000 Phase 3: finalize:  62%|██████▎   | 100/160 [00:01<00:01, 49.62it/s][A
→ 1000 Phase 3: finalize:  66%|██████▋   | 106/160 [00:01<00:01, 50.06it/s][A
→ 1000 Phase 3: finalize:  70%|███████   | 112/160 [00:01<00:00, 51.36it/s][A
→ 1000 Phase 3: finalize:  74%|███████▍  | 118/160 [00:02<00:00, 51.76it/s][A
→ 1000 Phase 3: finalize:  78%|███████▊  | 124/160 [00:02<00:00, 51.83it/s][A
→ 1000 Phase 3: finalize:  81%|████████▏ | 130/160 [00:02<00:00, 52.98it/s][A
→ 1000 Phase 3: finalize:  85%|████████▌ | 136/160 [00:02<00:00, 53.43it/s][A
→ 1000 Phase 3: finalize:  89%|████████▉ | 142/160 [00:02<00:00, 53.66it/s][A
→ 1000 Phase 3: finalize:  92%|█████████▎| 148/160 [00:02<00:00, 53.67it/s][A
→ 1000 Phase 3: finalize:  96%|█████████▋| 154/160 [00:02<00:00, 53.32it/s][A
→ 1000 Phase 3: finalize: 100%|██████████| 160/160 [00:02<00:00, 52.85it/s][A
                                                                           [A
[TIMING] 1000 — 160 frames
  Phase 1  radial detect   (parallel)  :   2.64s  (16.5 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.52s  (9.5 ms/frame)
  Phase 2b corner fix      (sequential):   1.42s
  Phase 3  finalize        (sequential):   2.85s  (17.8 ms/frame)
    decode + undistort                 :   1.48s  (9.3 ms/frame)
    corner apply + refinement          :   0.60s  (3.8 ms/frame)
    segment                            :   0.62s  (3.8 ms/frame)
    smooth                             :   0.10s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :   8.43s

Processing Rigs: 100%|██████████| 2/2 [00:26<00:00, 12.83s/it]Processing Rigs: 100%|██████████| 2/2 [00:26<00:00, 13.14s/it]
[💾] Saved RigFrameDataset to /working/MDC044_W038_2026-03-10/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 361 frames from 2 rigs to /working/MDC044_W038_2026-03-10/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDC044_W038_2026-03-10/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 500: 100 frames selected from 201
[📋] 1000: 100 frames selected from 160
[💾] Saved RigFrameDataset to /working/MDC044_W038_2026-03-10/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDC044_W038_2026-03-10/calibration/debug/1_digitized/rig_frames.json

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

-> Calculating the casing center ...
[INFO] Using 40 total sampled bright frames
Computing max image from bright frames:   0%|          | 0/40 [00:00<?, ?it/s]Computing max image from bright frames:   2%|▎         | 1/40 [00:03<02:05,  3.22s/it]Computing max image from bright frames:   5%|▌         | 2/40 [00:06<02:01,  3.19s/it]Computing max image from bright frames:   8%|▊         | 3/40 [00:09<01:57,  3.17s/it]Computing max image from bright frames:  10%|█         | 4/40 [00:12<01:53,  3.16s/it]Computing max image from bright frames:  12%|█▎        | 5/40 [00:15<01:50,  3.16s/it]Computing max image from bright frames:  15%|█▌        | 6/40 [00:19<01:47,  3.16s/it]Computing max image from bright frames:  18%|█▊        | 7/40 [00:22<01:44,  3.16s/it]Computing max image from bright frames:  20%|██        | 8/40 [00:25<01:41,  3.16s/it]Computing max image from bright frames:  22%|██▎       | 9/40 [00:28<01:38,  3.17s/it]Computing max image from bright frames:  25%|██▌       | 10/40 [00:31<01:36,  3.20s/it]Computing max image from bright frames:  28%|██▊       | 11/40 [00:35<01:36,  3.32s/it]Computing max image from bright frames:  30%|███       | 12/40 [00:38<01:34,  3.38s/it]Computing max image from bright frames:  32%|███▎      | 13/40 [00:42<01:32,  3.41s/it]Computing max image from bright frames:  35%|███▌      | 14/40 [00:45<01:28,  3.42s/it]Computing max image from bright frames:  38%|███▊      | 15/40 [00:49<01:25,  3.40s/it]Computing max image from bright frames:  40%|████      | 16/40 [00:52<01:19,  3.33s/it]Computing max image from bright frames:  42%|████▎     | 17/40 [00:55<01:15,  3.27s/it]Computing max image from bright frames:  45%|████▌     | 18/40 [00:58<01:11,  3.24s/it]Computing max image from bright frames:  48%|████▊     | 19/40 [01:01<01:07,  3.21s/it]Computing max image from bright frames:  50%|█████     | 20/40 [01:05<01:04,  3.22s/it]Computing max image from bright frames:  52%|█████▎    | 21/40 [01:08<01:00,  3.20s/it]Computing max image from bright frames:  55%|█████▌    | 22/40 [01:11<00:57,  3.17s/it]Computing max image from bright frames:  57%|█████▊    | 23/40 [01:14<00:53,  3.16s/it]Computing max image from bright frames:  60%|██████    | 24/40 [01:17<00:50,  3.15s/it]Computing max image from bright frames:  62%|██████▎   | 25/40 [01:20<00:47,  3.19s/it]Computing max image from bright frames:  65%|██████▌   | 26/40 [01:24<00:44,  3.18s/it]Computing max image from bright frames:  68%|██████▊   | 27/40 [01:27<00:41,  3.19s/it]Computing max image from bright frames:  70%|███████   | 28/40 [01:30<00:38,  3.21s/it]Computing max image from bright frames:  72%|███████▎  | 29/40 [01:33<00:35,  3.23s/it]Computing max image from bright frames:  75%|███████▌  | 30/40 [01:36<00:32,  3.21s/it]Computing max image from bright frames:  78%|███████▊  | 31/40 [01:40<00:28,  3.20s/it]Computing max image from bright frames:  80%|████████  | 32/40 [01:43<00:25,  3.19s/it]Computing max image from bright frames:  82%|████████▎ | 33/40 [01:46<00:22,  3.18s/it]Computing max image from bright frames:  85%|████████▌ | 34/40 [01:49<00:19,  3.18s/it]Computing max image from bright frames:  88%|████████▊ | 35/40 [01:52<00:15,  3.19s/it]Computing max image from bright frames:  90%|█████████ | 36/40 [01:55<00:12,  3.19s/it]Computing max image from bright frames:  92%|█████████▎| 37/40 [01:59<00:09,  3.21s/it]Computing max image from bright frames:  95%|█████████▌| 38/40 [02:02<00:06,  3.22s/it]Computing max image from bright frames:  98%|█████████▊| 39/40 [02:05<00:03,  3.24s/it]Computing max image from bright frames: 100%|██████████| 40/40 [02:09<00:00,  3.24s/it]                                                                                       [✅] Casing detection complete: cx=1018.0, cy=751.0

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

  0%|          | 0/100 [00:00<?, ?it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.016 | Best: {'fx': 356.566} (0.016):   0%|          | 0/100 [00:00<?, ?it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.016 | Best: {'fx': 356.566} (0.016):   1%|          | 1/100 [00:00<00:29,  3.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.015 | Best: {'fx': 356.566} (0.016):   1%|          | 1/100 [00:00<00:29,  3.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.016 | Best: {'fx': 356.566} (0.016):   2%|▏         | 2/100 [00:00<00:29,  3.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.016 | Best: {'fx': 349.495} (0.016):   3%|▎         | 3/100 [00:00<00:28,  3.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.019 | Best: {'fx': 300.0} (0.019):   4%|▍         | 4/100 [00:00<00:28,  3.37it/s]  Brute | Start: {'fx': 500.0} (0.023) | Current: 0.014 | Best: {'fx': 300.0} (0.019):   5%|▌         | 5/100 [00:00<00:28,  3.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.015 | Best: {'fx': 300.0} (0.019):   6%|▌         | 6/100 [00:00<00:27,  3.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.014 | Best: {'fx': 300.0} (0.019):   7%|▋         | 7/100 [00:00<00:27,  3.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.014 | Best: {'fx': 300.0} (0.019):   8%|▊         | 8/100 [00:00<00:27,  3.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.014 | Best: {'fx': 300.0} (0.019):   9%|▉         | 9/100 [00:00<00:27,  3.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.014 | Best: {'fx': 300.0} (0.019):  10%|█         | 10/100 [00:00<00:26,  3.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.015 | Best: {'fx': 300.0} (0.019):  11%|█         | 11/100 [00:00<00:26,  3.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.015 | Best: {'fx': 300.0} (0.019):  12%|█▏        | 12/100 [00:00<00:26,  3.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.015 | Best: {'fx': 300.0} (0.019):  13%|█▎        | 13/100 [00:00<00:02, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.048 | Best: {'fx': 519.192} (0.048):  13%|█▎        | 13/100 [00:00<00:02, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.062 | Best: {'fx': 526.263} (0.062):  14%|█▍        | 14/100 [00:00<00:02, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.062 | Best: {'fx': 540.404} (0.062):  15%|█▌        | 15/100 [00:00<00:02, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.015 | Best: {'fx': 540.404} (0.062):  16%|█▌        | 16/100 [00:00<00:02, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.085 | Best: {'fx': 533.333} (0.085):  17%|█▋        | 17/100 [00:00<00:02, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.014 | Best: {'fx': 533.333} (0.085):  18%|█▊        | 18/100 [00:00<00:02, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.015 | Best: {'fx': 533.333} (0.085):  19%|█▉        | 19/100 [00:00<00:02, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.016 | Best: {'fx': 533.333} (0.085):  20%|██        | 20/100 [00:00<00:01, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.015 | Best: {'fx': 533.333} (0.085):  21%|██        | 21/100 [00:00<00:01, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.015 | Best: {'fx': 533.333} (0.085):  22%|██▏       | 22/100 [00:00<00:01, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.048 | Best: {'fx': 533.333} (0.085):  23%|██▎       | 23/100 [00:00<00:01, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.041 | Best: {'fx': 533.333} (0.085):  24%|██▍       | 24/100 [00:00<00:01, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.016 | Best: {'fx': 533.333} (0.085):  25%|██▌       | 25/100 [00:00<00:01, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.036 | Best: {'fx': 533.333} (0.085):  26%|██▌       | 26/100 [00:00<00:01, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.015 | Best: {'fx': 533.333} (0.085):  27%|██▋       | 27/100 [00:00<00:01, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.038 | Best: {'fx': 533.333} (0.085):  28%|██▊       | 28/100 [00:00<00:01, 40.03it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.038 | Best: {'fx': 533.333} (0.085):  29%|██▉       | 29/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.034 | Best: {'fx': 533.333} (0.085):  29%|██▉       | 29/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.015 | Best: {'fx': 533.333} (0.085):  30%|███       | 30/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.016 | Best: {'fx': 533.333} (0.085):  31%|███       | 31/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.032 | Best: {'fx': 533.333} (0.085):  32%|███▏      | 32/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.031 | Best: {'fx': 533.333} (0.085):  33%|███▎      | 33/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.016 | Best: {'fx': 533.333} (0.085):  34%|███▍      | 34/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.030 | Best: {'fx': 533.333} (0.085):  35%|███▌      | 35/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  36%|███▌      | 36/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  37%|███▋      | 37/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.017 | Best: {'fx': 533.333} (0.085):  38%|███▊      | 38/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.017 | Best: {'fx': 533.333} (0.085):  39%|███▉      | 39/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.030 | Best: {'fx': 533.333} (0.085):  40%|████      | 40/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  41%|████      | 41/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  42%|████▏     | 42/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  43%|████▎     | 43/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  44%|████▍     | 44/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.022 | Best: {'fx': 533.333} (0.085):  45%|████▌     | 45/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  46%|████▌     | 46/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  47%|████▋     | 47/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.025 | Best: {'fx': 533.333} (0.085):  48%|████▊     | 48/100 [00:00<00:00, 76.06it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.025 | Best: {'fx': 533.333} (0.085):  49%|████▉     | 49/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  49%|████▉     | 49/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.035 | Best: {'fx': 533.333} (0.085):  50%|█████     | 50/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.027 | Best: {'fx': 533.333} (0.085):  51%|█████     | 51/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  52%|█████▏    | 52/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.027 | Best: {'fx': 533.333} (0.085):  53%|█████▎    | 53/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  54%|█████▍    | 54/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.027 | Best: {'fx': 533.333} (0.085):  55%|█████▌    | 55/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.027 | Best: {'fx': 533.333} (0.085):  56%|█████▌    | 56/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.027 | Best: {'fx': 533.333} (0.085):  57%|█████▋    | 57/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.027 | Best: {'fx': 533.333} (0.085):  58%|█████▊    | 58/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.027 | Best: {'fx': 533.333} (0.085):  59%|█████▉    | 59/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.027 | Best: {'fx': 533.333} (0.085):  60%|██████    | 60/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  61%|██████    | 61/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.027 | Best: {'fx': 533.333} (0.085):  62%|██████▏   | 62/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.027 | Best: {'fx': 533.333} (0.085):  63%|██████▎   | 63/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  64%|██████▍   | 64/100 [00:00<00:00, 112.44it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  65%|██████▌   | 65/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  65%|██████▌   | 65/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  66%|██████▌   | 66/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  67%|██████▋   | 