2026-08-28T15:20:49 - INFO: Slick 0.0.8a13

🟢 Starting Calibration Pipeline

=== Processing MDC026_W024_2026-08-25 ===
2026-08-28T15:20:49 - INFO: Camera ID: 11481106
2026-08-28T15:20:49 - INFO: Wand ID: 
2026-08-28T15:20:49 - INFO: Recorded At: 2026-08-25T12:16:13Z

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                        Step 1: Digitization                       
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[🔄] Full PTD mode: Processing ALL images then creating calibration subset
[📸] Digitizing ALL images...
[📸] Full dataset mode: Processing ALL images (no debug visualizations)
[INFO] Found 2 las0.zip files to process
Processing Rigs:   0%|          | 0/2 [00:00<?, ?it/s][INFO] Filtered 631 stationary frames, 671 remain

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                                                                           [A[PASS2] Frame 0000310: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000311: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000312: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000314: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000315: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000316: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000317: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000318: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000341: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000342: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000343: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000345: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000347: fixed corners {2, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000350: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000351: fixed corners {2, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000353: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000354: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000355: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000356: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000357: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000359: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000360: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000361: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000362: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000366: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000367: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000368: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000372: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000373: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000374: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000375: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000376: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000377: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000454: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000455: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000456: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000457: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000458: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000461: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000462: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000463: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000465: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000466: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000468: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000469: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000472: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000488: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000489: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000490: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000491: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000501: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000502: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000503: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000504: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000505: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000506: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000507: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000508: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000509: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000510: fixed corners {3} (was_fixed=True, trusted=True)
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[PASS2] Frame 0000516: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000517: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000518: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000519: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000521: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000523: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000581: fixed corners {3} (was_fixed=True, trusted=False)
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[PASS2] Frame 0000621: fixed corners {3} (was_fixed=False, trusted=False)
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[PASS2] Frame 0000649: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000650: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000651: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000658: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000659: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000660: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000663: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001021: fixed corners {2} (was_fixed=False, trusted=False)
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[PASS2] Frame 0001024: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001036: fixed corners {2} (was_fixed=False, trusted=False)
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[PASS2] Frame 0001039: fixed corners {2} (was_fixed=True, trusted=False)