67/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  68%|██████▊   | 68/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  69%|██████▉   | 69/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  70%|███████   | 70/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  71%|███████   | 71/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  72%|███████▏  | 72/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  73%|███████▎  | 73/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.027 | Best: {'fx': 533.333} (0.085):  74%|███████▍  | 74/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.027 | Best: {'fx': 533.333} (0.085):  75%|███████▌  | 75/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  76%|███████▌  | 76/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  77%|███████▋  | 77/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  78%|███████▊  | 78/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  79%|███████▉  | 79/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  80%|████████  | 80/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  81%|████████  | 81/100 [00:00<00:00, 126.64it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  82%|████████▏ | 82/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  82%|████████▏ | 82/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  83%|████████▎ | 83/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  84%|████████▍ | 84/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  85%|████████▌ | 85/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  86%|████████▌ | 86/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  87%|████████▋ | 87/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  88%|████████▊ | 88/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  89%|████████▉ | 89/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  90%|█████████ | 90/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  91%|█████████ | 91/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  92%|█████████▏| 92/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  93%|█████████▎| 93/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  94%|█████████▍| 94/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  95%|█████████▌| 95/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  96%|█████████▌| 96/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  97%|█████████▋| 97/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  98%|█████████▊| 98/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  99%|█████████▉| 99/100 [00:00<00:00, 132.37it/s]Brute | Start: {'fx': 500.0} (0.023) | Current: 0.028 | Best: {'fx': 533.333} (0.085): 100%|██████████| 100/100 [00:00<00:00, 127.10it/s]                                                                                                                                           0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.028 | Best: {'fx': 508.333} (0.028):   0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.028 | Best: {'fx': 508.333} (0.028):   2%|▏         | 1/50 [00:00<00:06,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.030 | Best: {'fx': 509.354} (0.030):   2%|▏         | 1/50 [00:00<00:06,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.030 | Best: {'fx': 510.374} (0.030):   4%|▍         | 2/50 [00:00<00:05,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.032 | Best: {'fx': 511.395} (0.032):   6%|▌         | 3/50 [00:00<00:05,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.040 | Best: {'fx': 513.435} (0.040):   8%|▊         | 4/50 [00:00<00:05,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.037 | Best: {'fx': 513.435} (0.040):  10%|█         | 5/50 [00:00<00:05,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.047 | Best: {'fx': 518.537} (0.047):  12%|█▏        | 6/50 [00:00<00:05,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.041 | Best: {'fx': 518.537} (0.047):  14%|█▍        | 7/50 [00:00<00:05,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.043 | Best: {'fx': 518.537} (0.047):  16%|█▌        | 8/50 [00:00<00:05,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.044 | Best: {'fx': 518.537} (0.047):  18%|█▊        | 9/50 [00:00<00:05,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.046 | Best: {'fx': 518.537} (0.047):  20%|██        | 10/50 [00:00<00:04,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.054 | Best: {'fx': 522.619} (0.054):  22%|██▏       | 11/50 [00:00<00:04,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.049 | Best: {'fx': 522.619} (0.054):  24%|██▍       | 12/50 [00:00<00:04,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.056 | Best: {'fx': 523.639} (0.056):  26%|██▌       | 13/50 [00:00<00:04,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.052 | Best: {'fx': 523.639} (0.056):  28%|██▊       | 14/50 [00:00<00:04,  8.11it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.052 | Best: {'fx': 523.639} (0.056):  30%|███       | 15/50 [00:00<00:00, 75.62it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.050 | Best: {'fx': 523.639} (0.056):  30%|███       | 15/50 [00:00<00:00, 75.62it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.058 | Best: {'fx': 524.66} (0.058):  32%|███▏      | 16/50 [00:00<00:00, 75.62it/s] Brute | Start: {'fx': 533.333} (0.085) | Current: 0.061 | Best: {'fx': 525.68} (0.061):  34%|███▍      | 17/50 [00:00<00:00, 75.62it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.065 | Best: {'fx': 526.701} (0.065):  36%|███▌      | 18/50 [00:00<00:00, 75.62it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.069 | Best: {'fx': 527.721} (0.069):  38%|███▊      | 19/50 [00:00<00:00, 75.62it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.087 | Best: {'fx': 531.803} (0.087):  40%|████      | 20/50 [00:00<00:00, 75.62it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.072 | Best: {'fx': 531.803} (0.087):  42%|████▏     | 21/50 [00:00<00:00, 75.62it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.078 | Best: {'fx': 531.803} (0.087):  44%|████▍     | 22/50 [00:00<00:00, 75.62it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.088 | Best: {'fx': 532.823} (0.088):  46%|████▌     | 23/50 [00:00<00:00, 75.62it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.088 | Best: {'fx': 532.823} (0.088):  48%|████▊     | 24/50 [00:00<00:00, 79.46it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.081 | Best: {'fx': 532.823} (0.088):  48%|████▊     | 24/50 [00:00<00:00, 79.46it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.085 | Best: {'fx': 532.823} (0.088):  50%|█████     | 25/50 [00:00<00:00, 79.46it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.088 | Best: {'fx': 532.823} (0.088):  52%|█████▏    | 26/50 [00:00<00:00, 79.46it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.074 | Best: {'fx': 532.823} (0.088):  54%|█████▍    | 27/50 [00:00<00:00, 79.46it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.070 | Best: {'fx': 532.823} (0.088):  56%|█████▌    | 28/50 [00:00<00:00, 79.46it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.064 | Best: {'fx': 532.823} (0.088):  58%|█████▊    | 29/50 [00:00<00:00, 79.46it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.079 | Best: {'fx': 532.823} (0.088):  60%|██████    | 30/50 [00:00<00:00, 79.46it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.066 | Best: {'fx': 532.823} (0.088):  62%|██████▏   | 31/50 [00:00<00:00, 79.46it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.061 | Best: {'fx': 532.823} (0.088):  64%|██████▍   | 32/50 [00:00<00:00, 79.46it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.054 | Best: {'fx': 532.823} (0.088):  66%|██████▌   | 33/50 [00:00<00:00, 79.46it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.054 | Best: {'fx': 532.823} (0.088):  68%|██████▊   | 34/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.058 | Best: {'fx': 532.823} (0.088):  68%|██████▊   | 34/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.054 | Best: {'fx': 532.823} (0.088):  70%|███████   | 35/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.051 | Best: {'fx': 532.823} (0.088):  72%|███████▏  | 36/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.050 | Best: {'fx': 532.823} (0.088):  74%|███████▍  | 37/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.043 | Best: {'fx': 532.823} (0.088):  76%|███████▌  | 38/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.046 | Best: {'fx': 532.823} (0.088):  78%|███████▊  | 39/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.049 | Best: {'fx': 532.823} (0.088):  80%|████████  | 40/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.047 | Best: {'fx': 532.823} (0.088):  82%|████████▏ | 41/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.047 | Best: {'fx': 532.823} (0.088):  84%|████████▍ | 42/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.041 | Best: {'fx': 532.823} (0.088):  86%|████████▌ | 43/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.045 | Best: {'fx': 532.823} (0.088):  88%|████████▊ | 44/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.040 | Best: {'fx': 532.823} (0.088):  90%|█████████ | 45/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.039 | Best: {'fx': 532.823} (0.088):  92%|█████████▏| 46/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.043 | Best: {'fx': 532.823} (0.088):  94%|█████████▍| 47/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.042 | Best: {'fx': 532.823} (0.088):  96%|█████████▌| 48/50 [00:00<00:00, 85.79it/s]Brute | Start: {'fx': 533.333} (0.085) | Current: 0.041 | Best: {'fx': 532.823} (0.088):  98%|█████████▊| 49/50 [00:00<00:00, 85.79it/s]                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 532.8231292517007
    px: 1018.0
    py: 751.0
    k1: 0.0
    k2: 0.0
    k3: 0.0
    k4: 0.0
    p1: 0.0
    p2: 0.0
    p3: 0.0
    p4: 0.0
    scale: 3.0
    rotation: 0.0


[🔲] Square Reference Optimization
    Including tangential distortion parameters (p1, p2, p3, p4) in joint optimization
  Selecting up to 20 frames per rig (excluded 2 incomplete frames): 18 frames will be used for optimization
  Rigs: 1000(1000mm):18/20
  Total: 18/20 frames used for optimization
Initial score: 27.4011: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 27.4011, picklable_objective(x0) = 24.2655
Best score: 24.2655: : 0iter [00:01, ?iter/s] Best score: 24.2655: : 1iter [00:01,  1.88s/iter]Best score: 24.2655: : 1iter [00:01,  1.88s/iter]Best score: 24.2655: : 2iter [00:01,  1.88s/iter]Best score: 24.2655: : 3iter [00:01,  1.88s/iter]Best score: 24.2655: : 4iter [00:01,  1.88s/iter]Best score: 24.2655: : 5iter [00:01,  1.88s/iter]Best score: 24.2655: : 6iter [00:01,  3.98iter/s]Best score: 24.2655: : 6iter [00:02,  3.98iter/s]Best score: 24.2655: : 7iter [00:02,  3.98iter/s]Best score: 24.2655: : 8iter [00:02,  3.98iter/s]Best score: 24.2655: : 9iter [00:02,  3.98iter/s]Best score: 24.2655: : 10iter [00:02,  3.98iter/s]Best score: 24.2655: : 11iter [00:02,  8.02iter/s]Best score: 24.2655: : 11iter [00:02,  8.02iter/s]Best score: 24.2655: : 12iter [00:02,  8.02iter/s]Best score: 24.2655: : 13iter [00:02,  8.02iter/s]Best score: 24.2655: : 14iter [00:02,  8.02iter/s]Best score: 24.2655: : 15iter [00:02,  8.02iter/s]Best score: 24.2655: : 16iter [00:02, 11.14iter/s]Best score: 24.2655: : 16iter [00:02, 11.14iter/s]Best score: 24.2655: : 17iter [00:02, 11.14iter/s]Best score: 24.2655: : 18iter [00:02, 11.14iter/s]Best score: 24.2655: : 19iter [00:02, 11.14iter/s]Best score: 24.2655: : 20iter [00:02, 11.14iter/s]Best score: 24.2655: : 21iter [00:02, 15.61iter/s]Best score: 24.2655: : 21iter [00:02, 15.61iter/s]Best score: 24.2655: : 22iter [00:02, 15.61iter/s]Best score: 24.2655: : 23iter [00:02, 15.61iter/s]Best score: 24.2655: : 24iter [00:02, 15.61iter/s]Best score: 24.2655: : 25iter [00:02, 15.61iter/s]Best score: 24.2655: : 26iter [00:02, 20.21iter/s]Best score: 24.2655: : 26iter [00:02, 20.21iter/s]Best score: 24.2655: : 27iter [00:02, 20.21iter/s]Best score: 24.2655: : 28iter [00:02, 20.21iter/s]Best score: 24.2655: : 29iter [00:02, 20.21iter/s]Best score: 24.2655: : 30iter [00:02, 20.21iter/s]Best score: 24.2655: : 31iter [00:02, 24.56iter/s]Best score: 24.2655: : 31iter [00:02, 24.56iter/s]Best score: 24.2655: : 32iter [00:02, 24.56iter/s]Best score: 24.2655: : 33iter [00:02, 24.56iter/s]Best score: 24.2655: : 34iter [00:02, 24.56iter/s]Best score: 24.2655: : 35iter [00:02, 24.56iter/s]Best score: 24.2655: : 36iter [00:02, 28.51iter/s]Best score: 24.2655: : 36iter [00:02, 28.51iter/s]Best score: 24.2655: : 37iter [00:02, 28.51iter/s]Best score: 24.2655: : 38iter [00:02, 28.51iter/s]Best score: 24.2655: : 39iter [00:02, 28.51iter/s]Best score: 24.2655: : 40iter [00:02, 28.51iter/s]Best score: 24.2655: : 41iter [00:02, 31.70iter/s]Best score: 24.2655: : 41iter [00:02, 31.70iter/s]Best score: 24.2655: : 42iter [00:02, 31.70iter/s]Best score: 24.2655: : 43iter [00:02, 31.70iter/s]Best score: 24.2655: : 44iter [00:03, 31.70iter/s]Best score: 24.2655: : 45iter [00:03, 31.70iter/s]Best score: 24.2655: : 46iter [00:03, 34.54iter/s]Best score: 24.2655: : 46iter [00:03, 34.54iter/s]Best score: 24.2655: : 47iter [00:03, 34.54iter/s]Best score: 24.2655: : 48iter [00:03, 34.54iter/s]
[ITER 50] Best: 24.2655
[PARAMS] Current best parameters:
  fx: 532.8231
  fy: 532.8231
  px: 1018.0000
  py: 751.0000
  k1: 0.00000000
  k2: -0.00000000
  k3: 0.00000000
  k4: 0.00000000
  p1: 0.00000000
  p2: 0.00000000
  p3: 0.00000000
  p4: 0.00000000
  s1: 0.0000
  s2: 0.0000
  s3: 0.0000
  s4: 0.0000
  tilt_x: 0.0000
  tilt_y: 0.0000
  scale: 3.0000
  rotation: 0.0000
Best score: 24.2655: : 49iter [00:03, 34.54iter/s]Best score: 24.2655: : 50iter [00:03, 34.54iter/s]Best score: 24.2655: : 51iter [00:03, 36.60iter/s]Best score: 24.2655: : 51iter [00:03, 36.60iter/s]Best score: 24.2655: : 52iter [00:03, 36.60iter/s]Best score: 24.2655: : 53iter [00:03, 36.60iter/s]Best score: 24.2655: : 54iter [00:03, 36.60iter/s]Best score: 24.2655: : 55iter [00:03, 36.60iter/s]Best score: 24.2655: : 56iter [00:03, 38.37iter/s]Best score: 24.2655: : 56iter [00:03, 38.37iter/s]Best score: 24.2655: : 57iter [00:03, 38.37iter/s]Best score: 24.2655: : 58iter [00:03, 38.37iter/s]Best score: 24.2655: : 59iter [00:03, 38.37iter/s]Best score: 24.2655: : 60iter [00:03, 38.37iter/s]Best score: 24.2655: : 61iter [00:03, 39.47iter/s]Best score: 24.2655: : 61iter [00:03, 39.47iter/s]Best score: 24.2655: : 62iter [00:03, 39.47iter/s]Best score: 24.2655: : 63iter [00:03, 39.47iter/s]Best score: 24.2655: : 64iter [00:03, 39.47iter/s]Best score: 24.2655: : 65iter [00:03, 39.47iter/s]Best score: 24.2655: : 66iter [00:03, 40.53iter/s]Best score: 24.2655: : 66iter [00:03, 40.53iter/s]Best score: 24.2655: : 67iter [00:03, 40.53iter/s]Best score: 24.2655: : 68iter [00:03, 40.53iter/s]Best score: 24.2655: : 69iter [00:03, 40.53iter/s]Best score: 24.2655: : 70iter [00:03, 40.53iter/s]Best score: 24.2655: : 71iter [00:03, 41.22iter/s]Best score: 24.2655: : 71iter [00:03, 41.22iter/s]Best score: 24.2655: : 72iter [00:03, 41.22iter/s]Best score: 24.2655: : 73iter [00:03, 41.22iter/s]Best score: 24.2655: : 74iter [00:03, 41.22iter/s]Best score: 24.2655: : 75iter [00:03, 41.22iter/s]Best score: 24.2655: : 76iter [00:03, 41.97iter/s]Best score: 24.2655: : 76iter [00:03, 41.97iter/s]Best score: 24.2655: : 77iter [00:03, 41.97iter/s]Best score: 24.2655: : 78iter [00:03, 41.97iter/s]Best score: 24.2655: : 79iter [00:03, 41.97iter/s]Best score: 24.2655: : 80iter [00:03, 41.97iter/s]Best score: 24.2655: : 81iter [00:03, 42.25iter/s]Best score: 24.2655: : 81iter [00:03, 42.25iter/s]Best score: 24.2655: : 82iter [00:03, 42.25iter/s]Best score: 24.2655: : 83iter [00:03, 42.25iter/s]Best score: 24.2655: : 84iter [00:03, 42.25iter/s]Best score: 24.2655: : 85iter [00:03, 42.25iter/s]Best score: 24.2655: : 86iter [00:03, 42.64iter/s]Best score: 24.2655: : 86iter [00:03, 42.64iter/s]Best score: 24.2655: : 87iter [00:04, 42.64iter/s]Best score: 24.2655: : 88iter [00:04, 42.64iter/s]Best score: 24.2655: : 89iter [00:04, 42.64iter/s]Best score: 24.2655: : 90iter [00:04, 42.64iter/s]Best score: 24.2655: : 91iter [00:04, 42.78iter/s]Best score: 24.2655: : 91iter [00:04, 42.78iter/s]Best score: 24.2655: : 92iter [00:04, 42.78iter/s]Best score: 24.2655: : 93iter [00:04, 42.78iter/s]Best score: 24.2655: : 94iter [00:04, 42.78iter/s]Best score: 24.2655: : 95iter [00:04, 42.78iter/s]Best score: 24.2655: : 96iter [00:04, 43.05iter/s]Best score: 24.2655: : 96iter [00:04, 43.05iter/s]Best score: 24.2655: : 97iter [00:04, 43.05iter/s]Best score: 24.2655: : 98iter [00:04, 43.05iter/s]
[ITER 100] Best: 24.2655
[PARAMS] Current best parameters:
  fx: 532.8231
  fy: 532.8231
  px: 1018.0000
  py: 751.0000
  k1: 0.00000000
  k2: -0.00000000
  k3: 0.00000000
  k4: 0.00000000
  p1: 0.00000000
  p2: 0.00000000
  p3: 0.00000000
  p4: 0.00000000
  s1: 0.0000
  s2: 0.0000
  s3: 0.0000
  s4: 0.0000
  tilt_x: 0.0000
  tilt_y: 0.0000
  scale: 3.0000
  rotation: 0.0000
Best score: 24.2655: : 99iter [00:04, 43.05iter/s]Best score: 24.2655: : 100iter [00:04, 43.05iter/s]Best score: 24.2655: : 101iter [00:04, 40.65iter/s]Best score: 24.2655: : 101iter [00:04, 40.65iter/s]Best score: 24.2655: : 102iter [00:04, 40.65iter/s]Best score: 24.2655: : 103iter [00:04, 40.65iter/s]Best score: 24.2655: : 104iter [00:04, 40.65iter/s]Best score: 24.2655: : 105iter [00:04, 40.65iter/s]Best score: 24.2655: : 106iter [00:04, 40.96iter/s]Best score: 24.2655: : 106iter [00:04, 40.96iter/s]Best score: 24.2655: : 107iter [00:04, 40.96iter/s]Best score: 24.2655: : 108iter [00:04, 40.96iter/s]Best score: 24.2655: : 109iter [00:04, 40.96iter/s]Best score: 24.2655: : 110iter [00:04, 40.96iter/s]Best score: 24.2655: : 111iter [00:04, 41.37iter/s]Best score: 24.2655: : 111iter [00:04, 41.37iter/s]Best score: 24.2655: : 112iter [00:04, 41.37iter/s]Best score: 24.2655: : 113iter [00:04, 41.37iter/s]Best score: 24.2655: : 114iter [00:04, 41.37iter/s]Best score: 24.2655: : 115iter [00:04, 41.37iter/s]Best score: 24.2655: : 116iter [00:04, 41.86iter/s]Best score: 24.2655: : 116iter [00:04, 41.86iter/s]Best score: 24.2655: : 117iter [00:04, 41.86iter/s]Best score: 24.2655: : 118iter [00:04, 41.86iter/s]Best score: 24.2655: : 119iter [00:04, 41.86iter/s]Best score: 24.2655: : 120iter [00:04, 41.86iter/s]Best score: 24.2655: : 121iter [00:04, 42.05iter/s]Best score: 24.2655: : 121iter [00:04, 42.05iter/s]Best score: 24.2655: : 122iter [00:04, 42.05iter/s]Best score: 24.2655: : 123iter [00:04, 42.05iter/s]Best score: 24.2655: : 124iter [00:04, 42.05iter/s]Best score: 24.2655: : 125iter [00:04, 42.05iter/s]Best score: 24.2655: : 126iter [00:04, 42.47iter/s]Best score: 24.2655: : 126iter [00:04, 42.47iter/s]Best score: 24.2655: : 127iter [00:04, 42.47iter/s]Best score: 24.2655: : 128iter [00:05, 42.47iter/s]Best score: 24.2655: : 129iter [00:05, 42.47iter/s]Best score: 24.2655: : 130iter [00:05, 42.47iter/s]Best score: 24.2655: : 131iter [00:05, 42.42iter/s]Best score: 24.2655: : 131iter [00:05, 42.42iter/s]Best score: 24.2655: : 132iter [00:05, 42.42iter/s]Best score: 24.2655: : 133iter [00:05, 42.42iter/s]Best score: 24.2655: : 134iter [00:05, 42.42iter/s]Best score: 24.2655: : 135iter [00:05, 42.42iter/s]Best score: 24.2655: : 136iter [00:05, 42.64iter/s]Best score: 24.2655: : 136iter [00:05, 42.64iter/s]Best score: 24.2655: : 137iter [00:05, 42.64iter/s]Best score: 24.2655: : 138iter [00:05, 42.64iter/s]Best score: 24.2655: : 139iter [00:05, 42.64iter/s]Best score: 24.2655: : 140iter [00:05, 42.64iter/s]Best score: 24.2655: : 141iter [00:05, 42.58iter/s]Best score: 24.2655: : 141iter [00:05, 42.58iter/s]Best score: 24.2655: : 142iter [00:05, 42.58iter/s]Best score: 24.2655: : 143iter [00:05, 42.58iter/s]Best score: 24.2655: : 144iter [00:05, 42.58iter/s]Best score: 24.2655: : 145iter [00:05, 42.58iter/s]Best score: 24.2655: : 146iter [00:05, 42.72iter/s]Best score: 24.2655: : 146iter [00:05, 42.72iter/s]Best score: 24.2655: : 147iter [00:05, 42.72iter/s]Best score: 24.2655: : 148iter [00:05, 42.72iter/s]
[ITER 150] Best: 24.2655
[PARAMS] Current best parameters:
  fx: 532.8231
  fy: 532.8231
  px: 1018.0000
  py: 751.0000
  k1: 0.00000000
  k2: -0.00000000
  k3: 0.00000000
  k4: 0.00000000
  p1: 0.00000000
  p2: 0.00000000
  p3: 0.00000000
  p4: 0.00000000
  s1: 0.0000
  s2: 0.0000
  s3: 0.0000
  s4: 0.0000
  tilt_x: 0.0000
  tilt_y: 0.0000
  scale: 3.0000
  rotation: 0.0000
Best score: 24.2655: : 149iter [00:05, 42.72iter/s]Best score: 24.2655: : 150iter [00:05, 42.72iter/s]Best score: 24.2655: : 151iter [00:05, 36.25iter/s]Best score: 24.2655: : 151iter [00:05, 36.25iter/s]Best score: 24.2655: : 152iter [00:05, 36.25iter/s]Best score: 24.2655: : 153iter [00:05, 36.25iter/s]Best score: 24.2655: : 154iter [00:05, 36.25iter/s]Best score: 24.2655: : 155iter [00:05, 36.25iter/s]Best score: 24.2655: : 156iter [00:05, 37.98iter/s]Best score: 24.2655: : 156iter [00:05, 37.98iter/s]Best score: 24.2655: : 157iter [00:05, 37.98iter/s]Best score: 24.2655: : 158iter [00:05, 37.98iter/s]Best score: 24.2655: : 159iter [00:05, 37.98iter/s]Best score: 24.2655: : 160iter [00:05, 37.98iter/s]Best score: 24.2655: : 161iter [00:05, 39.15iter/s]Best score: 24.2655: : 161iter [00:05, 39.15iter/s]Best score: 24.2655: : 162iter [00:05, 39.15iter/s]Best score: 24.2655: : 163iter [00:05, 39.15iter/s]Best score: 24.2655: : 164iter [00:05, 39.15iter/s]Best score: 24.2655: : 165iter [00:05, 39.15iter/s]Best score: 24.2655: : 166iter [00:05, 40.32iter/s]Best score: 24.2655: : 166iter [00:05, 40.32iter/s]Best score: 24.2655: : 167iter [00:05, 40.32iter/s]Best score: 24.2655: : 168iter [00:06, 40.32iter/s]Best score: 24.2655: : 169iter [00:06, 40.32iter/s]Best score: 24.2655: : 170iter [00:06, 40.32iter/s]Best score: 24.2655: : 171iter [00:06, 40.98iter/s]Best score: 24.2655: : 171iter [00:06, 40.98iter/s]Best score: 24.2655: : 172iter [00:06, 40.98iter/s]Best score: 24.2655: : 173iter [00:06, 40.98iter/s]Best score: 24.2655: : 174iter [00:06, 40.98iter/s]Best score: 24.2655: : 175iter [00:06, 40.98iter/s]Best score: 24.2655: : 176iter [00:06, 41.75iter/s]Best score: 24.2655: : 176iter [00:06, 41.75iter/s]Best score: 24.2655: : 177iter [00:06, 41.75iter/s]Best score: 24.2655: : 178iter [00:06, 41.75iter/s]Best score: 24.2655: : 179iter [00:06, 41.75iter/s]Best score: 24.2655: : 180iter [00:06, 41.75iter/s]Best score: 24.2655: : 181iter [00:06, 42.05iter/s]Best score: 24.2655: : 181iter [00:06, 42.05iter/s]Best score: 24.2655: : 182iter [00:06, 42.05iter/s]Best score: 24.2655: : 183iter [00:06, 42.05iter/s]Best score: 24.2655: : 184iter [00:06, 42.05iter/s]Best score: 24.2655: : 185iter [00:06, 42.05iter/s]Best score: 24.2655: : 186iter [00:06, 42.59iter/s]Best score: 24.2655: : 186iter [00:06, 42.59iter/s]Best score: 24.2655: : 187iter [00:06, 42.59iter/s]Best score: 24.2655: : 188iter [00:06, 42.59iter/s]Best score: 24.2655: : 189iter [00:06, 42.59iter/s]Best score: 24.2655: : 190iter [00:06, 42.59iter/s]Best score: 24.2655: : 191iter [00:06, 42.71iter/s]Best score: 24.2655: : 191iter [00:06, 42.71iter/s]Best score: 24.2655: : 192iter [00:06, 42.71iter/s]Best score: 24.2655: : 193iter [00:06, 42.71iter/s]Best score: 24.2655: : 194iter [00:06, 42.71iter/s]Best score: 24.2655: : 195iter [00:06, 42.71iter/s]Best score: 24.2655: : 196iter [00:06, 43.13iter/s]Best score: 24.2655: : 196iter [00:06, 43.13iter/s]Best score: 24.2655: : 197iter [00:06, 43.13iter/s]Best score: 24.2655: : 198iter [00:06, 43.13iter/s]
[ITER 200] Best: 24.2655
[PARAMS] Current best parameters:
  fx: 532.8231
  fy: 532.8231
  px: 1018.0000
  py: 751.0000
  k1: 0.00000000
  k2: -0.00000000
  k3: 0.00000000
  k4: 0.00000000
  p1: 0.00000000
  p2: 0.00000000
  p3: 0.00000000
  p4: 0.00000000
  s1: 0.0000
  s2: 0.0000
  s3: 0.0000
  s4: 0.0000
  tilt_x: 0.0000
  tilt_y: 0.0000
  scale: 3.0000
  rotation: 0.0000
Best score: 24.2655: : 199iter [00:06, 43.13iter/s]Best score: 24.2655: : 200iter [00:06, 43.13iter/s]Best score: 24.2655: : 201iter [00:06, 36.52iter/s]Best score: 24.2655: : 201iter [00:06, 36.52iter/s]Best score: 24.2655: : 202iter [00:06, 36.52iter/s]Best score: 24.2655: : 203iter [00:06, 36.52iter/s]Best score: 24.2655: : 204iter [00:06, 36.52iter/s]Best score: 24.2655: : 205iter [00:06, 36.52iter/s]Best score: 24.2655: : 206iter [00:06, 38.45iter/s]Best score: 24.2655: : 206iter [00:06, 38.45iter/s]Best score: 24.2655: : 207iter [00:06, 38.45iter/s]Best score: 24.2655: : 208iter [00:06, 38.45iter/s]Best score: 17.7805: : 209iter [00:07, 38.45iter/s]Best score: 17.7805: : 210iter [00:07, 38.45iter/s]Best score: 17.7805: : 211iter [00:07, 39.72iter/s]Best score: 17.7805: : 211iter [00:07, 39.72iter/s]Best score: 17.7805: : 212iter [00:07, 39.72iter/s]Best score: 17.7805: : 213iter [00:07, 39.72iter/s]Best score: 17.7805: : 214iter [00:07, 39.72iter/s]Best score: 17.7805: : 215iter [00:07, 39.72iter/s]Best score: 17.7805: : 216iter [00:07, 40.86iter/s]Best score: 17.7805: : 216iter [00:07, 40.86iter/s]Best score: 17.7805: : 217iter [00:07, 40.86iter/s]Best score: 17.7805: : 218iter [00:07, 40.86iter/s]Best score: 17.7805: : 219iter [00:07, 40.86iter/s]Best score: 17.7805: : 220iter [00:07, 40.86iter/s]Best score: 17.7805: : 221iter [00:07, 41.38iter/s]Best score: 17.7805: : 221iter [00:07, 41.38iter/s]Best score: 17.7805: : 222iter [00:07, 41.38iter/s]Best score: 17.7805: : 223iter [00:07, 41.38iter/s]Best score: 17.7805: : 224iter [00:07, 41.38iter/s]Best score: 17.7805: : 225iter [00:07, 41.38iter/s]Best score: 17.7805: : 226iter [00:07, 42.16iter/s]Best score: 17.7805: : 226iter [00:07, 42.16iter/s]Best score: 17.7805: : 227iter [00:07, 42.16iter/s]Best score: 17.7805: : 228iter [00:07, 42.16iter/s]Best score: 13.2839: : 229iter [00:07, 42.16iter/s]Best score: 13.2839: : 230iter [00:07, 42.16iter/s]Best score: 13.2839: : 231iter [00:07, 42.39iter/s]Best score: 13.2839: : 231iter [00:07, 42.39iter/s]Best score: 13.2839: : 232iter [00:07, 42.39iter/s]Best score: 13.2839: : 233iter [00:07, 42.39iter/s]Best score: 13.2839: : 234iter [00:07, 42.39iter/s]Best score: 13.2839: : 235iter [00:07, 42.39iter/s]Best score: 13.2839: : 236iter [00:07, 42.77iter/s]Best score: 13.2839: : 236iter [00:07, 42.77iter/s]Best score: 13.2839: : 237iter [00:07, 42.77iter/s]Best score: 13.2839: : 238iter [00:07, 42.77iter/s]Best score: 8.6904: : 239iter [00:07, 42.77iter/s] Best score: 8.6904: : 240iter [00:07, 42.77iter/s]Best score: 8.6904: : 241iter [00:07, 42.86iter/s]Best score: 8.6904: : 241iter [00:07, 42.86iter/s]Best score: 8.6904: : 242iter [00:07, 42.86iter/s]Best score: 8.6904: : 243iter [00:07, 42.86iter/s]Best score: 8.6904: : 244iter [00:07, 42.86iter/s]Best score: 8.6904: : 245iter [00:07, 42.86iter/s]Best score: 8.6904: : 246iter [00:07, 43.17iter/s]Best score: 8.6904: : 246iter [00:07, 43.17iter/s]Best score: 8.6904: : 247iter [00:07, 43.17iter/s]Best score: 8.6904: : 248iter [00:07, 43.17iter/s]
[ITER 250] Best: 8.6904
[PARAMS] Current best parameters:
  fx: 557.4632
  fy: 556.7238
  px: 1010.8702
  py: 773.9353
  k1: -0.04423490
  k2: -0.01732026
  k3: 0.04240015
  k4: -0.01442527
  p1: 0.01279693
  p2: -0.01411811
  p3: 0.00157294
  p4: 0.00591829
  s1: -0.0161
  s2: 0.0073
  s3: 0.0069
  s4: -0.0069
  tilt_x: 0.0717
  tilt_y: 0.0209
  scale: 3.0253
  rotation: 0.1666