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[PASS2] Frame 0001055: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001056: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001057: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001058: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001059: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001060: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001061: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001062: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001125: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001126: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001127: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001128: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001129: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001130: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001133: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001134: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001135: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001136: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001140: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001141: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001142: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001143: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001144: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001145: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001146: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001147: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001148: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001149: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001150: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001151: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001154: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001155: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001156: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001157: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001158: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001159: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001163: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001164: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001165: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001170: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001171: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001172: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001186: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001187: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001188: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001191: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001197: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001200: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001201: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001203: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001284: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001285: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001286: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001287: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001288: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001289: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001290: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001293: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001298: fixed corners {0, 2, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001302: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001303: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001304: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001305: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001306: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001307: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001308: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001311: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001312: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001314: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001315: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001316: fixed corners {2, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001318: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001319: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000312: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000313: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000315: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000317: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000351: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000352: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000353: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000357: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000358: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000360: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000361: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000375: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000376: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000456: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000457: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000463: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000464: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000467: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000468: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000490: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000503: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000504: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000508: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000509: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000515: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000517: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000518: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000519: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000521: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000523: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000581: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000589: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000594: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000595: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000596: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000598: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000599: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000600: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000606: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000608: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000612: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000623: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000634: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000636: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000647: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000650: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000660: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001023: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001040: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001