Best score: 8.6904: : 249iter [00:07, 43.17iter/s]Best score: 8.6904: : 250iter [00:08, 43.17iter/s]Best score: 8.6904: : 251iter [00:08, 36.36iter/s]Best score: 8.6904: : 251iter [00:08, 36.36iter/s]Best score: 8.6904: : 252iter [00:08, 36.36iter/s]Best score: 8.6904: : 253iter [00:08, 36.36iter/s]Best score: 8.6904: : 254iter [00:08, 36.36iter/s]Best score: 8.6904: : 255iter [00:08, 36.36iter/s]Best score: 8.6904: : 256iter [00:08, 38.29iter/s]Best score: 8.6904: : 256iter [00:08, 38.29iter/s]Best score: 8.6904: : 257iter [00:08, 38.29iter/s]Best score: 8.6904: : 258iter [00:08, 38.29iter/s]Best score: 8.3112: : 259iter [00:08, 38.29iter/s]Best score: 8.3112: : 260iter [00:08, 38.29iter/s]Best score: 8.3112: : 261iter [00:08, 39.52iter/s]Best score: 8.3112: : 261iter [00:08, 39.52iter/s]Best score: 8.3112: : 262iter [00:08, 39.52iter/s]Best score: 8.3112: : 263iter [00:08, 39.52iter/s]Best score: 8.3112: : 264iter [00:08, 39.52iter/s]Best score: 8.3112: : 265iter [00:08, 39.52iter/s]Best score: 8.3112: : 266iter [00:08, 40.73iter/s]Best score: 8.3112: : 266iter [00:08, 40.73iter/s]Best score: 8.3112: : 267iter [00:08, 40.73iter/s]Best score: 8.3112: : 268iter [00:08, 40.73iter/s]Best score: 6.0838: : 269iter [00:08, 40.73iter/s]Best score: 6.0838: : 270iter [00:08, 40.73iter/s]Best score: 6.0838: : 271iter [00:08, 41.32iter/s]Best score: 6.0838: : 271iter [00:08, 41.32iter/s]Best score: 6.0838: : 272iter [00:08, 41.32iter/s]Best score: 6.0838: : 273iter [00:08, 41.32iter/s]Best score: 6.0838: : 274iter [00:08, 41.32iter/s]Best score: 6.0838: : 275iter [00:08, 41.32iter/s]Best score: 6.0838: : 276iter [00:08, 41.92iter/s]Best score: 6.0838: : 276iter [00:08, 41.92iter/s]Best score: 6.0838: : 277iter [00:08, 41.92iter/s]Best score: 6.0838: : 278iter [00:08, 41.92iter/s]Best score: 2.8611: : 279iter [00:08, 41.92iter/s]Best score: 2.8611: : 280iter [00:08, 41.92iter/s]Best score: 2.8611: : 281iter [00:08, 42.28iter/s]Best score: 2.8611: : 281iter [00:08, 42.28iter/s]Best score: 2.8611: : 282iter [00:08, 42.28iter/s]Best score: 2.8611: : 283iter [00:08, 42.28iter/s]Best score: 2.8611: : 284iter [00:08, 42.28iter/s]Best score: 2.8611: : 285iter [00:08, 42.28iter/s]Best score: 2.8611: : 286iter [00:08, 42.75iter/s]Best score: 2.8611: : 286iter [00:08, 42.75iter/s]Best score: 2.8611: : 287iter [00:08, 42.75iter/s]Best score: 2.8611: : 288iter [00:08, 42.75iter/s]Best score: 2.8611: : 289iter [00:08, 42.75iter/s]Best score: 2.8611: : 290iter [00:08, 42.75iter/s]Best score: 2.8611: : 291iter [00:08, 42.72iter/s]Best score: 2.8611: : 291iter [00:08, 42.72iter/s]Best score: 2.8611: : 292iter [00:09, 42.72iter/s]Best score: 2.8611: : 293iter [00:09, 42.72iter/s]Best score: 2.8611: : 294iter [00:09, 42.72iter/s]Best score: 2.8611: : 295iter [00:09, 42.72iter/s]Best score: 2.8611: : 296iter [00:09, 42.99iter/s]Best score: 2.8611: : 296iter [00:09, 42.99iter/s]Best score: 2.8611: : 297iter [00:09, 42.99iter/s]Best score: 2.8611: : 298iter [00:09, 42.99iter/s]
[ITER 300] Best: 2.1901
[PARAMS] Current best parameters:
  fx: 569.8621
  fy: 567.4214
  px: 1022.7895
  py: 763.9154
  k1: -0.00703876
  k2: -0.03066137
  k3: 0.01485870
  k4: -0.00279357
  p1: 0.01599274
  p2: -0.00323000
  p3: 0.01392943
  p4: 0.00060693
  s1: -0.0011
  s2: -0.0022
  s3: -0.0169
  s4: -0.0047
  tilt_x: 0.0169
  tilt_y: -0.0150
  scale: 2.9259
  rotation: -0.0295
Best score: 2.1901: : 299iter [00:09, 42.99iter/s]Best score: 2.1901: : 300iter [00:09, 42.99iter/s]Best score: 2.1901: : 301iter [00:09, 36.37iter/s]Best score: 2.1901: : 301iter [00:09, 36.37iter/s]Best score: 2.1901: : 302iter [00:09, 36.37iter/s]Best score: 2.1901: : 303iter [00:09, 36.37iter/s]Best score: 2.1901: : 304iter [00:09, 36.37iter/s]Best score: 2.1901: : 305iter [00:09, 36.37iter/s]Best score: 2.1901: : 306iter [00:09, 38.38iter/s]Best score: 2.1901: : 306iter [00:09, 38.38iter/s]Best score: 2.1901: : 307iter [00:09, 38.38iter/s]Best score: 2.1901: : 308iter [00:09, 38.38iter/s]Best score: 2.1901: : 309iter [00:09, 38.38iter/s]Best score: 2.1901: : 310iter [00:09, 38.38iter/s]Best score: 2.1901: : 311iter [00:09, 39.70iter/s]Best score: 2.1901: : 311iter [00:09, 39.70iter/s]Best score: 2.1901: : 312iter [00:09, 39.70iter/s]Best score: 2.1901: : 313iter [00:09, 39.70iter/s]Best score: 2.1901: : 314iter [00:09, 39.70iter/s]Best score: 2.1901: : 315iter [00:09, 39.70iter/s]Best score: 2.1901: : 316iter [00:09, 40.89iter/s]Best score: 2.1901: : 316iter [00:09, 40.89iter/s]Best score: 2.1901: : 317iter [00:09, 40.89iter/s]Best score: 2.1901: : 318iter [00:09, 40.89iter/s]Best score: 2.1901: : 319iter [00:09, 40.89iter/s]Best score: 2.1901: : 320iter [00:09, 40.89iter/s]Best score: 2.1901: : 321iter [00:09, 41.58iter/s]Best score: 2.1901: : 321iter [00:09, 41.58iter/s]Best score: 2.1901: : 322iter [00:09, 41.58iter/s]Best score: 2.1901: : 323iter [00:09, 41.58iter/s]Best score: 2.1901: : 324iter [00:09, 41.58iter/s]Best score: 2.1901: : 325iter [00:09, 41.58iter/s]Best score: 2.1901: : 326iter [00:09, 42.29iter/s]Best score: 2.1901: : 326iter [00:09, 42.29iter/s]Best score: 2.1901: : 327iter [00:09, 42.29iter/s]Best score: 2.1901: : 328iter [00:09, 42.29iter/s]Best score: 1.8322: : 329iter [00:09, 42.29iter/s]Best score: 1.8322: : 330iter [00:09, 42.29iter/s]Best score: 1.8322: : 331iter [00:09, 42.44iter/s]Best score: 1.8322: : 331iter [00:09, 42.44iter/s]Best score: 1.8322: : 332iter [00:10, 42.44iter/s]Best score: 1.8322: : 333iter [00:10, 42.44iter/s]Best score: 1.8322: : 334iter [00:10, 42.44iter/s]Best score: 1.8322: : 335iter [00:10, 42.44iter/s]Best score: 1.8322: : 336iter [00:10, 42.97iter/s]Best score: 1.8322: : 336iter [00:10, 42.97iter/s]Best score: 1.8322: : 337iter [00:10, 42.97iter/s]Best score: 1.8322: : 338iter [00:10, 42.97iter/s]Best score: 1.6840: : 339iter [00:10, 42.97iter/s]Best score: 1.6840: : 340iter [00:10, 42.97iter/s]Best score: 1.6840: : 341iter [00:10, 43.11iter/s]Best score: 1.6840: : 341iter [00:10, 43.11iter/s]Best score: 1.6840: : 342iter [00:10, 43.11iter/s]Best score: 1.6840: : 343iter [00:10, 43.11iter/s]Best score: 1.6840: : 344iter [00:10, 43.11iter/s]Best score: 1.6840: : 345iter [00:10, 43.11iter/s]Best score: 1.6840: : 346iter [00:10, 43.21iter/s]Best score: 1.6840: : 346iter [00:10, 43.21iter/s]Best score: 1.6840: : 347iter [00:10, 43.21iter/s]Best score: 1.6840: : 348iter [00:10, 43.21iter/s]
[ITER 350] Best: 1.3424
[PARAMS] Current best parameters:
  fx: 577.6733
  fy: 576.2532
  px: 1015.6962
  py: 764.6120
  k1: 0.02197422
  k2: -0.08631288
  k3: 0.04397929
  k4: -0.00779034
  p1: 0.01483770
  p2: -0.01178290
  p3: 0.01941175
  p4: -0.00433926
  s1: -0.0124
  s2: 0.0060
  s3: -0.0115
  s4: -0.0027
  tilt_x: 0.0223
  tilt_y: 0.0032
  scale: 2.8984
  rotation: -0.0289
Best score: 1.3424: : 349iter [00:10, 43.21iter/s]Best score: 1.3424: : 350iter [00:10, 43.21iter/s]Best score: 1.3424: : 351iter [00:10, 36.32iter/s]Best score: 1.3424: : 351iter [00:10, 36.32iter/s]Best score: 1.3424: : 352iter [00:10, 36.32iter/s]Best score: 1.3424: : 353iter [00:10, 36.32iter/s]Best score: 1.3424: : 354iter [00:10, 36.32iter/s]Best score: 1.3424: : 355iter [00:10, 36.32iter/s]Best score: 1.3424: : 356iter [00:10, 38.30iter/s]Best score: 1.3424: : 356iter [00:10, 38.30iter/s]Best score: 1.3424: : 357iter [00:10, 38.30iter/s]Best score: 1.3424: : 358iter [00:10, 38.30iter/s]Best score: 1.2962: : 359iter [00:10, 38.30iter/s]Best score: 1.2962: : 360iter [00:10, 38.30iter/s]Best score: 1.2962: : 361iter [00:10, 39.55iter/s]Best score: 1.2962: : 361iter [00:10, 39.55iter/s]Best score: 1.2962: : 362iter [00:10, 39.55iter/s]Best score: 1.2962: : 363iter [00:10, 39.55iter/s]Best score: 1.2962: : 364iter [00:10, 39.55iter/s]Best score: 1.2962: : 365iter [00:10, 39.55iter/s]Best score: 1.2962: : 366iter [00:10, 40.68iter/s]Best score: 1.2962: : 366iter [00:10, 40.68iter/s]Best score: 1.2962: : 367iter [00:10, 40.68iter/s]Best score: 1.2962: : 368iter [00:10, 40.68iter/s]Best score: 1.2962: : 369iter [00:10, 40.68iter/s]Best score: 1.2962: : 370iter [00:10, 40.68iter/s]Best score: 1.2962: : 371iter [00:10, 41.36iter/s]Best score: 1.2962: : 371iter [00:10, 41.36iter/s]Best score: 1.2962: : 372iter [00:11, 41.36iter/s]Best score: 1.2962: : 373iter [00:11, 41.36iter/s]Best score: 1.2962: : 374iter [00:11, 41.36iter/s]Best score: 1.2962: : 375iter [00:11, 41.36iter/s]Best score: 1.2962: : 376iter [00:11, 34.70iter/s]Best score: 1.2962: : 376iter [00:11, 34.70iter/s]Best score: 1.2962: : 377iter [00:11, 34.70iter/s]Best score: 1.2962: : 378iter [00:11, 34.70iter/s]Best score: 1.2411: : 379iter [00:11, 34.70iter/s]Best score: 1.2411: : 380iter [00:11, 34.70iter/s]Best score: 1.2411: : 381iter [00:11, 36.80iter/s]Best score: 1.2411: : 381iter [00:11, 36.80iter/s]Best score: 1.2411: : 382iter [00:11, 36.80iter/s]Best score: 1.2411: : 383iter [00:11, 36.80iter/s]Best score: 1.2411: : 384iter [00:11, 36.80iter/s]Best score: 1.2411: : 385iter [00:11, 36.80iter/s]Best score: 1.2411: : 386iter [00:11, 38.67iter/s]Best score: 1.2411: : 386iter [00:11, 38.67iter/s]Best score: 1.2411: : 387iter [00:11, 38.67iter/s]Best score: 1.2411: : 388iter [00:11, 38.67iter/s]Best score: 1.2100: : 389iter [00:11, 38.67iter/s]Best score: 1.2100: : 390iter [00:11, 38.67iter/s]Best score: 1.2100: : 391iter [00:11, 39.98iter/s]Best score: 1.2100: : 391iter [00:11, 39.98iter/s]Best score: 1.2100: : 392iter [00:11, 39.98iter/s]Best score: 1.2100: : 393iter [00:11, 39.98iter/s]Best score: 1.2100: : 394iter [00:11, 39.98iter/s]Best score: 1.2100: : 395iter [00:11, 39.98iter/s]Best score: 1.2100: : 396iter [00:11, 41.07iter/s]Best score: 1.2100: : 396iter [00:11, 41.07iter/s]Best score: 1.2100: : 397iter [00:11, 41.07iter/s]Best score: 1.2100: : 398iter [00:11, 41.07iter/s]
[ITER 400] Best: 1.1263
[PARAMS] Current best parameters:
  fx: 568.1058
  fy: 566.8016
  px: 1016.5356
  py: 763.5825
  k1: 0.00992238
  k2: -0.05883571
  k3: 0.03066338
  k4: -0.00564363
  p1: 0.00983989
  p2: -0.00976561
  p3: 0.01633389
  p4: -0.00009539
  s1: -0.0081
  s2: -0.0005
  s3: -0.0107
  s4: -0.0038
  tilt_x: 0.0276
  tilt_y: 0.0034
  scale: 2.9352
  rotation: 0.0123
Best score: 1.1263: : 399iter [00:11, 41.07iter/s]Best score: 1.1263: : 400iter [00:11, 41.07iter/s]Best score: 1.1263: : 401iter [00:11, 35.26iter/s]Best score: 1.1263: : 401iter [00:11, 35.26iter/s]Best score: 1.1263: : 402iter [00:11, 35.26iter/s]Best score: 1.1263: : 403iter [00:11, 35.26iter/s]Best score: 1.1263: : 404iter [00:11, 35.26iter/s]Best score: 1.1263: : 405iter [00:11, 35.26iter/s]Best score: 1.1263: : 406iter [00:11, 37.41iter/s]Best score: 1.1263: : 406iter [00:11, 37.41iter/s]Best score: 1.1263: : 407iter [00:11, 37.41iter/s]Best score: 1.1263: : 408iter [00:11, 37.41iter/s]Best score: 1.0529: : 409iter [00:12, 37.41iter/s]Best score: 1.0529: : 410iter [00:12, 37.41iter/s]Best score: 1.0529: : 411iter [00:12, 38.60iter/s]Best score: 1.0529: : 411iter [00:12, 38.60iter/s]Best score: 1.0529: : 412iter [00:12, 38.60iter/s]Best score: 1.0529: : 413iter [00:12, 38.60iter/s]Best score: 1.0529: : 414iter [00:12, 38.60iter/s]Best score: 1.0529: : 415iter [00:12, 38.60iter/s]Best score: 1.0529: : 416iter [00:12, 39.94iter/s]Best score: 1.0529: : 416iter [00:12, 39.94iter/s]Best score: 1.0529: : 417iter [00:12, 39.94iter/s]Best score: 1.0529: : 418iter [00:12, 39.94iter/s]Best score: 1.0500: : 419iter [00:12, 39.94iter/s]Best score: 1.0500: : 420iter [00:12, 39.94iter/s]Best score: 1.0500: : 421iter [00:12, 40.78iter/s]Best score: 1.0500: : 421iter [00:12, 40.78iter/s]Best score: 1.0500: : 422iter [00:12, 40.78iter/s]Best score: 1.0500: : 423iter [00:12, 40.78iter/s]Best score: 1.0500: : 424iter [00:12, 40.78iter/s]Best score: 1.0500: : 425iter [00:12, 40.78iter/s]Best score: 1.0500: : 426iter [00:12, 41.67iter/s]Best score: 1.0500: : 426iter [00:12, 41.67iter/s]Best score: 1.0500: : 427iter [00:12, 41.67iter/s]Best score: 1.0500: : 428iter [00:12, 41.67iter/s]Best score: 1.0500: : 429iter [00:12, 41.67iter/s]Best score: 1.0500: : 430iter [00:12, 41.67iter/s]Best score: 1.0500: : 431iter [00:12, 42.12iter/s]Best score: 1.0500: : 431iter [00:12, 42.12iter/s]Best score: 1.0500: : 432iter [00:12, 42.12iter/s]Best score: 1.0500: : 433iter [00:12, 42.12iter/s]Best score: 1.0500: : 434iter [00:12, 42.12iter/s]Best score: 1.0500: : 435iter [00:12, 42.12iter/s]Best score: 1.0500: : 436iter [00:12, 42.55iter/s]Best score: 1.0500: : 436iter [00:12, 42.55iter/s]Best score: 1.0500: : 437iter [00:12, 42.55iter/s]Best score: 1.0500: : 438iter [00:12, 42.55iter/s]Best score: 1.0315: : 439iter [00:12, 42.55iter/s]Best score: 1.0315: : 440iter [00:12, 42.55iter/s]Best score: 1.0315: : 441iter [00:12, 42.70iter/s]Best score: 1.0315: : 441iter [00:12, 42.70iter/s]Best score: 1.0315: : 442iter [00:12, 42.70iter/s]Best score: 1.0315: : 443iter [00:12, 42.70iter/s]Best score: 1.0315: : 444iter [00:12, 42.70iter/s]Best score: 1.0315: : 445iter [00:12, 42.70iter/s]Best score: 1.0315: : 446iter [00:12, 42.91iter/s]Best score: 1.0315: : 446iter [00:12, 42.91iter/s]Best score: 1.0315: : 447iter [00:12, 42.91iter/s]Best score: 1.0315: : 448iter [00:12, 42.91iter/s]
[ITER 450] Best: 0.9485
[PARAMS] Current best parameters:
  fx: 567.8356
  fy: 566.6838
  px: 1016.1413
  py: 761.5680
  k1: 0.00704769
  k2: -0.05376277
  k3: 0.02888087
  k4: -0.00564039
  p1: 0.00916755
  p2: -0.00756018
  p3: 0.01437232
  p4: -0.00269770
  s1: -0.0109
  s2: 0.0048
  s3: -0.0099
  s4: -0.0002
  tilt_x: 0.0166
  tilt_y: 0.0109
  scale: 2.9251
  rotation: -0.0113
Best score: 0.9485: : 449iter [00:12, 42.91iter/s]Best score: 0.9485: : 450iter [00:13, 42.91iter/s]Best score: 0.9485: : 451iter [00:13, 36.37iter/s]Best score: 0.9485: : 451iter [00:13, 36.37iter/s]Best score: 0.9485: : 452iter [00:13, 36.37iter/s]Best score: 0.9485: : 453iter [00:13, 36.37iter/s]Best score: 0.9485: : 454iter [00:13, 36.37iter/s]Best score: 0.9485: : 455iter [00:13, 36.37iter/s]Best score: 0.9485: : 456iter [00:13, 38.29iter/s]Best score: 0.9485: : 456iter [00:13, 38.29iter/s]Best score: 0.9485: : 457iter [00:13, 38.29iter/s]Best score: 0.9485: : 458iter [00:13, 38.29iter/s]Best score: 0.9485: : 459iter [00:13, 38.29iter/s]Best score: 0.9485: : 460iter [00:13, 38.29iter/s]Best score: 0.9485: : 461iter [00:13, 39.58iter/s]Best score: 0.9485: : 461iter [00:13, 39.58iter/s]Best score: 0.9485: : 462iter [00:13, 39.58iter/s]Best score: 0.9485: : 463iter [00:13, 39.58iter/s]Best score: 0.9485: : 464iter [00:13, 39.58iter/s]Best score: 0.9485: : 465iter [00:13, 39.58iter/s]Best score: 0.9485: : 466iter [00:13, 40.87iter/s]Best score: 0.9485: : 466iter [00:13, 40.87iter/s]Best score: 0.9485: : 467iter [00:13, 40.87iter/s]Best score: 0.9485: : 468iter [00:13, 40.87iter/s]Best score: 0.9309: : 469iter [00:13, 40.87iter/s]Best score: 0.9309: : 470iter [00:13, 40.87iter/s]Best score: 0.9309: : 471iter [00:13, 41.36iter/s]Best score: 0.9309: : 471iter [00:13, 41.36iter/s]Best score: 0.9309: : 472iter [00:13, 41.36iter/s]Best score: 0.9309: : 473iter [00:13, 41.36iter/s]Best score: 0.9309: : 474iter [00:13, 41.36iter/s]Best score: 0.9309: : 475iter [00:13, 41.36iter/s]Best score: 0.9309: : 476iter [00:13, 41.94iter/s]Best score: 0.9309: : 476iter [00:13, 41.94iter/s]Best score: 0.9309: : 477iter [00:13, 41.94iter/s]Best score: 0.9309: : 478iter [00:13, 41.94iter/s]Best score: 0.8955: : 479iter [00:13, 41.94iter/s]Best score: 0.8955: : 480iter [00:13, 41.94iter/s]Best score: 0.8955: : 481iter [00:13, 42.18iter/s]Best score: 0.8955: : 481iter [00:13, 42.18iter/s]Best score: 0.8955: : 482iter [00:13, 42.18iter/s]Best score: 0.8955: : 483iter [00:13, 42.18iter/s]Best score: 0.8955: : 484iter [00:13, 42.18iter/s]Best score: 0.8955: : 485iter [00:13, 42.18iter/s]Best score: 0.8955: : 486iter [00:13, 42.52iter/s]Best score: 0.8955: : 486iter [00:13, 42.52iter/s]Best score: 0.8955: : 487iter [00:13, 42.52iter/s]Best score: 0.8955: : 488iter [00:13, 42.52iter/s]Best score: 0.8831: : 489iter [00:13, 42.52iter/s]Best score: 0.8831: : 490iter [00:13, 42.52iter/s]Best score: 0.8831: : 491iter [00:13, 42.64iter/s]Best score: 0.8831: : 491iter [00:13, 42.64iter/s]Best score: 0.8831: : 492iter [00:13, 42.64iter/s]Best score: 0.8831: : 493iter [00:14, 42.64iter/s]Best score: 0.8831: : 494iter [00:14, 42.64iter/s]Best score: 0.8831: : 495iter [00:14, 42.64iter/s]Best score: 0.8831: : 496iter [00:14, 42.95iter/s]Best score: 0.8831: : 496iter [00:14, 42.95iter/s]Best score: 0.8831: : 497iter [00:14, 42.95iter/s]Best score: 0.8831: : 498iter [00:14, 42.95iter/s]
[ITER 500] Best: 0.8625
[PARAMS] Current best parameters:
  fx: 564.6802
  fy: 563.9687
  px: 1014.0182
  py: 755.5908
  k1: 0.02128311
  k2: -0.06266123
  k3: 0.02783579
  k4: -0.00424389
  p1: -0.00101489
  p2: -0.01005263
  p3: 0.01613773
  p4: -0.00349082
  s1: -0.0139
  s2: 0.0059
  s3: -0.0076
  s4: 0.0014
  tilt_x: 0.0058
  tilt_y: 0.0172
  scale: 2.9118
  rotation: -0.0111
Best score: 0.8625: : 499iter [00:14, 42.95iter/s]Best score: 0.8625: : 500iter [00:14, 42.95iter/s]Best score: 0.8625: : 501iter [00:14, 36.36iter/s]Best score: 0.8625: : 501iter [00:14, 36.36iter/s]Best score: 0.8625: : 502iter [00:14, 36.36iter/s]Best score: 0.8625: : 503iter [00:14, 36.36iter/s]Best score: 0.8625: : 504iter [00:14, 36.36iter/s]Best score: 0.8625: : 505iter [00:14, 36.36iter/s]Best score: 0.8625: : 506iter [00:14, 38.38iter/s]Best score: 0.8625: : 506iter [00:14, 38.38iter/s]Best score: 0.8625: : 507iter [00:14, 38.38iter/s]Best score: 0.8625: : 508iter [00:14, 38.38iter/s]Best score: 0.8495: : 509iter [00:14, 38.38iter/s]Best score: 0.8495: : 510iter [00:14, 38.38iter/s]Best score: 0.8495: : 511iter [00:14, 39.59iter/s]Best score: 0.8495: : 511iter [00:14, 39.59iter/s]Best score: 0.8495: : 512iter [00:14, 39.59iter/s]Best score: 0.8495: : 513iter [00:14, 39.59iter/s]Best score: 0.8495: : 514iter [00:14, 39.59iter/s]Best score: 0.8495: : 515iter [00:14, 39.59iter/s]Best score: 0.8495: : 516iter [00:14, 40.78iter/s]Best score: 0.8495: : 516iter [00:14, 40.78iter/s]Best score: 0.8495: : 517iter [00:14, 40.78iter/s]Best score: 0.8495: : 518iter [00:14, 40.78iter/s]Best score: 0.8167: : 519iter [00:14, 40.78iter/s]Best score: 0.8167: : 520iter [00:14, 40.78iter/s]Best score: 0.8167: : 521iter [00:14, 41.41iter/s]Best score: 0.8167: : 521iter [00:14, 41.41iter/s]Best score: 0.8167: : 522iter [00:14, 41.41iter/s]Best score: 0.8167: : 523iter [00:14, 41.41iter/s]Best score: 0.8167: : 524iter [00:14, 41.41iter/s]Best score: 0.8167: : 525iter [00:14, 41.41iter/s]Best score: 0.8167: : 526iter [00:14, 42.00iter/s]Best score: 0.8167: : 526iter [00:14, 42.00iter/s]Best score: 0.8167: : 527iter [00:14, 42.00iter/s]Best score: 0.8167: : 528iter [00:14, 42.00iter/s]Best score: 0.8167: : 529iter [00:14, 42.00iter/s]Best score: 0.8167: : 530iter [00:14, 42.00iter/s]Best score: 0.8167: : 531iter [00:14, 42.21iter/s]Best score: 0.8167: : 531iter [00:14, 42.21iter/s]Best score: 0.8167: : 532iter [00:14, 42.21iter/s]Best score: 0.8167: : 533iter [00:15, 42.21iter/s]Best score: 0.8167: : 534iter [00:15, 42.21iter/s]Best score: 0.8167: : 535iter [00:15, 42.21iter/s]Best score: 0.8167: : 536iter [00:15, 42.61iter/s]Best score: 0.8167: : 536iter [00:15, 42.61iter/s]Best score: 0.8167: : 537iter [00:15, 42.61iter/s]Best score: 0.8167: : 538iter [00:15, 42.61iter/s]Best score: 0.8034: : 539iter [00:15, 42.61iter/s]Best score: 0.8034: : 540iter [00:15, 42.61iter/s]Best score: 0.8034: : 541iter [00:15, 42.58iter/s]Best score: 0.8034: : 541iter [00:15, 42.58iter/s]Best score: 0.8034: : 542iter [00:15, 42.58iter/s]Best score: 0.8034: : 543iter [00:15, 42.58iter/s]Best score: 0.8034: : 544iter [00:15, 42.58iter/s]Best score: 0.8034: : 545iter [00:15, 42.58iter/s]Best score: 0.8034: : 546iter [00:15, 42.80iter/s]Best score: 0.8034: : 546iter [00:15, 42.80iter/s]Best score: 0.8034: : 547iter [00:15, 42.80iter/s]Best score: 0.8034: : 548iter [00:15, 42.80iter/s]
[ITER 550] Best: 0.7878
[PARAMS] Current best parameters:
  fx: 554.6173
  fy: 554.0535
  px: 1018.7701
  py: 748.6450
  k1: -0.01084284
  k2: 0.00129407
  k3: -0.00835269
  k4: 0.00277406
  p1: -0.00945452
  p2: -0.00235356
  p3: 0.00906136
  p4: 0.00528805
  s1: -0.0092
  s2: -0.0033
  s3: -0.0012
  s4: -0.0052
  tilt_x: -0.0145
  tilt_y: 0.0063
  scale: 2.9646
  rotation: -0.0843
Best score: 0.7878: : 549iter [00:15, 42.80iter/s]Best score: 0.7878: : 550iter [00:15, 42.80iter/s]Best score: 0.7878: : 551iter [00:15, 36.22iter/s]Best score: 0.7878: : 551iter [00:15, 36.22iter/s]Best score: 0.7878: : 552iter [00:15, 36.22iter/s]Best score: 0.7878: : 553iter [00:15, 36.22iter/s]Best score: 0.7878: : 554iter [00:15, 36.22iter/s]Best score: 0.7878: : 555iter [00:15, 36.22iter/s]Best score: 0.7878: : 556iter [00:15, 38.32iter/s]Best score: 0.7878: : 556iter [00:15, 38.32iter/s]Best score: 0.7878: : 557iter [00:15, 38.32iter/s]Best score: 0.7878: : 558iter [00:15, 38.32iter/s]Best score: 0.7878: : 559iter [00:15, 38.32iter/s]Best score: 0.7878: : 560iter [00:15, 38.32iter/s]Best score: 0.7878: : 561iter [00:15, 39.60iter/s]Best score: 0.7878: : 561iter [00:15, 39.60iter/s]Best score: 0.7878: : 562iter [00:15, 39.60iter/s]Best score: 0.7878: : 563iter [00:15, 39.60iter/s]Best score: 0.7878: : 564iter [00:15, 39.60iter/s]Best score: 0.7878: : 565iter [00:15, 39.60iter/s]Best score: 0.7878: : 566iter [00:15, 40.76iter/s]Best score: 0.7878: : 566iter [00:15, 40.76iter/s]Best score: 0.7878: : 567iter [00:15, 40.76iter/s]Best score: 0.7878: : 568iter [00:15, 40.76iter/s]Best score: 0.7806: : 569iter [00:15, 40.76iter/s]Best score: 0.7806: : 570iter [00:15, 40.76iter/s]Best score: 0.7806: : 571iter [00:15, 41.40iter/s]Best score: 0.7806: : 571iter [00:15, 41.40iter/s]Best score: 0.7806: : 572iter [00:15, 41.40iter/s]Best score: 0.7806: : 573iter [00:16, 41.40iter/s]Best score: 0.7806: : 574iter [00:16, 41.40iter/s]Best score: 0.7806: : 575iter [00:16, 41.40iter/s]Best score: 0.7806: : 576iter [00:16, 42.18iter/s]Best score: 0.7806: : 576iter [00:16, 42.18iter/s]Best score: 0.7806: : 577iter [00:16, 42.18iter/s]Best score: 0.7806: : 578iter [00:16, 42.18iter/s]Best score: 0.7749: : 579iter [00:16, 42.18iter/s]Best score: 0.7749: : 580iter [00:16, 42.18iter/s]Best score: 0.7749: : 581iter [00:16, 42.45iter/s]Best score: 0.7749: : 581iter [00:16, 42.45iter/s]Best score: 0.7749: : 582iter [00:16, 42.45iter/s]Best score: 0.7749: : 583iter [00:16, 42.45iter/s]Best score: 0.7749: : 584iter [00:16, 42.45iter/s]Best score: 0.7749: : 585iter [00:16, 42.45iter/s]Best score: 0.7749: : 586iter [00:16, 42.79iter/s]Best score: 0.7749: : 586iter [00:16, 42.79iter/s]Best score: 0.7749: : 587iter [00:16, 42.79iter/s]Best score: 0.7749: : 588iter [00:16, 42.79iter/s]Best score: 0.7666: : 589iter [00:16, 42.79iter/s]Best score: 0.7666: : 590iter [00:16, 42.79iter/s]Best score: 0.7666: : 591iter [00:16, 42.94iter/s]Best score: 0.7666: : 591iter [00:16, 42.94iter/s]Best score: 0.7666: : 592iter [00:16, 42.94iter/s]Best score: 0.7666: : 593iter [00:16, 42.94iter/s]Best score: 0.7666: : 594iter [00:16, 42.94iter/s]Best score: 0.7666: : 595iter [00:16, 42.94iter/s]Best score: 0.7666: : 596iter [00:16, 43.08iter/s]Best score: 0.7666: : 596iter [00:16, 43.08iter/s]Best score: 0.7666: : 597iter [00:16, 43.08iter/s]Best score: 0.7666: : 598iter [00:16, 43.08iter/s]
[ITER 600] Best: 0.7565
[PARAMS] Current best parameters:
  fx: 561.9345
  fy: 561.3023
  px: 1018.1490
  py: 752.6724
  k1: 0.00313686
  k2: -0.03670680
  k3: 0.01656595
  k4: -0.00269005
  p1: -0.00493063
  p2: -0.01034412
  p3: 0.00306293
  p4: 0.00146494
  s1: 0.0024
  s2: 0.0015
  s3: 0.0100
  s4: -0.0052
  tilt_x: -0.0025
  tilt_y: -0.0064
  scale: 2.9441
  rotation: -0.0343
Best score: 0.7565: : 599iter [00:16, 43.08iter/s]Best score: 0.7565: : 600iter [00:16, 43.08iter/s]Best score: 0.7565: : 601iter [00:16, 36.24iter/s]Best score: 0.7565: : 601iter [00:16, 36.24iter/s]Best score: 0.7565: : 602iter [00:16, 36.24iter/s]Best score: 0.7565: : 603iter [00:16, 36.24iter/s]Best score: 0.7565: : 604iter [00:16, 36.24iter/s]Best score: 0.7565: : 605iter [00:16, 36.24iter/s]Best score: 0.7565: : 606iter [00:16, 38.14iter/s]Best score: 0.7565: : 606iter [00:16, 38.14iter/s]Best score: 0.7565: : 607iter [00:16, 38.14iter/s]Best score: 0.7565: : 608iter [00:16, 38.14iter/s]Best score: 0.7565: : 609iter [00:16, 38.14iter/s]Best score: 0.7565: : 610iter [00:16, 38.14iter/s]Best score: 0.7565: : 611iter [00:16, 39.48iter/s]Best score: 0.7565: : 611iter [00:16, 39.48iter/s]Best score: 0.7565: : 612iter [00:16, 39.48iter/s]Best score: 0.7565: : 613iter [00:17, 39.48iter/s]Best score: 0.7565: : 614iter [00:17, 39.48iter/s]Best score: 0.7565: : 615iter [00:17, 39.48iter/s]Best score: 0.7565: : 616iter [00:17, 40.69iter/s]Best score: 0.7565: : 616iter [00:17, 40.69iter/s]Best score: 0.7565: : 617iter [00:17, 40.69iter/s]Best score: 0.7565: : 618iter [00:17, 40.69iter/s]Best score: 0.7519: : 619iter [00:17, 40.69iter/s]Best score: 0.7519: : 620iter [00:17, 40.69iter/s]Best score: 0.7519: : 621iter [00:17, 41.39iter/s]Best score: 0.7519: : 621iter [00:17, 41.39iter/s]Best score: 0.7519: : 622iter [00:17, 41.39iter/s]Best score: 0.7519: : 623iter [00:17, 41.39iter/s]Best score: 0.7519: : 624iter [00:17, 41.39iter/s]Best score: 0.7519: : 625iter [00:17, 41.39iter/s]Best score: 0.7519: : 626iter [00:17, 42.07iter/s]Best score: 0.7519: : 626iter [00:17, 42.07iter/s]Best score: 0.7519: : 627iter [00:17, 42.07iter/s]Best score: 0.7519: : 628iter [00:17, 42.07iter/s]Best score: 0.7441: : 629iter [00:17, 42.07iter/s]Best score: 0.7441: : 630iter [00:17, 42.07iter/s]Best score: 0.7441: : 631iter [00:17, 42.29iter/s]Best score: 0.7441: : 631iter [00:17, 42.29iter/s]Best score: 0.7441: : 632iter [00:17, 42.29iter/s]Best score: 0.7441: : 633iter [00:17, 42.29iter/s]Best score: 0.7441: : 634iter [00:17, 42.29iter/s]Best score: 0.7441: : 635iter [00:17, 42.29iter/s]Best score: 0.7441: : 636iter [00:17, 42.71iter/s]Best score: 0.7441: : 636iter [00:17, 42.71iter/s]Best score: 0.7441: : 637iter [00:17, 42.71iter/s]Best score: 0.7441: : 638iter [00:17, 42.71iter/s]Best score: 0.7441: : 639iter [00:17, 42.71iter/s]Best score: 0.7441: : 640iter [00:17, 42.71iter/s]Best score: 0.7441: : 641iter [00:17, 42.69iter/s]Best score: 0.7441: : 641iter [00:17, 42.69iter/s]Best score: 0.7441: : 642iter [00:17, 42.69iter/s]Best score: 0.7441: : 643iter [00:17, 42.69iter/s]Best score: 0.7441: : 644iter [00:17, 42.69iter/s]Best score: 0.7441: : 645iter [00:17, 42.69iter/s]Best score: 0.7441: : 646iter [00:17, 43.06iter/s]Best score: 0.7441: : 646iter [00:17, 43.06iter/s]Best score: 0.7441: : 647iter [00:17, 43.06iter/s]Best score: 0.7441: : 648iter [00:17, 43.06iter/s]
[ITER 650] Best: 0.7441
[PARAMS] Current best parameters:
  fx: 561.2296
  fy: 560.6214
  px: 1018.7503
  py: 751.9243
  k1: -0.00528716
  k2: -0.02625879
  k3: 0.01257910
  k4: -0.00223168
  p1: -0.00467027
  p2: -0.00922926
  p3: -0.00182706
  p4: 0.00219157
  s1: 0.0073
  s2: 0.0004
  s3: 0.0126
  s4: -0.0050
  tilt_x: -0.0069
  tilt_y: -0.0077
  scale: 2.9592
  rotation: -0.0319
Best score: 0.7441: : 649iter [00:17, 43.06iter/s]Best score: 0.7441: : 650iter [00:17, 43.06iter/s]Best score: 0.7441: : 651iter [00:17, 36.35iter/s]Best score: 0.7441: : 651iter [00:17, 36.35iter/s]Best score: 0.7441: : 652iter [00:17, 36.35iter/s]Best score: 0.7441: : 653iter [00:17, 36.35iter/s]Best score: 0.7441: : 654iter [00:18, 36.35iter/s]Best score: 0.7441: : 655iter [00:18, 36.35iter/s]Best score: 0.7441: : 656iter [00:18, 38.30iter/s]Best score: 0.7441: : 656iter [00:18, 38.30iter/s]Best score: 0.7441: : 657iter [00:18, 38.30iter/s]Best score: 0.7441: : 658iter [00:18, 38.30iter/s]Best score: 0.7441: : 659iter [00:18, 38.30iter/s]Best score: 0.7441: : 660iter [00:18, 38.30iter/s]Best score: 0.7441: : 661iter [00:18, 39.63iter/s]Best score: 0.7441: : 661iter [00:18, 39.63iter/s]Best score: 0.7441: : 662iter [00:18, 39.63iter/s]Best score: 0.7441: : 663iter [00:18, 39.63iter/s]Best score: 0.7441: : 664iter [00:18, 39.63iter/s]Best score: 0.7441: : 665iter [00:18, 39.63iter/s]Best score: 0.7441: : 666iter [00:18, 40.89iter/s]Best score: 0.7441: : 666iter [00:18, 40.89iter/s]Best score: 0.7441: : 667iter [00:18, 40.89iter/s]Best score: 0.7441: : 668iter [00:18, 40.89iter/s]Best score: 0.7391: : 669iter [00:18, 40.89iter/s]Best score: 0.7391: : 670iter [00:18, 40.89iter/s]Best score: 0.7391: : 671iter [00:18, 41.67iter/s]Best score: 0.7391: : 671iter [00:18, 41.67iter/s]Best score: 0.7391: : 672iter [00:18, 41.67iter/s]Best score: 0.7391: : 673iter [00:18, 41.67iter/s]Best score: 0.7391: : 674iter [00:18, 41.67iter/s]Best score: 0.7391: : 675iter [00:18, 41.67iter/s]Best score: 0.7391: : 676iter [00:18, 42.43iter/s]Best score: 0.7391: : 676iter [00:18, 42.43iter/s]Best score: 0.7391: : 677iter [00:18, 42.43iter/s]Best score: 0.7391: : 678iter [00:18, 42.43iter/s]Best score: 0.7386: : 679iter [00:18, 42.43iter/s]Best score: 0.7386: : 680iter [00:18, 42.43iter/s]Best score: 0.7386: : 681iter [00:18, 42.57iter/s]Best score: 0.7386: : 681iter [00:18, 42.57iter/s]Best score: 0.7386: : 682iter [00:18, 42.57iter/s]Best score: 0.7386: : 683iter [00:18, 42.57iter/s]Best score: 0.7386: : 684iter [00:18, 42.57iter/s]Best score: 0.7386: : 685iter [00:18, 42.57iter/s]Best score: 0.7386: : 686iter [00:18, 42.98iter/s]Best score: 0.7386: : 686iter [00:18, 42.98iter/s]Best score: 0.7386: : 687iter [00:18, 42.98iter/s]Best score: 0.7386: : 688iter [00:18, 42.98iter/s]Best score: 0.7272: : 689iter [00:18, 42.98iter/s]Best score: 0.7272: : 690iter [00:18, 42.98iter/s]Best score: 0.7272: : 691iter [00:18, 35.27iter/s]Best score: 0.7272: : 691iter [00:18, 35.27iter/s]Best score: 0.7272: : 692iter [00:18, 35.27iter/s]Best score: 0.7272: : 693iter [00:18, 35.27iter/s]Best score: 0.7272: : 694iter [00:19, 35.27iter/s]Best score: 0.7272: : 695iter [00:19, 35.27iter/s]Best score: 0.7272: : 696iter [00:19, 37.44iter/s]Best score: 0.7272: : 696iter [00:19, 37.44iter/s]Best score: 0.7272: : 697iter [00:19, 37.44iter/s]Best score: 0.7272: : 698iter [00:19, 37.44iter/s]