049: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001058: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001059: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001128: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001129: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001135: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001143: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001147: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001149: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001150: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001156: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001157: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001158: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001167: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001170: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001171: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001188: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001201: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001286: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001288: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001289: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001290: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001299: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001301: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001305: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001308: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001309: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001310: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001311: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001316: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001317: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001318: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000348: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000349: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000372: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000373: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000467: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000517: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000518: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000519: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000521: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000523: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000581: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000592: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000593: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000594: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000598: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000599: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000600: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001167: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001170: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001287: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001288: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001289: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001298: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001299: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Summary: 129 frames fixed, 120 untrusted, 671 total

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                                                                           [A
[TIMING] 1000 — 671 frames
  Phase 1  radial detect   (parallel)  :   9.50s  (14.2 ms/frame)
  Phase 2a corner detect   (parallel)  :   4.73s  (7.0 ms/frame)
  Phase 2b corner fix      (sequential):   5.03s
  Phase 3  finalize        (sequential):  13.10s  (19.5 ms/frame)
    decode + undistort                 :   6.58s  (9.8 ms/frame)
    corner apply + refinement          :   3.12s  (4.6 ms/frame)
    segment                            :   2.78s  (4.1 ms/frame)
    smooth                             :   0.40s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  32.35s

Processing Rigs:  50%|█████     | 1/2 [00:38<00:38, 38.27s/it][INFO] Filtered 668 stationary frames, 609 remain

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                                                                          [A[PASS2] Frame 0000341: fixed corners {2} (was_fixed=False, 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 0000344: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000437: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000438: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000439: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000440: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000963: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001185: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001186: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001189: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001192: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001257: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001258: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001259: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001260: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001275: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001276: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001277: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001278: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001290: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001291: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001292: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001293: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001294: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001295: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001300: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001301: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001302: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001303: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001306: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001307: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001308: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001309: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000343: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000439: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001189: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001259: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001292: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001293: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001294: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001302: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001308: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 19 frames fixed, 17 untrusted, 609 total

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                                                                          [A
[TIMING] 500 — 609 frames
  Phase 1  radial detect   (parallel)  :   8.97s  (14.7 ms/frame)
  Phase 2a corner detect   (parallel)  :   4.80s  (7.9 ms/frame)
  Phase 2b corner fix      (sequential):   0.98s
  Phase 3  finalize        (sequential):  11.52s  (18.9 ms/frame)
    decode + undistort                 :   5.93s  (9.7 ms/frame)
    corner apply + refinement          :   2.44s  (4.0 ms/frame)
    segment                            :   2.49s  (4.1 ms/frame)
    smooth                             :   0.46s  (0.8 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  26.27s

Processing Rigs: 100%|██████████| 2/2 [01:08<00:00, 33.64s/it]Processing Rigs: 100%|██████████| 2/2 [01:08<00:00, 34.33s/it]
[💾] Saved RigFrameDataset to /working/MDC026_W024_2026-08-25/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 1280 frames from 2 rigs to /working/MDC026_W024_2026-08-25/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDC026_W024_2026-08-25/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 1000: 100 frames selected from 671
[📋] 500: 100 frames selected from 609
[💾] Saved RigFrameDataset to /working/MDC026_W024_2026-08-25/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDC026_W024_2026-08-25/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 [00:04<02:54,  4.46s/it]Computing max image from bright frames:   5%|▌         | 2/40 [00:04<01:12,  1.92s/it]Computing max image from bright frames:   8%|▊         | 3/40 [00:04<00:43,  1.19s/it]Computing max image from bright frames:  10%|█         | 4/40 [00:05<00:27,  1.30it/s]Computing max image from bright frames:  12%|█▎        | 5/40 [00:05<00:19,  1.84it/s]Computing max image from bright frames:  15%|█▌        | 6/40 [00:05<00:13,  2.48it/s]Computing max image from bright frames:  18%|█▊        | 7/40 [00:05<00:10,  3.27it/s]Computing max image from bright frames:  22%|██▎       | 9/40 [00:05<00:05,  5.39it/s]Computing max image from bright frames:  28%|██▊       | 11/40 [00:05<00:04,  6.83it/s]Computing max image from bright frames:  32%|███▎      | 13/40 [00:06<00:05,  4.57it/s]Computing max image from bright frames:  38%|███▊      | 15/40 [00:06<00:04,  6.22it/s]Computing max image from bright frames:  42%|████▎     | 17/40 [00:06<00:03,  7.55it/s]Computing max image from bright frames:  48%|████▊     | 19/40 [00:06<00:02,  9.09it/s]Computing max image from bright frames:  52%|█████▎    | 21/40 [00:06<00:01,  9.93it/s]Computing max image from bright frames:  57%|█████▊    | 23/40 [00:07<00:01,  9.23it/s]Computing max image from bright frames:  62%|██████▎   | 25/40 [00:07<00:01, 10.48it/s]Computing max image from bright frames:  70%|███████   | 28/40 [00:07<00:01, 11.91it/s]Computing max image from bright frames:  75%|███████▌  | 30/40 [00:07<00:00, 12.47it/s]Computing max image from bright frames:  80%|████████  | 32/40 [00:08<00:00,  9.40it/s]Computing max image from bright frames:  85%|████████▌ | 34/40 [00:08<00:01,  5.26it/s]Computing max image from bright frames:  88%|████████▊ | 35/40 [00:09<00:01,  4.84it/s]Computing max image from bright frames:  95%|█████████▌| 38/40 [00:09<00:00,  7.36it/s]Computing max image from bright frames: 100%|██████████| 40/40 [00:09<00:00,  8.95it/s]                                                                                       [✅] Casing detection complete: cx=998.0, cy=760.0

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

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533.333} (0.088):  33%|███▎      | 33/100 [00:00<00:01, 51.21it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.014 | Best: {'fx': 533.333} (0.088):  34%|███▍      | 34/100 [00:00<00:01, 51.21it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.014 | Best: {'fx': 533.333} (0.088):  35%|███▌      | 35/100 [00:00<00:01, 51.21it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 533.333} (0.088):  36%|███▌      | 36/100 [00:00<00:01, 51.21it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.013 | Best: {'fx': 533.333} (0.088):  37%|███▋      | 37/100 [00:00<00:01, 51.21it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 533.333} (0.088):  38%|███▊      | 38/100 [00:00<00:01, 51.21it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 533.333} (0.088):  39%|███▉      | 39/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 533.333} (0.088):  39%|███▉      | 39/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 533.333} (0.088):  40%|████      | 40/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 533.333} (0.088):  41%|████      | 41/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.088):  42%|████▏     | 42/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.088):  43%|████▎     | 43/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.088):  44%|████▍     | 44/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 533.333} (0.088):  45%|████▌     | 45/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.004 | Best: {'fx': 533.333} (0.088):  46%|████▌     | 46/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.033 | Best: {'fx': 533.333} (0.088):  47%|████▋     | 47/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.088):  48%|████▊     | 48/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.007 | Best: {'fx': 533.333} (0.088):  49%|████▉     | 49/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.001 | Best: {'fx': 533.333} (0.088):  50%|█████     | 50/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.020 | Best: {'fx': 533.333} (0.088):  51%|█████     | 51/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.088):  52%|█████▏    | 52/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.088):  53%|█████▎    | 53/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.088):  54%|█████▍    | 54/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.088):  55%|█████▌    | 55/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.088):  56%|█████▌    | 56/100 [00:00<00:00, 94.88it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.088):  57%|█████▋    | 57/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.088):  57%|█████▋    | 57/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.088):  58%|█████▊    | 58/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.088):  59%|█████▉    | 59/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.088):  60%|██████    | 