[ITER 700] Best: 0.7272
[PARAMS] Current best parameters:
  fx: 560.2788
  fy: 559.6461
  px: 1019.7203
  py: 750.9362
  k1: -0.01938497
  k2: -0.00828754
  k3: 0.00507111
  k4: -0.00117451
  p1: -0.00368316
  p2: -0.00648466
  p3: -0.00608414
  p4: 0.00307089
  s1: 0.0107
  s2: -0.0012
  s3: 0.0151
  s4: -0.0061
  tilt_x: -0.0140
  tilt_y: -0.0072
  scale: 2.9844
  rotation: -0.0329
Best score: 0.7272: : 699iter [00:19, 37.44iter/s]Best score: 0.7272: : 700iter [00:19, 37.44iter/s]Best score: 0.7272: : 701iter [00:19, 33.43iter/s]Best score: 0.7272: : 701iter [00:19, 33.43iter/s]Best score: 0.7272: : 702iter [00:19, 33.43iter/s]Best score: 0.7272: : 703iter [00:19, 33.43iter/s]Best score: 0.7272: : 704iter [00:19, 33.43iter/s]Best score: 0.7272: : 705iter [00:19, 33.43iter/s]Best score: 0.7272: : 706iter [00:19, 36.00iter/s]Best score: 0.7272: : 706iter [00:19, 36.00iter/s]Best score: 0.7272: : 707iter [00:19, 36.00iter/s]Best score: 0.7272: : 708iter [00:19, 36.00iter/s]Best score: 0.7221: : 709iter [00:19, 36.00iter/s]Best score: 0.7221: : 710iter [00:19, 36.00iter/s]Best score: 0.7221: : 711iter [00:19, 37.86iter/s]Best score: 0.7221: : 711iter [00:19, 37.86iter/s]Best score: 0.7221: : 712iter [00:19, 37.86iter/s]Best score: 0.7221: : 713iter [00:19, 37.86iter/s]Best score: 0.7221: : 714iter [00:19, 37.86iter/s]Best score: 0.7221: : 715iter [00:19, 37.86iter/s]Best score: 0.7221: : 716iter [00:19, 39.52iter/s]Best score: 0.7221: : 716iter [00:19, 39.52iter/s]Best score: 0.7221: : 717iter [00:19, 39.52iter/s]Best score: 0.7221: : 718iter [00:19, 39.52iter/s]Best score: 0.7221: : 719iter [00:19, 39.52iter/s]Best score: 0.7221: : 720iter [00:19, 39.52iter/s]Best score: 0.7221: : 721iter [00:19, 40.55iter/s]Best score: 0.7221: : 721iter [00:19, 40.55iter/s]Best score: 0.7221: : 722iter [00:19, 40.55iter/s]Best score: 0.7221: : 723iter [00:19, 40.55iter/s]Best score: 0.7221: : 724iter [00:19, 40.55iter/s]Best score: 0.7221: : 725iter [00:19, 40.55iter/s]Best score: 0.7221: : 726iter [00:19, 41.46iter/s]Best score: 0.7221: : 726iter [00:19, 41.46iter/s]Best score: 0.7221: : 727iter [00:19, 41.46iter/s]Best score: 0.7221: : 728iter [00:19, 41.46iter/s]Best score: 0.7221: : 729iter [00:19, 41.46iter/s]Best score: 0.7221: : 730iter [00:19, 41.46iter/s]Best score: 0.7221: : 731iter [00:19, 41.96iter/s]Best score: 0.7221: : 731iter [00:19, 41.96iter/s]Best score: 0.7221: : 732iter [00:19, 41.96iter/s]Best score: 0.7221: : 733iter [00:19, 41.96iter/s]Best score: 0.7221: : 734iter [00:20, 41.96iter/s]Best score: 0.7221: : 735iter [00:20, 41.96iter/s]Best score: 0.7221: : 736iter [00:20, 42.62iter/s]Best score: 0.7221: : 736iter [00:20, 42.62iter/s]Best score: 0.7221: : 737iter [00:20, 42.62iter/s]Best score: 0.7221: : 738iter [00:20, 42.62iter/s]Best score: 0.7214: : 739iter [00:20, 42.62iter/s]Best score: 0.7214: : 740iter [00:20, 42.62iter/s]Best score: 0.7214: : 741iter [00:20, 42.62iter/s]Best score: 0.7214: : 741iter [00:20, 42.62iter/s]Best score: 0.7214: : 742iter [00:20, 42.62iter/s]Best score: 0.7214: : 743iter [00:20, 42.62iter/s]Best score: 0.7214: : 744iter [00:20, 42.62iter/s]Best score: 0.7214: : 745iter [00:20, 42.62iter/s]Best score: 0.7214: : 746iter [00:20, 42.99iter/s]Best score: 0.7214: : 746iter [00:20, 42.99iter/s]Best score: 0.7214: : 747iter [00:20, 42.99iter/s]Best score: 0.7214: : 748iter [00:20, 42.99iter/s]
[ITER 750] Best: 0.7175
[PARAMS] Current best parameters:
  fx: 559.3522
  fy: 558.7146
  px: 1018.5959
  py: 749.5702
  k1: -0.01741231
  k2: -0.00917303
  k3: 0.00498810
  k4: -0.00105765
  p1: -0.00569161
  p2: -0.00718894
  p3: -0.00526114
  p4: 0.00347435
  s1: 0.0090
  s2: -0.0013
  s3: 0.0145
  s4: -0.0062
  tilt_x: -0.0170
  tilt_y: -0.0025
  scale: 2.9838
  rotation: -0.0388
Best score: 0.7175: : 749iter [00:20, 42.99iter/s]Best score: 0.7175: : 750iter [00:20, 42.99iter/s]Best score: 0.7175: : 751iter [00:20, 36.32iter/s]Best score: 0.7175: : 751iter [00:20, 36.32iter/s]Best score: 0.7175: : 752iter [00:20, 36.32iter/s]Best score: 0.7175: : 753iter [00:20, 36.32iter/s]Best score: 0.7175: : 754iter [00:20, 36.32iter/s]Best score: 0.7175: : 755iter [00:20, 36.32iter/s]Best score: 0.7175: : 756iter [00:20, 38.31iter/s]Best score: 0.7175: : 756iter [00:20, 38.31iter/s]Best score: 0.7175: : 757iter [00:20, 38.31iter/s]Best score: 0.7175: : 758iter [00:20, 38.31iter/s]Best score: 0.7175: : 759iter [00:20, 38.31iter/s]Best score: 0.7175: : 760iter [00:20, 38.31iter/s]Best score: 0.7175: : 761iter [00:20, 39.54iter/s]Best score: 0.7175: : 761iter [00:20, 39.54iter/s]Best score: 0.7175: : 762iter [00:20, 39.54iter/s]Best score: 0.7175: : 763iter [00:20, 39.54iter/s]Best score: 0.7175: : 764iter [00:20, 39.54iter/s]Best score: 0.7175: : 765iter [00:20, 39.54iter/s]Best score: 0.7175: : 766iter [00:20, 40.67iter/s]Best score: 0.7175: : 766iter [00:20, 40.67iter/s]Best score: 0.7175: : 767iter [00:20, 40.67iter/s]Best score: 0.7175: : 768iter [00:20, 40.67iter/s]Best score: 0.7163: : 769iter [00:20, 40.67iter/s]Best score: 0.7163: : 770iter [00:20, 40.67iter/s]Best score: 0.7163: : 771iter [00:20, 41.31iter/s]Best score: 0.7163: : 771iter [00:20, 41.31iter/s]Best score: 0.7163: : 772iter [00:20, 41.31iter/s]Best score: 0.7163: : 773iter [00:20, 41.31iter/s]Best score: 0.7163: : 774iter [00:21, 41.31iter/s]Best score: 0.7163: : 775iter [00:21, 41.31iter/s]Best score: 0.7163: : 776iter [00:21, 41.96iter/s]Best score: 0.7163: : 776iter [00:21, 41.96iter/s]Best score: 0.7163: : 777iter [00:21, 41.96iter/s]Best score: 0.7163: : 778iter [00:21, 41.96iter/s]Best score: 0.7161: : 779iter [00:21, 41.96iter/s]Best score: 0.7161: : 780iter [00:21, 41.96iter/s]Best score: 0.7161: : 781iter [00:21, 42.24iter/s]Best score: 0.7161: : 781iter [00:21, 42.24iter/s]Best score: 0.7161: : 782iter [00:21, 42.24iter/s]Best score: 0.7161: : 783iter [00:21, 42.24iter/s]Best score: 0.7161: : 784iter [00:21, 42.24iter/s]Best score: 0.7161: : 785iter [00:21, 42.24iter/s]Best score: 0.7161: : 786iter [00:21, 42.67iter/s]Best score: 0.7161: : 786iter [00:21, 42.67iter/s]Best score: 0.7161: : 787iter [00:21, 42.67iter/s]Best score: 0.7161: : 788iter [00:21, 42.67iter/s]Best score: 0.7151: : 789iter [00:21, 42.67iter/s]Best score: 0.7151: : 790iter [00:21, 42.67iter/s]Best score: 0.7151: : 791iter [00:21, 42.71iter/s]Best score: 0.7151: : 791iter [00:21, 42.71iter/s]Best score: 0.7151: : 792iter [00:21, 42.71iter/s]Best score: 0.7151: : 793iter [00:21, 42.71iter/s]Best score: 0.7151: : 794iter [00:21, 42.71iter/s]Best score: 0.7151: : 795iter [00:21, 42.71iter/s]Best score: 0.7151: : 796iter [00:21, 43.04iter/s]Best score: 0.7151: : 796iter [00:21, 43.04iter/s]Best score: 0.7151: : 797iter [00:21, 43.04iter/s]Best score: 0.7151: : 798iter [00:21, 43.04iter/s]
[ITER 800] Best: 0.7140
[PARAMS] Current best parameters:
  fx: 556.8252
  fy: 556.1398
  px: 1019.5805
  py: 749.0445
  k1: -0.02901982
  k2: 0.01173576
  k3: -0.00664111
  k4: 0.00122785
  p1: -0.00725722
  p2: -0.00478424
  p3: -0.00462336
  p4: 0.00511296
  s1: 0.0074
  s2: -0.0034
  s3: 0.0141
  s4: -0.0074
  tilt_x: -0.0163
  tilt_y: -0.0030
  scale: 3.0018
  rotation: -0.0381
Best score: 0.7140: : 799iter [00:21, 43.04iter/s]
[Periodic outlier @ iter 700] Removing 1000 frame 13 (score=3.23, threshold=2.78)
  Remaining frames: 17
Best score: 0.7140: : 800iter [00:21, 43.04iter/s]Best score: 0.7140: : 801iter [00:21, 33.86iter/s]Best score: 0.7140: : 801iter [00:21, 33.86iter/s]Best score: 0.7140: : 802iter [00:21, 33.86iter/s]Best score: 0.7140: : 803iter [00:21, 33.86iter/s]Best score: 0.7140: : 804iter [00:21, 33.86iter/s]Best score: 0.7140: : 805iter [00:21, 33.86iter/s]Best score: 0.7140: : 806iter [00:21, 36.48iter/s]Best score: 0.7140: : 806iter [00:21, 36.48iter/s]Best score: 0.7140: : 807iter [00:21, 36.48iter/s]Best score: 0.7140: : 808iter [00:21, 36.48iter/s]Best score: 0.5675: : 809iter [00:21, 36.48iter/s]Best score: 0.5675: : 810iter [00:21, 36.48iter/s]Best score: 0.5675: : 811iter [00:21, 38.46iter/s]Best score: 0.5675: : 811iter [00:21, 38.46iter/s]Best score: 0.5675: : 812iter [00:21, 38.46iter/s]Best score: 0.5675: : 813iter [00:22, 38.46iter/s]Best score: 0.5675: : 814iter [00:22, 38.46iter/s]Best score: 0.5675: : 815iter [00:22, 38.46iter/s]Best score: 0.5675: : 816iter [00:22, 40.03iter/s]Best score: 0.5675: : 816iter [00:22, 40.03iter/s]Best score: 0.5675: : 817iter [00:22, 40.03iter/s]Best score: 0.5675: : 818iter [00:22, 40.03iter/s]Best score: 0.5675: : 819iter [00:22, 40.03iter/s]Best score: 0.5675: : 820iter [00:22, 40.03iter/s]Best score: 0.5675: : 821iter [00:22, 41.17iter/s]Best score: 0.5675: : 821iter [00:22, 41.17iter/s]Best score: 0.5675: : 822iter [00:22, 41.17iter/s]Best score: 0.5675: : 823iter [00:22, 41.17iter/s]Best score: 0.5675: : 824iter [00:22, 41.17iter/s]Best score: 0.5675: : 825iter [00:22, 41.17iter/s]Best score: 0.5675: : 826iter [00:22, 42.30iter/s]Best score: 0.5675: : 826iter [00:22, 42.30iter/s]Best score: 0.5675: : 827iter [00:22, 42.30iter/s]Best score: 0.5675: : 828iter [00:22, 42.30iter/s]Best score: 0.5675: : 829iter [00:22, 42.30iter/s]Best score: 0.5675: : 830iter [00:22, 42.30iter/s]Best score: 0.5675: : 831iter [00:22, 43.01iter/s]Best score: 0.5675: : 831iter [00:22, 43.01iter/s]Best score: 0.5675: : 832iter [00:22, 43.01iter/s]Best score: 0.5675: : 833iter [00:22, 43.01iter/s]Best score: 0.5675: : 834iter [00:22, 43.01iter/s]Best score: 0.5675: : 835iter [00:22, 43.01iter/s]Best score: 0.5675: : 836iter [00:22, 43.73iter/s]Best score: 0.5675: : 836iter [00:22, 43.73iter/s]Best score: 0.5675: : 837iter [00:22, 43.73iter/s]Best score: 0.5675: : 838iter [00:22, 43.73iter/s]Best score: 0.5675: : 839iter [00:22, 43.73iter/s]Best score: 0.5675: : 840iter [00:22, 43.73iter/s]Best score: 0.5675: : 841iter [00:22, 44.07iter/s]Best score: 0.5675: : 841iter [00:22, 44.07iter/s]Best score: 0.5675: : 842iter [00:22, 44.07iter/s]Best score: 0.5675: : 843iter [00:22, 44.07iter/s]Best score: 0.5675: : 844iter [00:22, 44.07iter/s]Best score: 0.5675: : 845iter [00:22, 44.07iter/s]Best score: 0.5675: : 846iter [00:22, 44.49iter/s]Best score: 0.5675: : 846iter [00:22, 44.49iter/s]Best score: 0.5675: : 847iter [00:22, 44.49iter/s]Best score: 0.5675: : 848iter [00:22, 44.49iter/s]
[ITER 850] Best: 0.5675
[PARAMS] Current best parameters:
  fx: 556.8252
  fy: 556.1398
  px: 1019.5805
  py: 749.0445
  k1: -0.02901982
  k2: 0.01173576
  k3: -0.00664111
  k4: 0.00122785
  p1: -0.00725722
  p2: -0.00478424
  p3: -0.00462336
  p4: 0.00511296
  s1: 0.0074
  s2: -0.0034
  s3: 0.0141
  s4: -0.0074
  tilt_x: -0.0163
  tilt_y: -0.0030
  scale: 3.0018
  rotation: -0.0381
Best score: 0.5675: : 849iter [00:22, 44.49iter/s]
[Periodic outlier @ iter 750] Removing 1000 frame 15 (score=3.03, threshold=2.24)
  Remaining frames: 16
Best score: 0.5675: : 850iter [00:22, 44.49iter/s]Best score: 0.5675: : 851iter [00:22, 35.04iter/s]Best score: 0.5675: : 851iter [00:22, 35.04iter/s]Best score: 0.5675: : 852iter [00:22, 35.04iter/s]Best score: 0.5675: : 853iter [00:22, 35.04iter/s]Best score: 0.5675: : 854iter [00:23, 35.04iter/s]Best score: 0.5675: : 855iter [00:23, 35.04iter/s]Best score: 0.5675: : 856iter [00:23, 37.95iter/s]Best score: 0.5675: : 856iter [00:23, 37.95iter/s]Best score: 0.5675: : 857iter [00:23, 37.95iter/s]Best score: 0.5675: : 858iter [00:23, 37.95iter/s]Best score: 0.4142: : 859iter [00:23, 37.95iter/s]Best score: 0.4142: : 860iter [00:23, 37.95iter/s]Best score: 0.4142: : 861iter [00:23, 40.12iter/s]Best score: 0.4142: : 861iter [00:23, 40.12iter/s]Best score: 0.4142: : 862iter [00:23, 40.12iter/s]Best score: 0.4142: : 863iter [00:23, 40.12iter/s]Best score: 0.4142: : 864iter [00:23, 40.12iter/s]Best score: 0.4142: : 865iter [00:23, 40.12iter/s]Best score: 0.4142: : 866iter [00:23, 42.11iter/s]Best score: 0.4142: : 866iter [00:23, 42.11iter/s]Best score: 0.4142: : 867iter [00:23, 42.11iter/s]Best score: 0.4142: : 868iter [00:23, 42.11iter/s]Best score: 0.4142: : 869iter [00:23, 42.11iter/s]Best score: 0.4142: : 870iter [00:23, 42.11iter/s]Best score: 0.4142: : 871iter [00:23, 43.39iter/s]Best score: 0.4142: : 871iter [00:23, 43.39iter/s]Best score: 0.4142: : 872iter [00:23, 43.39iter/s]Best score: 0.4142: : 873iter [00:23, 43.39iter/s]Best score: 0.4142: : 874iter [00:23, 43.39iter/s]Best score: 0.4142: : 875iter [00:23, 43.39iter/s]Best score: 0.4142: : 876iter [00:23, 44.62iter/s]Best score: 0.4142: : 876iter [00:23, 44.62iter/s]Best score: 0.4142: : 877iter [00:23, 44.62iter/s]Best score: 0.4142: : 878iter [00:23, 44.62iter/s]Best score: 0.4142: : 879iter [00:23, 44.62iter/s]Best score: 0.4142: : 880iter [00:23, 44.62iter/s]Best score: 0.4142: : 881iter [00:23, 45.06iter/s]Best score: 0.4142: : 881iter [00:23, 45.06iter/s]Best score: 0.4142: : 882iter [00:23, 45.06iter/s]Best score: 0.4142: : 883iter [00:23, 45.06iter/s]Best score: 0.4142: : 884iter [00:23, 45.06iter/s]Best score: 0.4142: : 885iter [00:23, 45.06iter/s]Best score: 0.4142: : 886iter [00:23, 45.56iter/s]Best score: 0.4142: : 886iter [00:23, 45.56iter/s]Best score: 0.4142: : 887iter [00:23, 45.56iter/s]Best score: 0.4142: : 888iter [00:23, 45.56iter/s]Best score: 0.4142: : 889iter [00:23, 45.56iter/s]Best score: 0.4142: : 890iter [00:23, 45.56iter/s]Best score: 0.4142: : 891iter [00:23, 45.83iter/s]Best score: 0.4142: : 891iter [00:23, 45.83iter/s]Best score: 0.4142: : 892iter [00:23, 45.83iter/s]Best score: 0.4142: : 893iter [00:23, 45.83iter/s]Best score: 0.4142: : 894iter [00:23, 45.83iter/s]Best score: 0.4142: : 895iter [00:23, 45.83iter/s]Best score: 0.4142: : 896iter [00:23, 46.25iter/s]Best score: 0.4142: : 896iter [00:23, 46.25iter/s]Best score: 0.4142: : 897iter [00:23, 46.25iter/s]Best score: 0.4142: : 898iter [00:23, 46.25iter/s]