60/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  61%|██████    | 61/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.088):  62%|██████▏   | 62/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  63%|██████▎   | 63/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  64%|██████▍   | 64/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  65%|██████▌   | 65/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  66%|██████▌   | 66/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  67%|██████▋   | 67/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  68%|██████▊   | 68/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  69%|██████▉   | 69/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  70%|███████   | 70/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  71%|███████   | 71/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  72%|███████▏  | 72/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  73%|███████▎  | 73/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  74%|███████▍  | 74/100 [00:00<00:00, 114.00it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  75%|███████▌  | 75/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  75%|███████▌  | 75/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  76%|███████▌  | 76/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  77%|███████▋  | 77/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  78%|███████▊  | 78/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  79%|███████▉  | 79/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  80%|████████  | 80/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  81%|████████  | 81/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  82%|████████▏ | 82/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  83%|████████▎ | 83/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  84%|████████▍ | 84/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  85%|████████▌ | 85/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  86%|████████▌ | 86/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  87%|████████▋ | 87/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  88%|████████▊ | 88/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  89%|████████▉ | 89/100 [00:00<00:00, 130.60it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  90%|█████████ | 90/100 [00:00<00:00, 127.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  90%|█████████ | 90/100 [00:00<00:00, 127.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  91%|█████████ | 91/100 [00:00<00:00, 127.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  92%|█████████▏| 92/100 [00:00<00:00, 127.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  93%|█████████▎| 93/100 [00:00<00:00, 127.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  94%|█████████▍| 94/100 [00:01<00:00, 127.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  95%|█████████▌| 95/100 [00:01<00:00, 127.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  96%|█████████▌| 96/100 [00:01<00:00, 127.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  97%|█████████▋| 97/100 [00:01<00:00, 127.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  98%|█████████▊| 98/100 [00:01<00:00, 127.87it/s]Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.088):  99%|█████████▉| 99/100 [00:01<00:00, 127.87it/s]                                                                                                                                          0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.011 | Best: {'fx': 508.333} (0.011):   0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.011 | Best: {'fx': 508.333} (0.011):   2%|▏         | 1/50 [00:00<00:05,  8.41it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.013 | Best: {'fx': 509.354} (0.013):   2%|▏         | 1/50 [00:00<00:05,  8.41it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.016 | Best: {'fx': 511.395} (0.016):   4%|▍         | 2/50 [00:00<00:05,  8.41it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.014 | Best: {'fx': 511.395} (0.016):   6%|▌         | 3/50 [00:00<00:05,  8.41it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.026 | Best: {'fx': 515.476} (0.026):   8%|▊         | 4/50 [00:00<00:05,  8.41it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.020 | Best: {'fx': 515.476} (0.026):  10%|█         | 5/50 [00:00<00:05,  8.41it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.024 | Best: {'fx': 515.476} (0.026):  12%|█▏        | 6/50 [00:00<00:05,  8.41it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.025 | Best: {'fx': 515.476} (0.026):  14%|█▍        | 7/50 [00:00<00:05,  8.41it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.028 | Best: {'fx': 516.497} (0.028):  16%|█▌        | 8/50 [00:00<00:04,  8.41it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.032 | Best: {'fx': 518.537} (0.032):  18%|█▊        | 9/50 [00:00<00:04,  8.41it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.029 | Best: {'fx': 518.537} (0.032):  20%|██        | 10/50 [00:00<00:04,  8.41it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.033 | Best: {'fx': 519.558} (0.033):  22%|██▏       | 11/50 [00:00<00:04,  8.41it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.033 | Best: {'fx': 519.558} (0.033):  24%|██▍       | 12/50 [00:00<00:00, 62.32it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.036 | Best: {'fx': 520.578} (0.036):  24%|██▍       | 12/50 [00:00<00:00, 62.32it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.046 | Best: {'fx': 523.639} (0.046):  26%|██▌       | 13/50 [00:00<00:00, 62.32it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.039 | Best: {'fx': 523.639} (0.046):  28%|██▊       | 14/50 [00:00<00:00, 62.32it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.042 | Best: {'fx': 523.639} (0.046):  30%|███       | 15/50 [00:00<00:00, 62.32it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.050 | Best: {'fx': 524.66} (0.050):  32%|███▏      | 16/50 [00:00<00:00, 62.32it/s] Brute | Start: {'fx': 533.333} (0.088) | Current: 0.054 | Best: {'fx': 525.68} (0.054):  34%|███▍      | 17/50 [00:00<00:00, 62.32it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.059 | Best: {'fx': 526.701} (0.059):  36%|███▌      | 18/50 [00:00<00:00, 62.32it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.086 | Best: {'fx': 530.782} (0.086):  38%|███▊      | 19/50 [00:00<00:00, 62.32it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.067 | Best: {'fx': 530.782} (0.086):  40%|████      | 20/50 [00:00<00:00, 62.32it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.073 | Best: {'fx': 530.782} (0.086):  42%|████▏     | 21/50 [00:00<00:00, 62.32it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.087 | Best: {'fx': 531.803} (0.087):  44%|████▍     | 22/50 [00:00<00:00, 62.32it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.076 | Best: {'fx': 531.803} (0.087):  46%|████▌     | 23/50 [00:00<00:00, 62.32it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.079 | Best: {'fx': 531.803} (0.087):  48%|████▊     | 24/50 [00:00<00:00, 62.32it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.079 | Best: {'fx': 531.803} (0.087):  50%|█████     | 25/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.088 | Best: {'fx': 532.823} (0.088):  50%|█████     | 25/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.085 | Best: {'fx': 532.823} (0.088):  52%|█████▏    | 26/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.051 | Best: {'fx': 532.823} (0.088):  54%|█████▍    | 27/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.066 | Best: {'fx': 532.823} (0.088):  56%|█████▌    | 28/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.046 | Best: {'fx': 532.823} (0.088):  58%|█████▊    | 29/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.060 | Best: {'fx': 532.823} (0.088):  60%|██████    | 30/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.073 | Best: {'fx': 532.823} (0.088):  62%|██████▏   | 31/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.044 | Best: {'fx': 532.823} (0.088):  64%|██████▍   | 32/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.056 | Best: {'fx': 532.823} (0.088):  66%|██████▌   | 33/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.040 | Best: {'fx': 532.823} (0.088):  68%|██████▊   | 34/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.042 | Best: {'fx': 532.823} (0.088):  70%|███████   | 35/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.035 | Best: {'fx': 532.823} (0.088):  72%|███████▏  | 36/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.037 | Best: {'fx': 532.823} (0.088):  74%|███████▍  | 37/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.034 | Best: {'fx': 532.823} (0.088):  76%|███████▌  | 38/50 [00:00<00:00, 88.44it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.034 | Best: {'fx': 532.823} (0.088):  78%|███████▊  | 39/50 [00:00<00:00, 106.69it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.032 | Best: {'fx': 532.823} (0.088):  78%|███████▊  | 39/50 [00:00<00:00, 106.69it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.031 | Best: {'fx': 532.823} (0.088):  80%|████████  | 40/50 [00:00<00:00, 106.69it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.030 | Best: {'fx': 532.823} (0.088):  82%|████████▏ | 41/50 [00:00<00:00, 106.69it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.030 | Best: {'fx': 532.823} (0.088):  84%|████████▍ | 42/50 [00:00<00:00, 106.69it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.027 | Best: {'fx': 532.823} (0.088):  86%|████████▌ | 43/50 [00:00<00:00, 106.69it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.028 | Best: {'fx': 532.823} (0.088):  88%|████████▊ | 44/50 [00:00<00:00, 106.69it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.025 | Best: {'fx': 532.823} (0.088):  90%|█████████ | 45/50 [00:00<00:00, 106.69it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.027 | Best: {'fx': 532.823} (0.088):  92%|█████████▏| 46/50 [00:00<00:00, 106.69it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.025 | Best: {'fx': 532.823} (0.088):  94%|█████████▍| 47/50 [00:00<00:00, 106.69it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.024 | Best: {'fx': 532.823} (0.088):  96%|█████████▌| 48/50 [00:00<00:00, 106.69it/s]Brute | Start: {'fx': 533.333} (0.088) | Current: 0.024 | Best: {'fx': 532.823} (0.088):  98%|█████████▊| 49/50 [00:00<00:00, 106.69it/s]                                                                                                                                         
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 533.3333333333334
    px: 998.0
    py: 760.0
    k1: 0.0
    k2: 0.0
    k3: 0.0
    k4: 0.0
    p1: 0.0
    p2: 0.0
    p3: 0.0
    p4: 0.0
    scale: 3.0
    rotation: 0.0


[🔲] Square Reference Optimization
    Including tangential distortion parameters (p1, p2, p3, p4) in joint optimization
  Selecting up to 20 frames per rig (excluded 0 incomplete frames): 20 frames will be used for optimization
  Rigs: 1000(1000mm):20/20
  Total: 20/20 frames used for optimization
Initial score: 13.6168: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 13.6168, picklable_objective(x0) = 13.6431
Best score: 13.6431: : 0iter [00:01, ?iter/s] Best score: 13.6431: : 1iter [00:01,  1.83s/iter]Best score: 13.6431: : 1iter [00:01,  1.83s/iter]Best score: 13.6431: : 2iter [00:02,  1.83s/iter]Best score: 13.6431: : 3iter [00:02,  1.84iter/s]Best score: 13.6431: : 3iter [00:02,  1.84iter/s]Best score: 13.6431: : 4iter [00:02,  1.84iter/s]Best score: 13.6431: : 5iter [00:02,  1.84iter/s]Best score: 13.6431: : 6iter [00:02,  1.84iter/s]Best score: 13.6431: : 7iter [00:02,  5.22iter/s]Best score: 13.6431: : 7iter [00:02,  5.22iter/s]Best score: 13.6431: : 8iter [00:02,  5.22iter/s]Best score: 13.6431: : 9iter [00:02,  5.22iter/s]Best score: 13.6431: : 10iter [00:02,  5.22iter/s]Best score: 13.6431: : 11iter [00:02,  9.08iter/s]Best score: 13.6431: : 11iter [00:02,  9.08iter/s]Best score: 13.6431: : 12iter [00:02,  9.08iter/s]Best score: 13.6431: : 13iter [00:02,  9.08iter/s]Best score: 13.6431: : 14iter [00:02,  9.08iter/s]Best score: 13.6431: : 15iter [00:02, 13.34iter/s]Best score: 13.6431: : 15iter [00:02, 13.34iter/s]Best score: 13.6431: : 16iter [00:02, 13.34iter/s]Best score: 13.6431: : 17iter [00:02, 13.34iter/s]Best score: 13.6431: : 18iter [00:02, 13.34iter/s]Best score: 13.6431: : 19iter [00:02, 17.71iter/s]Best score: 13.6431: : 19iter [00:02, 17.71iter/s]Best score: 13.6431: : 20iter [00:02, 17.71iter/s]Best score: 13.6431: : 21iter [00:02, 17.71iter/s]Best score: 13.6431: : 22iter [00:02, 17.71iter/s]Best score: 13.6431: : 23iter [00:02, 21.83iter/s]Best score: 13.6431: : 23iter [00:02, 21.83iter/s]Best score: 13.6431: : 24iter [00:02, 21.83iter/s]Best score: 13.6431: : 25iter [00:02, 21.83iter/s]Best score: 13.6431: : 26iter [00:02, 21.83iter/s]Best score: 13.6431: : 27iter [00:02, 25.67iter/s]Best score: 13.6431: : 27iter [00:02, 25.67iter/s]Best score: 13.6431: : 28iter [00:02, 25.67iter/s]Best score: 13.6431: : 29iter [00:02, 25.67iter/s]Best score: 13.6431: : 30iter [00:02, 25.67iter/s]Best score: 13.6431: : 31iter [00:02, 28.83iter/s]Best score: 13.6431: : 31iter [00:02, 28.83iter/s]Best score: 13.6431: : 32iter [00:02, 28.83iter/s]Best score: 13.6431: : 33iter [00:02, 28.83iter/s]Best score: 13.6431: : 34iter [00:02, 28.83iter/s]Best score: 13.6431: : 35iter [00:02, 31.60iter/s]Best score: 13.6431: : 35iter [00:02, 31.60iter/s]Best score: 13.6431: : 36iter [00:02, 31.60iter/s]Best score: 13.6431: : 37iter [00:02, 31.60iter/s]Best score: 13.6431: : 38iter [00:02, 31.60iter/s]Best score: 13.6431: : 39iter [00:02, 33.76iter/s]Best score: 13.6431: : 39iter [00:02, 33.76iter/s]Best score: 13.6431: : 40iter [00:02, 33.76iter/s]Best score: 13.6431: : 41iter [00:03, 33.76iter/s]Best score: 13.6431: : 42iter [00:03, 33.76iter/s]Best score: 13.6431: : 43iter [00:03, 35.25iter/s]Best score: 13.6431: : 43iter [00:03, 35.25iter/s]Best score: 13.6431: : 44iter [00:03, 35.25iter/s]Best score: 13.6431: : 45iter [00:03, 35.25iter/s]Best score: 13.6431: : 46iter [00:03, 35.25iter/s]Best score: 13.6431: : 47iter [00:03, 35.25iter/s]Best score: 13.6431: : 48iter [00:03, 36.84iter/s]Best score: 13.6431: : 48iter [00:03, 36.84iter/s]