[ITER 900] Best: 0.4142
[PARAMS] Current best parameters:
  fx: 556.8252
  fy: 556.1398
  px: 1019.5805
  py: 749.0445
  k1: -0.02901982
  k2: 0.01173576
  k3: -0.00664111
  k4: 0.00122785
  p1: -0.00725722
  p2: -0.00478424
  p3: -0.00462336
  p4: 0.00511296
  s1: 0.0074
  s2: -0.0034
  s3: 0.0141
  s4: -0.0074
  tilt_x: -0.0163
  tilt_y: -0.0030
  scale: 3.0018
  rotation: -0.0381
Best score: 0.4142: : 899iter [00:23, 46.25iter/s]Best score: 0.4142: : 900iter [00:24, 46.25iter/s]Best score: 0.4142: : 901iter [00:24, 39.12iter/s]Best score: 0.4142: : 901iter [00:24, 39.12iter/s]Best score: 0.4142: : 902iter [00:24, 39.12iter/s]Best score: 0.4142: : 903iter [00:24, 39.12iter/s]Best score: 0.4142: : 904iter [00:24, 39.12iter/s]Best score: 0.4142: : 905iter [00:24, 39.12iter/s]Best score: 0.4142: : 906iter [00:24, 41.33iter/s]Best score: 0.4142: : 906iter [00:24, 41.33iter/s]Best score: 0.4142: : 907iter [00:24, 41.33iter/s]Best score: 0.4142: : 908iter [00:24, 41.33iter/s]Best score: 0.4142: : 909iter [00:24, 41.33iter/s]Best score: 0.4142: : 910iter [00:24, 41.33iter/s]Best score: 0.4142: : 911iter [00:24, 42.82iter/s]Best score: 0.4142: : 911iter [00:24, 42.82iter/s]Best score: 0.4142: : 912iter [00:24, 42.82iter/s]Best score: 0.4142: : 913iter [00:24, 42.82iter/s]Best score: 0.4142: : 914iter [00:24, 42.82iter/s]Best score: 0.4142: : 915iter [00:24, 42.82iter/s]Best score: 0.4142: : 916iter [00:24, 44.26iter/s]Best score: 0.4142: : 916iter [00:24, 44.26iter/s]Best score: 0.4142: : 917iter [00:24, 44.26iter/s]Best score: 0.4142: : 918iter [00:24, 44.26iter/s]Best score: 0.4142: : 919iter [00:24, 44.26iter/s]Best score: 0.4142: : 920iter [00:24, 44.26iter/s]Best score: 0.4142: : 921iter [00:24, 44.89iter/s]Best score: 0.4142: : 921iter [00:24, 44.89iter/s]Best score: 0.4142: : 922iter [00:24, 44.89iter/s]Best score: 0.4142: : 923iter [00:24, 44.89iter/s]Best score: 0.4142: : 924iter [00:24, 44.89iter/s]Best score: 0.4142: : 925iter [00:24, 44.89iter/s]Best score: 0.4142: : 926iter [00:24, 45.72iter/s]Best score: 0.4142: : 926iter [00:24, 45.72iter/s]Best score: 0.4142: : 927iter [00:24, 45.72iter/s]Best score: 0.4142: : 928iter [00:24, 45.72iter/s]Best score: 0.4142: : 929iter [00:24, 45.72iter/s]Best score: 0.4142: : 930iter [00:24, 45.72iter/s]Best score: 0.4142: : 931iter [00:24, 46.04iter/s]Best score: 0.4142: : 931iter [00:24, 46.04iter/s]Best score: 0.4142: : 932iter [00:24, 46.04iter/s]Best score: 0.4142: : 933iter [00:24, 46.04iter/s]Best score: 0.4142: : 934iter [00:24, 46.04iter/s]Best score: 0.4142: : 935iter [00:24, 46.04iter/s]Best score: 0.4142: : 936iter [00:24, 46.70iter/s]Best score: 0.4142: : 936iter [00:24, 46.70iter/s]Best score: 0.4142: : 937iter [00:24, 46.70iter/s]Best score: 0.4142: : 938iter [00:24, 46.70iter/s]Best score: 0.4142: : 939iter [00:24, 46.70iter/s]Best score: 0.4142: : 940iter [00:24, 46.70iter/s]Best score: 0.4142: : 941iter [00:24, 46.86iter/s]Best score: 0.4142: : 941iter [00:24, 46.86iter/s]Best score: 0.4142: : 942iter [00:24, 46.86iter/s]Best score: 0.4142: : 943iter [00:24, 46.86iter/s]Best score: 0.4142: : 944iter [00:24, 46.86iter/s]Best score: 0.4142: : 945iter [00:25, 46.86iter/s]Best score: 0.4142: : 946iter [00:25, 47.32iter/s]Best score: 0.4142: : 946iter [00:25, 47.32iter/s]Best score: 0.4142: : 947iter [00:25, 47.32iter/s]Best score: 0.4142: : 948iter [00:25, 47.32iter/s]
[ITER 950] Best: 0.4142
[PARAMS] Current best parameters:
  fx: 556.8252
  fy: 556.1398
  px: 1019.5805
  py: 749.0445
  k1: -0.02901982
  k2: 0.01173576
  k3: -0.00664111
  k4: 0.00122785
  p1: -0.00725722
  p2: -0.00478424
  p3: -0.00462336
  p4: 0.00511296
  s1: 0.0074
  s2: -0.0034
  s3: 0.0141
  s4: -0.0074
  tilt_x: -0.0163
  tilt_y: -0.0030
  scale: 3.0018
  rotation: -0.0381
Best score: 0.4142: : 949iter [00:25, 47.32iter/s]Best score: 0.4142: : 950iter [00:25, 47.32iter/s]Best score: 0.4142: : 951iter [00:25, 39.78iter/s]Best score: 0.4142: : 951iter [00:25, 39.78iter/s]Best score: 0.4142: : 952iter [00:25, 39.78iter/s]Best score: 0.4142: : 953iter [00:25, 39.78iter/s]Best score: 0.4142: : 954iter [00:25, 39.78iter/s]Best score: 0.4142: : 955iter [00:25, 39.78iter/s]Best score: 0.4142: : 956iter [00:25, 42.04iter/s]Best score: 0.4142: : 956iter [00:25, 42.04iter/s]Best score: 0.4142: : 957iter [00:25, 42.04iter/s]Best score: 0.4142: : 958iter [00:25, 42.04iter/s]Best score: 0.4142: : 959iter [00:25, 42.04iter/s]Best score: 0.4142: : 960iter [00:25, 42.04iter/s]Best score: 0.4142: : 961iter [00:25, 43.54iter/s]Best score: 0.4142: : 961iter [00:25, 43.54iter/s]Best score: 0.4142: : 962iter [00:25, 43.54iter/s]Best score: 0.4142: : 963iter [00:25, 43.54iter/s]Best score: 0.4142: : 964iter [00:25, 43.54iter/s]Best score: 0.4142: : 965iter [00:25, 43.54iter/s]Best score: 0.4142: : 966iter [00:25, 44.93iter/s]Best score: 0.4142: : 966iter [00:25, 44.93iter/s]Best score: 0.4142: : 967iter [00:25, 44.93iter/s]Best score: 0.4142: : 968iter [00:25, 44.93iter/s]Best score: 0.4142: : 969iter [00:25, 44.93iter/s]Best score: 0.4142: : 970iter [00:25, 44.93iter/s]Best score: 0.4142: : 971iter [00:25, 45.68iter/s]Best score: 0.4142: : 971iter [00:25, 45.68iter/s]Best score: 0.4142: : 972iter [00:25, 45.68iter/s]Best score: 0.4142: : 973iter [00:25, 45.68iter/s]Best score: 0.4142: : 974iter [00:25, 45.68iter/s]Best score: 0.4142: : 975iter [00:25, 45.68iter/s]Best score: 0.4142: : 976iter [00:25, 46.57iter/s]Best score: 0.4142: : 976iter [00:25, 46.57iter/s]Best score: 0.4142: : 977iter [00:25, 46.57iter/s]Best score: 0.4142: : 978iter [00:25, 46.57iter/s]Best score: 0.4142: : 979iter [00:25, 46.57iter/s]Best score: 0.4142: : 980iter [00:25, 46.57iter/s]Best score: 0.4142: : 981iter [00:25, 46.86iter/s]Best score: 0.4142: : 981iter [00:25, 46.86iter/s]Best score: 0.4142: : 982iter [00:25, 46.86iter/s]Best score: 0.4142: : 983iter [00:25, 46.86iter/s]Best score: 0.4142: : 984iter [00:25, 46.86iter/s]Best score: 0.4142: : 985iter [00:25, 46.86iter/s]Best score: 0.4142: : 986iter [00:25, 47.27iter/s]Best score: 0.4142: : 986iter [00:25, 47.27iter/s]Best score: 0.4142: : 987iter [00:25, 47.27iter/s]Best score: 0.4142: : 988iter [00:25, 47.27iter/s]Best score: 0.4142: : 989iter [00:25, 47.27iter/s]Best score: 0.4142: : 990iter [00:26, 47.27iter/s]Best score: 0.4142: : 991iter [00:26, 47.28iter/s]Best score: 0.4142: : 991iter [00:26, 47.28iter/s]Best score: 0.4142: : 992iter [00:26, 47.28iter/s]Best score: 0.4142: : 993iter [00:26, 47.28iter/s]Best score: 0.4142: : 994iter [00:26, 47.28iter/s]Best score: 0.4142: : 995iter [00:26, 47.28iter/s]Best score: 0.4142: : 996iter [00:26, 47.63iter/s]Best score: 0.4142: : 996iter [00:26, 47.63iter/s]Best score: 0.4142: : 997iter [00:26, 47.63iter/s]Best score: 0.4142: : 998iter [00:26, 47.63iter/s]
[ITER 1000] Best: 0.4142
[PARAMS] Current best parameters:
  fx: 556.8252
  fy: 556.1398
  px: 1019.5805
  py: 749.0445
  k1: -0.02901982
  k2: 0.01173576
  k3: -0.00664111
  k4: 0.00122785
  p1: -0.00725722
  p2: -0.00478424
  p3: -0.00462336
  p4: 0.00511296
  s1: 0.0074
  s2: -0.0034
  s3: 0.0141
  s4: -0.0074
  tilt_x: -0.0163
  tilt_y: -0.0030
  scale: 3.0018
  rotation: -0.0381
Best score: 0.4142: : 999iter [00:26, 47.63iter/s]Best score: 0.4142: : 1000iter [00:26, 47.63iter/s]Best score: 0.4142: : 1001iter [00:26, 33.31iter/s]Best score: 0.4142: : 1001iter [00:26, 33.31iter/s]Best score: 0.4142: : 1002iter [00:26, 33.31iter/s]Best score: 0.4142: : 1003iter [00:26, 33.31iter/s]Best score: 0.4142: : 1004iter [00:26, 33.31iter/s]Best score: 0.4142: : 1005iter [00:26, 33.31iter/s]Best score: 0.4142: : 1006iter [00:26, 36.73iter/s]Best score: 0.4142: : 1006iter [00:26, 36.73iter/s]Best score: 0.4142: : 1007iter [00:26, 36.73iter/s]Best score: 0.4142: : 1008iter [00:26, 36.73iter/s]Best score: 0.4142: : 1009iter [00:26, 36.73iter/s]Best score: 0.4142: : 1010iter [00:26, 36.73iter/s]Best score: 0.4142: : 1011iter [00:26, 39.45iter/s]Best score: 0.4142: : 1011iter [00:26, 39.45iter/s]Best score: 0.4142: : 1012iter [00:26, 39.45iter/s]Best score: 0.4142: : 1013iter [00:26, 39.45iter/s]Best score: 0.4142: : 1014iter [00:26, 39.45iter/s]Best score: 0.4142: : 1015iter [00:26, 39.45iter/s]Best score: 0.4142: : 1016iter [00:26, 41.70iter/s]Best score: 0.4142: : 1016iter [00:26, 41.70iter/s]Best score: 0.4142: : 1017iter [00:26, 41.70iter/s]Best score: 0.4142: : 1018iter [00:26, 41.70iter/s]Best score: 0.4142: : 1019iter [00:26, 41.70iter/s]Best score: 0.4142: : 1020iter [00:26, 41.70iter/s]Best score: 0.4142: : 1021iter [00:26, 43.36iter/s]Best score: 0.4142: : 1021iter [00:26, 43.36iter/s]Best score: 0.4142: : 1022iter [00:26, 43.36iter/s]Best score: 0.4142: : 1023iter [00:26, 43.36iter/s]Best score: 0.4142: : 1024iter [00:26, 43.36iter/s]Best score: 0.4142: : 1025iter [00:26, 43.36iter/s]Best score: 0.4142: : 1026iter [00:26, 44.56iter/s]Best score: 0.4142: : 1026iter [00:26, 44.56iter/s]Best score: 0.4142: : 1027iter [00:26, 44.56iter/s]Best score: 0.4142: : 1028iter [00:26, 44.56iter/s]Best score: 0.4142: : 1029iter [00:26, 44.56iter/s]Best score: 0.4142: : 1030iter [00:27, 44.56iter/s]Best score: 0.4142: : 1031iter [00:27, 45.38iter/s]Best score: 0.4142: : 1031iter [00:27, 45.38iter/s]Best score: 0.4142: : 1032iter [00:27, 45.38iter/s]Best score: 0.4142: : 1033iter [00:27, 45.38iter/s]Best score: 0.4142: : 1034iter [00:27, 45.38iter/s]Best score: 0.4142: : 1035iter [00:27, 45.38iter/s]Best score: 0.4142: : 1036iter [00:27, 46.30iter/s]Best score: 0.4142: : 1036iter [00:27, 46.30iter/s]Best score: 0.4142: : 1037iter [00:27, 46.30iter/s]Best score: 0.4142: : 1038iter [00:27, 46.30iter/s]Best score: 0.4142: : 1039iter [00:27, 46.30iter/s]Best score: 0.4142: : 1040iter [00:27, 46.30iter/s]Best score: 0.4142: : 1041iter [00:27, 46.66iter/s]Best score: 0.4142: : 1041iter [00:27, 46.66iter/s]Best score: 0.4142: : 1042iter [00:27, 46.66iter/s]Best score: 0.4142: : 1043iter [00:27, 46.66iter/s]Best score: 0.4142: : 1044iter [00:27, 46.66iter/s]Best score: 0.4142: : 1045iter [00:27, 46.66iter/s]Best score: 0.4142: : 1046iter [00:27, 47.17iter/s]Best score: 0.4142: : 1046iter [00:27, 47.17iter/s]Best score: 0.4142: : 1047iter [00:27, 47.17iter/s]Best score: 0.4142: : 1048iter [00:27, 47.17iter/s]
[ITER 1050] Best: 0.4142
[PARAMS] Current best parameters:
  fx: 556.8252
  fy: 556.1398
  px: 1019.5805
  py: 749.0445
  k1: -0.02901982
  k2: 0.01173576
  k3: -0.00664111
  k4: 0.00122785
  p1: -0.00725722
  p2: -0.00478424
  p3: -0.00462336
  p4: 0.00511296
  s1: 0.0074
  s2: -0.0034
  s3: 0.0141
  s4: -0.0074
  tilt_x: -0.0163
  tilt_y: -0.0030
  scale: 3.0018
  rotation: -0.0381
Best score: 0.4142: : 1049iter [00:27, 47.17iter/s]Best score: 0.4142: : 1050iter [00:27, 47.17iter/s]Best score: 0.4142: : 1051iter [00:27, 39.58iter/s]Best score: 0.4142: : 1051iter [00:27, 39.58iter/s]Best score: 0.4142: : 1052iter [00:27, 39.58iter/s]Best score: 0.4142: : 1053iter [00:27, 39.58iter/s]Best score: 0.4142: : 1054iter [00:27, 39.58iter/s]Best score: 0.4142: : 1055iter [00:27, 39.58iter/s]Best score: 0.4142: : 1056iter [00:27, 41.81iter/s]Best score: 0.4142: : 1056iter [00:27, 41.81iter/s]Best score: 0.4142: : 1057iter [00:27, 41.81iter/s]Best score: 0.4142: : 1058iter [00:27, 41.81iter/s]Best score: 0.4142: : 1059iter [00:27, 41.81iter/s]Best score: 0.4142: : 1060iter [00:27, 41.81iter/s]Best score: 0.4142: : 1061iter [00:27, 43.20iter/s]Best score: 0.4142: : 1061iter [00:27, 43.20iter/s]Best score: 0.4142: : 1062iter [00:27, 43.20iter/s]Best score: 0.4142: : 1063iter [00:27, 43.20iter/s]Best score: 0.4142: : 1064iter [00:27, 43.20iter/s]Best score: 0.4142: : 1065iter [00:27, 43.20iter/s]Best score: 0.4142: : 1066iter [00:27, 44.42iter/s]Best score: 0.4142: : 1066iter [00:27, 44.42iter/s]Best score: 0.4142: : 1067iter [00:27, 44.42iter/s]Best score: 0.4142: : 1068iter [00:27, 44.42iter/s]Best score: 0.4142: : 1069iter [00:27, 44.42iter/s]Best score: 0.4142: : 1070iter [00:27, 44.42iter/s]Best score: 0.4142: : 1071iter [00:27, 44.98iter/s]Best score: 0.4142: : 1071iter [00:27, 44.98iter/s]Best score: 0.4142: : 1072iter [00:27, 44.98iter/s]Best score: 0.4142: : 1073iter [00:27, 44.98iter/s]Best score: 0.4142: : 1074iter [00:27, 44.98iter/s]Best score: 0.4142: : 1075iter [00:28, 44.98iter/s]Best score: 0.4142: : 1076iter [00:28, 45.79iter/s]Best score: 0.4142: : 1076iter [00:28, 45.79iter/s]Best score: 0.4142: : 1077iter [00:28, 45.79iter/s]Best score: 0.4142: : 1078iter [00:28, 45.79iter/s]Best score: 0.4142: : 1079iter [00:28, 45.79iter/s]Best score: 0.4142: : 1080iter [00:28, 45.79iter/s]Best score: 0.4142: : 1081iter [00:28, 46.26iter/s]Best score: 0.4142: : 1081iter [00:28, 46.26iter/s]Best score: 0.4142: : 1082iter [00:28, 46.26iter/s]Best score: 0.4142: : 1083iter [00:28, 46.26iter/s]Best score: 0.4142: : 1084iter [00:28, 46.26iter/s]Best score: 0.4142: : 1085iter [00:28, 46.26iter/s]Best score: 0.4142: : 1086iter [00:28, 46.86iter/s]Best score: 0.4142: : 1086iter [00:28, 46.86iter/s]Best score: 0.4142: : 1087iter [00:28, 46.86iter/s]Best score: 0.4142: : 1088iter [00:28, 46.86iter/s]Best score: 0.4142: : 1089iter [00:28, 46.86iter/s]Best score: 0.4142: : 1090iter [00:28, 46.86iter/s]Best score: 0.4142: : 1091iter [00:28, 47.01iter/s]Best score: 0.4142: : 1091iter [00:28, 47.01iter/s]Best score: 0.4142: : 1092iter [00:28, 47.01iter/s]Best score: 0.4142: : 1093iter [00:28, 47.01iter/s]Best score: 0.4142: : 1094iter [00:28, 47.01iter/s]Best score: 0.4142: : 1095iter [00:28, 47.01iter/s]Best score: 0.4142: : 1096iter [00:28, 47.28iter/s]Best score: 0.4142: : 1096iter [00:28, 47.28iter/s]Best score: 0.4142: : 1097iter [00:28, 47.28iter/s]Best score: 0.4142: : 1098iter [00:28, 47.28iter/s]
[ITER 1100] Best: 0.4142
[PARAMS] Current best parameters:
  fx: 556.8252
  fy: 556.1398
  px: 1019.5805
  py: 749.0445
  k1: -0.02901982
  k2: 0.01173576
  k3: -0.00664111
  k4: 0.00122785
  p1: -0.00725722
  p2: -0.00478424
  p3: -0.00462336
  p4: 0.00511296
  s1: 0.0074
  s2: -0.0034
  s3: 0.0141
  s4: -0.0074
  tilt_x: -0.0163
  tilt_y: -0.0030
  scale: 3.0018
  rotation: -0.0381
Best score: 0.4142: : 1099iter [00:28, 47.28iter/s]Best score: 0.4142: : 1100iter [00:28, 38.48iter/s]

[📈] Running L-BFGS-B polish after 1100 DE iterations...