[ITER 50] Best: 13.6431
[PARAMS] Current best parameters:
  fx: 533.3333
  fy: 533.3333
  px: 998.0000
  py: 760.0000
  k1: 0.00000000
  k2: -0.00000000
  k3: 0.00000000
  k4: 0.00000000
  p1: 0.00000000
  p2: 0.00000000
  p3: 0.00000000
  p4: 0.00000000
  s1: 0.0000
  s2: 0.0000
  s3: 0.0000
  s4: 0.0000
  tilt_x: 0.0000
  tilt_y: 0.0000
  scale: 3.0000
  rotation: 0.0000
Best score: 13.6431: : 49iter [00:03, 36.84iter/s]Best score: 13.6431: : 50iter [00:03, 36.84iter/s]Best score: 13.6431: : 51iter [00:03, 36.84iter/s]Best score: 13.6431: : 52iter [00:03, 37.61iter/s]Best score: 13.6431: : 52iter [00:03, 37.61iter/s]Best score: 13.6431: : 53iter [00:03, 37.61iter/s]Best score: 13.6431: : 54iter [00:03, 37.61iter/s]Best score: 13.6431: : 55iter [00:03, 37.61iter/s]Best score: 13.6431: : 56iter [00:03, 37.61iter/s]Best score: 13.6431: : 57iter [00:03, 38.51iter/s]Best score: 13.6431: : 57iter [00:03, 38.51iter/s]Best score: 13.6431: : 58iter [00:03, 38.51iter/s]Best score: 13.6431: : 59iter [00:03, 38.51iter/s]Best score: 13.6431: : 60iter [00:03, 38.51iter/s]Best score: 13.6431: : 61iter [00:03, 38.51iter/s]Best score: 13.6431: : 62iter [00:03, 38.97iter/s]Best score: 13.6431: : 62iter [00:03, 38.97iter/s]Best score: 13.6431: : 63iter [00:03, 38.97iter/s]Best score: 13.6431: : 64iter [00:03, 38.97iter/s]Best score: 13.6431: : 65iter [00:03, 38.97iter/s]Best score: 13.6431: : 66iter [00:03, 38.97iter/s]Best score: 13.6431: : 67iter [00:03, 39.40iter/s]Best score: 13.6431: : 67iter [00:03, 39.40iter/s]Best score: 13.6431: : 68iter [00:03, 39.40iter/s]Best score: 13.6431: : 69iter [00:03, 39.40iter/s]Best score: 13.6431: : 70iter [00:03, 39.40iter/s]Best score: 13.6431: : 71iter [00:03, 39.37iter/s]Best score: 13.6431: : 71iter [00:03, 39.37iter/s]Best score: 13.6431: : 72iter [00:03, 39.37iter/s]Best score: 13.6431: : 73iter [00:03, 39.37iter/s]Best score: 13.6431: : 74iter [00:03, 39.37iter/s]Best score: 13.6431: : 75iter [00:03, 39.37iter/s]Best score: 13.6431: : 76iter [00:03, 39.64iter/s]Best score: 13.6431: : 76iter [00:03, 39.64iter/s]Best score: 13.6431: : 77iter [00:03, 39.64iter/s]Best score: 13.6431: : 78iter [00:03, 39.64iter/s]Best score: 13.6431: : 79iter [00:03, 39.64iter/s]Best score: 13.6431: : 80iter [00:03, 39.64iter/s]Best score: 13.6431: : 80iter [00:03, 39.64iter/s]Best score: 13.6431: : 81iter [00:04, 39.64iter/s]Best score: 13.6431: : 82iter [00:04, 39.64iter/s]Best score: 13.6431: : 83iter [00:04, 39.64iter/s]Best score: 13.6431: : 84iter [00:04, 39.64iter/s]Best score: 13.6431: : 85iter [00:04, 39.84iter/s]Best score: 13.6431: : 85iter [00:04, 39.84iter/s]Best score: 13.6431: : 86iter [00:04, 39.84iter/s]Best score: 13.6431: : 87iter [00:04, 39.84iter/s]Best score: 13.6431: : 88iter [00:04, 39.84iter/s]Best score: 13.6431: : 89iter [00:04, 39.84iter/s]Best score: 13.6431: : 90iter [00:04, 39.92iter/s]Best score: 13.6431: : 90iter [00:04, 39.92iter/s]Best score: 13.6431: : 91iter [00:04, 39.92iter/s]Best score: 13.6431: : 92iter [00:04, 39.92iter/s]Best score: 13.6431: : 93iter [00:04, 39.92iter/s]Best score: 13.6431: : 94iter [00:04, 39.92iter/s]Best score: 13.6431: : 95iter [00:04, 40.23iter/s]Best score: 13.6431: : 95iter [00:04, 40.23iter/s]Best score: 13.6431: : 96iter [00:04, 40.23iter/s]Best score: 13.6431: : 97iter [00:04, 40.23iter/s]Best score: 13.6431: : 98iter [00:04, 40.23iter/s]
[ITER 100] Best: 12.3637
[PARAMS] Current best parameters:
  fx: 531.4529
  fy: 531.7136
  px: 998.0033
  py: 760.3874
  k1: 0.03481677
  k2: -0.02212330
  k3: -0.00067973
  k4: 0.00189283
  p1: -0.00996858
  p2: -0.00141540
  p3: 0.00524471
  p4: 0.00953046
  s1: -0.0064
  s2: -0.0012
  s3: 0.0065
  s4: -0.0086
  tilt_x: 0.0136
  tilt_y: 0.0077
  scale: 2.9133
  rotation: -0.1482
Best score: 12.3637: : 99iter [00:04, 40.23iter/s]Best score: 12.3637: : 100iter [00:04, 40.08iter/s]Best score: 12.3637: : 100iter [00:04, 40.08iter/s]Best score: 12.3637: : 101iter [00:04, 40.08iter/s]Best score: 12.3637: : 102iter [00:04, 40.08iter/s]Best score: 12.3637: : 103iter [00:04, 40.08iter/s]Best score: 12.3637: : 104iter [00:04, 40.08iter/s]Best score: 12.3637: : 105iter [00:04, 37.56iter/s]Best score: 12.3637: : 105iter [00:04, 37.56iter/s]Best score: 12.3637: : 106iter [00:04, 37.56iter/s]Best score: 12.3637: : 107iter [00:04, 37.56iter/s]Best score: 12.3637: : 108iter [00:04, 37.56iter/s]Best score: 12.3637: : 109iter [00:04, 38.06iter/s]Best score: 12.3637: : 109iter [00:04, 38.06iter/s]Best score: 12.3637: : 110iter [00:04, 38.06iter/s]Best score: 12.3637: : 111iter [00:04, 38.06iter/s]Best score: 12.3637: : 112iter [00:04, 38.06iter/s]Best score: 12.3637: : 113iter [00:04, 38.25iter/s]Best score: 12.3637: : 113iter [00:04, 38.25iter/s]Best score: 12.3637: : 114iter [00:04, 38.25iter/s]Best score: 12.3637: : 115iter [00:04, 38.25iter/s]Best score: 12.3637: : 116iter [00:04, 38.25iter/s]Best score: 12.3637: : 117iter [00:04, 38.70iter/s]Best score: 12.3637: : 117iter [00:04, 38.70iter/s]Best score: 12.3637: : 118iter [00:04, 38.70iter/s]Best score: 12.3637: : 119iter [00:04, 38.70iter/s]Best score: 12.3637: : 120iter [00:05, 38.70iter/s]Best score: 12.3637: : 121iter [00:05, 38.63iter/s]Best score: 12.3637: : 121iter [00:05, 38.63iter/s]Best score: 12.3637: : 122iter [00:05, 38.63iter/s]Best score: 12.3637: : 123iter [00:05, 38.63iter/s]Best score: 12.3637: : 124iter [00:05, 38.63iter/s]Best score: 12.3637: : 125iter [00:05, 38.92iter/s]Best score: 12.3637: : 125iter [00:05, 38.92iter/s]Best score: 12.3637: : 126iter [00:05, 38.92iter/s]Best score: 12.3637: : 127iter [00:05, 38.92iter/s]Best score: 12.3637: : 128iter [00:05, 38.92iter/s]Best score: 12.3637: : 129iter [00:05, 38.99iter/s]Best score: 12.3637: : 129iter [00:05, 38.99iter/s]Best score: 12.3637: : 130iter [00:05, 38.99iter/s]Best score: 12.3637: : 131iter [00:05, 38.99iter/s]Best score: 12.3637: : 132iter [00:05, 