  Polish improved score: 0.414189 -> 0.406641

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 20,802 → 20,802 within 3500mm ring
  Ring polish did not improve score: 0.406641
  Success: True
  Tangential distortion: p1=-0.007210, p2=-0.004802, p3=-0.003995, p4=0.004913
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.4066
[✅] Parameters copied to: /working/MDC044_W038_2026-03-10/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 556.8251945009869
    fy: 556.1397893675651
    px: 1019.5804485044943
    py: 749.0444674847147
    k1: -0.02889895287647972
    k2: 0.011896507100890715
    k3: -0.006708558868754903
    k4: 0.001205138369871379
    p1: -0.007210360535811448
    p2: -0.004802252855889397
    p3: -0.0039946781884762075
    p4: 0.0049134620532738935
    scale: 2.9999255163527994
    rotation: -0.03811128401040451
    mmpp: 1.27765918862247

[🔄] Converting 361 frames to PTD, creating debug images for 200 calibration frames...
📁 Rigs:   0%|          | 0/2 [00:00<?, ?rig/s]
   🔄 500:   0%|          | 0/201 [00:00<?, ?frame/s][A
   🔄 500:   8%|▊         | 17/201 [00:00<00:01, 168.41frame/s][A
   🔄 500:  17%|█▋        | 35/201 [00:00<00:00, 170.54frame/s][A
   🔄 500:  26%|██▋       | 53/201 [00:00<00:00, 171.24frame/s][A
   🔄 500:  35%|███▌      | 71/201 [00:00<00:00, 171.19frame/s][A
   🔄 500:  44%|████▍     | 89/201 [00:00<00:00, 173.90frame/s][A
   🔄 500:  54%|█████▎    | 108/201 [00:00<00:00, 176.35frame/s][A
   🔄 500:  63%|██████▎   | 127/201 [00:00<00:00, 177.66frame/s][A
   🔄 500:  72%|███████▏  | 145/201 [00:00<00:00, 175.57frame/s][A
   🔄 500:  81%|████████  | 163/201 [00:00<00:00, 174.40frame/s][A
   🔄 500:  90%|█████████ | 181/201 [00:01<00:00, 173.40frame/s][A
   🔄 500:  99%|█████████▉| 199/201 [00:01<00:00, 172.65frame/s][A
                                                                [A📁 Rigs:  50%|█████     | 1/2 [00:02<00:02,  2.11s/rig]
   🔄 1000:   0%|          | 0/160 [00:00<?, ?frame/s][A
   🔄 1000:  18%|█▊        | 28/160 [00:00<00:00, 273.68frame/s][A
   🔄 1000:  35%|███▌      | 56/160 [00:00<00:00, 208.37frame/s][A
   🔄 1000:  49%|████▉     | 78/160 [00:00<00:00, 192.20frame/s][A
   🔄 1000:  61%|██████▏   | 98/160 [00:00<00:00, 184.51frame/s][A
   🔄 1000:  73%|███████▎  | 117/160 [00:00<00:00, 181.20frame/s][A
   🔄 1000:  85%|████████▌ | 136/160 [00:00<00:00, 179.25frame/s][A
   🔄 1000:  96%|█████████▋| 154/160 [00:00<00:00, 177.98frame/s][A
                                                                 [A📁 Rigs: 100%|██████████| 2/2 [00:03<00:00,  1.77s/rig]📁 Rigs: 100%|██████████| 2/2 [00:03<00:00,  1.82s/rig]
[✅] Saved PTDs: /working/MDC044_W038_2026-03-10/calibration/debug/4_undistorted/output/ptd
📁 Rigs:   0%|          | 0/2 [00:00<?, ?rig/s]
   🔄 500:   0%|          | 0/100 [00:00<?, ?frame/s][A
   🔄 500:  18%|█▊        | 18/100 [00:00<00:00, 170.53frame/s][A
   🔄 500:  36%|███▌      | 36/100 [00:00<00:00, 170.76frame/s][A
   🔄 500:  54%|█████▍    | 54/100 [00:00<00:00, 174.61frame/s][A
   🔄 500:  72%|███████▏  | 72/100 [00:00<00:00, 176.23frame/s][A
   🔄 500:  90%|█████████ | 90/100 [00:00<00:00, 174.67frame/s][A
                                                               [A📁 Rigs:  50%|█████     | 1/2 [00:01<00:01,  1.02s/rig]
   🔄 1000:   0%|          | 0/100 [00:00<?, ?frame/s][A
   🔄 1000:  24%|██▍       | 24/100 [00:00<00:00, 238.31frame/s][A
   🔄 1000:  48%|████▊     | 48/100 [00:00<00:00, 194.10frame/s][A
   🔄 1000:  68%|██████▊   | 68/100 [00:00<00:00, 184.25frame/s][A
   🔄 1000:  87%|████████▋ | 87/100 [00:00<00:00, 180.67frame/s][A
                                                                [A📁 Rigs: 100%|██████████| 2/2 [00:01<00:00,  1.07rig/s]📁 Rigs: 100%|██████████| 2/2 [00:01<00:00,  1.05rig/s]
[✅] Saved PTDs: /working/MDC044_W038_2026-03-10/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%|▎         | 78301/3080448 [00:00<00:03, 783005.15px/s]📤 Writing LUT:   5%|▌         | 162541/3080448 [00:00<00:03, 817937.93px/s]📤 Writing LUT:   8%|▊         | 250891/3080448 [00:00<00:03, 847869.63px/s]📤 Writing LUT:  11%|█         | 335680/3080448 [00:00<00:03, 847874.80px/s]📤 Writing LUT:  14%|█▍        | 423766/3080448 [00:00<00:03, 859768.24px/s]📤 Writing LUT:  17%|█▋        | 512808/3080448 [00:00<00:02, 870186.57px/s]📤 Writing LUT:  20%|█▉        | 602223/3080448 [00:00<00:02, 878016.90px/s]📤 Writing LUT:  22%|██▏       | 691306/3080448 [00:00<00:02, 882093.54px/s]📤 Writing LUT:  25%|██▌       | 779516/3080448 [00:00<00:02, 876398.58px/s]📤 Writing LUT:  28%|██▊       | 867164/3080448 [00:01<00:02, 868737.29px/s]📤 Writing LUT:  31%|███       | 954404/3080448 [00:01<00:02, 869844.43px/s]📤 Writing LUT:  34%|███▍      | 1043048/3080448 [00:01<00:02, 874858.28px/s]📤 Writing LUT:  37%|███▋      | 1130546/3080448 [00:01<00:02, 873725.49px/s]📤 Writing LUT:  40%|███▉      | 1217927/3080448 [00:01<00:02, 873644.02px/s]📤 Writing LUT:  42%|████▏     | 1307487/3080448 [00:01<00:02, 880240.56px/s]📤 Writing LUT:  45%|████▌     | 1395518/3080448 [00:01<00:01, 877519.11px/s]📤 Writing LUT:  48%|████▊     | 1485126/3080448 [00:01<00:01, 883079.81px/s]📤 Writing LUT:  51%|█████     | 1575529/3080448 [00:01<00:01, 889356.89px/s]📤 Writing LUT:  54%|█████▍    | 1664471/3080448 [00:01<00:01, 888828.41px/s]📤 Writing LUT:  57%|█████▋    | 1754550/3080448 [00:02<00:01, 892413.36px/s]📤 Writing LUT:  60%|█████▉    | 1843795/3080448 [00:02<00:01, 879571.42px/s]📤 Writing LUT:  63%|██████▎   | 1932040/3080448 [00:02<00:01, 880423.64px/s]📤 Writing LUT:  66%|██████▌   | 2020621/3080448 [00:02<00:01, 882026.57px/s]📤 Writing LUT:  68%|██████▊   | 2108847/3080448 [00:02<00:01, 880488.26px/s]📤 Writing LUT:  71%|███████▏  | 2196912/3080448 [00:02<00:01, 878074.46px/s]📤 Writing LUT:  74%|███████▍  | 2284731/3080448 [00:02<00:00, 872295.94px/s]📤 Writing LUT:  77%|███████▋  | 2371975/3080448 [00:02<00:00, 871581.80px/s]📤 Writing LUT:  80%|███████▉  | 2459255/3080448 [00:02<00:00, 871942.65px/s]📤 Writing LUT:  83%|████████▎ | 2546647/3080448 [00:02<00:00, 872532.77px/s]📤 Writing LUT:  86%|████████▌ | 2636309/3080448 [00:03<00:00, 879733.52px/s]📤 Writing LUT:  89%|████████▊ | 2726409/3080448 [00:03<00:00, 886097.48px/s]📤 Writing LUT:  91%|█████████▏| 2816932/3080448 [00:03<00:00, 891826.54px/s]📤 Writing LUT:  94%|█████████▍| 2906120/3080448 [00:03<00:00, 889693.66px/s]📤 Writing LUT:  97%|█████████▋| 2995094/3080448 [00:03<00:00, 887930.09px/s]📤 Writing LUT: 100%|██████████| 3080448/3080448 [00:03<00:00, 876652.04px/s]
[✅] LUT written to: /working/MDC044_W038_2026-03-10/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'MDC044_W038_2026-03-10' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDC044_W038_2026-03-10/calibration/MDC044_W038_2026-03-10_unknown.lut

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

[ℹ️] Detected device type: MD (rigs: [500, 1000]mm)
📁 Rigs (heatmap):   0%|          | 0/2 [00:00<?, ?rig/s]
   🔥 500:   0%|          | 0/201 [00:00<?, ?frame/s][A
   🔥 500:   3%|▎         | 7/201 [00:00<00:02, 69.03frame/s][A
   🔥 500:   7%|▋         | 15/201 [00:00<00:02, 73.92frame/s][A
   🔥 500:  11%|█▏        | 23/201 [00:00<00:02, 74.48frame/s][A
   🔥 500:  15%|█▌        | 31/201 [00:00<00:02, 75.14frame/s][A
   🔥 500:  19%|█▉        | 39/201 [00:00<00:02, 75.36frame/s][A
   🔥 500:  23%|██▎       | 47/201 [00:00<00:02, 76.42frame/s][A
   🔥 500:  27%|██▋       | 55/201 [00:00<00:01, 76.49frame/s][A
   🔥 500:  31%|███▏      | 63/201 [00:00<00:01, 76.70frame/s][A
   🔥 500:  35%|███▌      | 71/201 [00:00<00:01, 76.63frame/s][A
   🔥 500:  40%|███▉      | 80/201 [00:01<00:01, 77.86frame/s][A
   🔥 500:  44%|████▍     | 88/201 [00:01<00:01, 77.75frame/s][A
   🔥 500:  48%|████▊     | 96/201 [00:01<00:01, 78.23frame/s][A
   🔥 500:  52%|█████▏    | 104/201 [00:01<00:01, 78.17frame/s][A
   🔥 500:  56%|█████▌    | 113/201 [00:01<00:01, 78.80frame/s][A
   🔥 500:  61%|██████    | 122/201 [00:01<00:00, 79.77frame/s][A
   🔥 500:  65%|██████▍   | 130/201 [00:01<00:00, 78.82frame/s][A
   🔥 500:  69%|██████▊   | 138/201 [00:01<00:00, 77.93frame/s][A
   🔥 500:  73%|███████▎  | 146/201 [00:01<00:00, 77.45frame/s][A
   🔥 500:  77%|███████▋  | 154/201 [00:01<00:00, 77.07frame/s][A
   🔥 500:  81%|████████  | 162/201 [00:02<00:00, 76.52frame/s][A
   🔥 500:  85%|████████▍ | 170/201 [00:02<00:00, 75.58frame/s][A
   🔥 500:  89%|████████▊ | 178/201 [00:02<00:00, 75.19frame/s][A
   🔥 500:  93%|█████████▎| 186/201 [00:02<00:00, 75.00frame/s][A
   🔥 500:  97%|█████████▋| 194/201 [00:02<00:00, 75.24frame/s][A
                                                               [A[✅] 500: /working/MDC044_W038_2026-03-10/calibration/debug/5_heatmap/500_heatmap.png
[✅] 500 (fitted): /working/MDC044_W038_2026-03-10/calibration/debug/5_heatmap/500_heatmap_fitted.png
📁 Rigs (heatmap):  50%|█████     | 1/2 [00:03<00:03,  3.84s/rig]
   🔥 1000:   0%|          | 0/160 [00:00<?, ?frame/s][A
   🔥 1000:   8%|▊         | 13/160 [00:00<00:01, 127.66frame/s][A
   🔥 1000:  16%|█▋        | 26/160 [00:00<00:01, 112.18frame/s][A
   🔥 1000:  24%|██▍       | 38/160 [00:00<00:01, 95.73frame/s] [A
   🔥 1000:  30%|███       | 48/160 [00:00<00:01, 89.03frame/s][A
   🔥 1000:  36%|███▋      | 58/160 [00:00<00:01, 84.32frame/s][A
   🔥 1000:  42%|████▏     | 67/160 [00:00<00:01, 82.78frame/s][A
   🔥 1000:  48%|████▊     | 76/160 [00:00<00:01, 82.75frame/s][A
   🔥 1000:  53%|█████▎    | 85/160 [00:00<00:00, 83.71frame/s][A
   🔥 1000:  59%|█████▉    | 94/160 [00:01<00:00, 82.73frame/s][A
   🔥 1000:  64%|██████▍   | 103/160 [00:01<00:00, 81.82frame/s][A
   🔥 1000:  70%|███████   | 112/160 [00:01<00:00, 82.48frame/s][A
   🔥 1000:  76%|███████▌  | 121/160 [00:01<00:00, 83.97frame/s][A
   🔥 1000:  81%|████████▏ | 130/160 [00:01<00:00, 84.20frame/s][A
   🔥 1000:  87%|████████▋ | 139/160 [00:01<00:00, 84.02frame/s][A
   🔥 1000:  92%|█████████▎| 148/160 [00:01<00:00, 84.59frame/s][A
   🔥 1000:  98%|█████████▊| 157/160 [00:01<00:00, 84.12frame/s][A
                                                                [A[✅] 1000: /working/MDC044_W038_2026-03-10/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDC044_W038_2026-03-10/calibration/debug/5_heatmap/1000_heatmap_fitted.png
📁 Rigs (heatmap): 100%|██████████| 2/2 [00:08<00:00,  4.45s/rig]📁 Rigs (heatmap): 100%|██████████| 2/2 [00:08<00:00,  4.36s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MDC044_W038_2026-03-10/calibration/debug/5_heatmap
[🏁] Finished processing MDC044_W038_2026-03-10


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