38.99iter/s]Best score: 12.3637: : 133iter [00:05, 38.76iter/s]Best score: 12.3637: : 133iter [00:05, 38.76iter/s]Best score: 12.3637: : 134iter [00:05, 38.76iter/s]Best score: 12.3637: : 135iter [00:05, 38.76iter/s]Best score: 12.3637: : 136iter [00:05, 38.76iter/s]Best score: 12.3637: : 137iter [00:05, 39.06iter/s]Best score: 12.3637: : 137iter [00:05, 39.06iter/s]Best score: 12.3637: : 138iter [00:05, 39.06iter/s]Best score: 12.3637: : 139iter [00:05, 39.06iter/s]Best score: 12.3637: : 140iter [00:05, 39.06iter/s]Best score: 12.3637: : 141iter [00:05, 39.02iter/s]Best score: 12.3637: : 141iter [00:05, 39.02iter/s]Best score: 12.3637: : 142iter [00:05, 39.02iter/s]Best score: 12.3637: : 143iter [00:05, 39.02iter/s]Best score: 12.3637: : 144iter [00:05, 39.02iter/s]Best score: 12.3637: : 145iter [00:05, 39.29iter/s]Best score: 12.3637: : 145iter [00:05, 39.29iter/s]Best score: 12.3637: : 146iter [00:05, 39.29iter/s]Best score: 12.3637: : 147iter [00:05, 39.29iter/s]Best score: 12.3637: : 148iter [00:05, 39.29iter/s]Best score: 12.3637: : 149iter [00:05, 39.38iter/s]
[ITER 150] Best: 12.3637
[PARAMS] Current best parameters:
  fx: 531.4529
  fy: 531.7136
  px: 998.0033
  py: 760.3874
  k1: 0.03481677
  k2: -0.02212330
  k3: -0.00067973
  k4: 0.00189283
  p1: -0.00996858
  p2: -0.00141540
  p3: 0.00524471
  p4: 0.00953046
  s1: -0.0064
  s2: -0.0012
  s3: 0.0065
  s4: -0.0086
  tilt_x: 0.0136
  tilt_y: 0.0077
  scale: 2.9133
  rotation: -0.1482
Best score: 12.3637: : 149iter [00:05, 39.38iter/s]Best score: 12.3637: : 150iter [00:05, 39.38iter/s]Best score: 12.3637: : 151iter [00:05, 39.38iter/s]Best score: 12.3637: : 152iter [00:05, 39.38iter/s]Best score: 12.3637: : 153iter [00:05, 31.89iter/s]Best score: 12.3637: : 153iter [00:05, 31.89iter/s]Best score: 12.3637: : 154iter [00:05, 31.89iter/s]Best score: 12.3637: : 155iter [00:05, 31.89iter/s]Best score: 12.3637: : 156iter [00:06, 31.89iter/s]Best score: 12.3637: : 157iter [00:06, 33.91iter/s]Best score: 12.3637: : 157iter [00:06, 33.91iter/s]Best score: 12.3637: : 158iter [00:06, 33.91iter/s]Best score: 12.3637: : 159iter [00:06, 33.91iter/s]Best score: 12.3637: : 160iter [00:06, 33.91iter/s]Best score: 12.3637: : 161iter [00:06, 35.31iter/s]Best score: 12.3637: : 161iter [00:06, 35.31iter/s]Best score: 12.3637: : 162iter [00:06, 35.31iter/s]Best score: 12.3637: : 163iter [00:06, 35.31iter/s]Best score: 12.3637: : 164iter [00:06, 35.31iter/s]Best score: 12.3637: : 165iter [00:06, 35.31iter/s]Best score: 12.3637: : 166iter [00:06, 36.92iter/s]Best score: 12.3637: : 166iter [00:06, 36.92iter/s]Best score: 12.3637: : 167iter [00:06, 36.92iter/s]Best score: 12.3637: : 168iter [00:06, 36.92iter/s]Best score: 12.3637: : 169iter [00:06, 36.92iter/s]Best score: 12.3637: : 170iter [00:06, 37.50iter/s]Best score: 12.3637: : 170iter [00:06, 37.50iter/s]Best score: 12.3637: : 171iter [00:06, 37.50iter/s]Best score: 12.3637: : 172iter [00:06, 37.50iter/s]Best score: 12.3637: : 173iter [00:06, 37.50iter/s]Best score: 12.3637: : 174iter [00:06, 37.50iter/s]Best score: 12.3637: : 175iter [00:06, 38.45iter/s]Best score: 12.3637: : 175iter [00:06, 38.45iter/s]Best score: 12.3637: : 176iter [00:06, 38.45iter/s]Best score: 12.3637: : 177iter [00:06, 38.45iter/s]Best score: 12.3637: : 178iter [00:06, 38.45iter/s]Best score: 12.3637: : 179iter [00:06, 38.45iter/s]Best score: 12.3637: : 180iter [00:06, 38.65iter/s]Best score: 12.3637: : 180iter [00:06, 38.65iter/s]Best score: 12.3637: : 181iter [00:06, 38.65iter/s]Best score: 12.3637: : 182iter [00:06, 38.65iter/s]Best score: 12.3637: : 183iter [00:06, 38.65iter/s]Best score: 12.3637: : 184iter [00:06, 38.92iter/s]Best score: 12.3637: : 184iter [00:06, 38.92iter/s]Best score: 12.3637: : 185iter [00:06, 38.92iter/s]Best score: 12.3637: : 186iter [00:06, 38.92iter/s]Best score: 12.3637: : 187iter [00:06, 38.92iter/s]Best score: 12.3637: : 188iter [00:06, 39.00iter/s]Best score: 12.3637: : 188iter [00:06, 39.00iter/s]Best score: 12.3637: : 189iter [00:06, 39.00iter/s]Best score: 12.3637: : 190iter [00:06, 39.00iter/s]Best score: 12.3637: : 191iter [00:06, 39.00iter/s]Best score: 12.3637: : 192iter [00:06, 38.97iter/s]Best score: 12.3637: : 192iter [00:06, 38.97iter/s]Best score: 12.3637: : 193iter [00:06, 38.97iter/s]Best score: 12.3637: : 194iter [00:06, 38.97iter/s]Best score: 12.3637: : 195iter [00:06, 38.97iter/s]Best score: 12.3637: : 196iter [00:07, 38.97iter/s]Best score: 12.3637: : 197iter [00:07, 39.43iter/s]Best score: 12.3637: : 197iter [00:07, 39.43iter/s]Best score: 12.3637: : 198iter [00:07, 39.43iter/s]
[ITER 200] Best: 12.3637
[PARAMS] Current best parameters:
  fx: 531.4529
  fy: 531.7136
  px: 998.0033
  py: 760.3874
  k1: 0.03481677
  k2: -0.02212330
  k3: -0.00067973
  k4: 0.00189283
  p1: -0.00996858
  p2: -0.00141540
  p3: 0.00524471
  p4: 0.00953046
  s1: -0.0064
  s2: -0.0012
  s3: 0.0065
  s4: -0.0086
  tilt_x: 0.0136
  tilt_y: 0.0077
  scale: 2.9133
  rotation: -0.1482
Best score: 12.3637: : 199iter [00:07, 39.43iter/s]Best score: 12.3637: : 200iter [00:07, 39.43iter/s]Best score: 12.3637: : 201iter [00:07, 32.38iter/s]Best score: 12.3637: : 201iter [00:07, 32.38iter/s]Best score: 12.3637: : 202iter [00:07, 32.38iter/s]Best score: 12.3637: : 203iter [00:07, 32.38iter/s]Best score: 12.3637: : 204iter [00:07, 32.38iter/s]Best score: 12.3637: : 205iter [00:07, 32.38iter/s]Best score: 12.3637: : 206iter [00:07, 34.72iter/s]Best score: 12.3637: : 206iter [00:07, 34.72iter/s]Best score: 12.3637: : 207iter [00:07, 34.72iter/s]Best score: 12.3637: : 208iter [00:07, 34.72iter/s]Best score: 12.3637: : 209iter [00:07, 34.72iter/s]Best score: 12.3637: : 210iter [00:07, 35.92iter/s]Best score: 12.3637: : 210iter [00:07, 35.92iter/s]Best score: 12.3637: : 211iter [00:07, 35.92iter/s]Best score: 12.3637: : 212iter [00:07, 35.92iter/s]Best score: 12.3637: : 213iter [00:07, 35.92iter/s]Best score: 12.3637: : 214iter [00:07, 35.92iter/s]Best score: 12.3637: : 215iter [00:07, 37.23iter/s]Best score: 12.3637: : 215iter [00:07, 37.23iter/s]Best score: 12.3637: : 216iter [00:07, 37.23iter/s]Best score: 12.3637: : 217iter [00:07, 37.23iter/s]Best score: 12.3637: : 218iter [00:07, 37.23iter/s]Best score: 12.3637: : 219iter [00:07, 37.23iter/s]Best score: 12.3637: : 220iter [00:07, 37.94iter/s]Best score: 12.3637: : 220iter [00:07, 37.94iter/s]Best score: 12.3637: : 221iter [00:07, 37.94iter/s]Best score: 12.3637: : 222iter [00:07, 37.94iter/s]Best score: 12.3637: : 223iter [00:07, 37.94iter/s]Best score: 12.3637: : 224iter [00:07, 37.94iter/s]Best score: 12.3637: : 225iter [00:07, 38.66iter/s]Best score: 12.3637: : 225iter [00:07, 38.66iter/s]Best score: 12.3637: : 226iter [00:07, 38.66iter/s]Best score: 12.3637: : 227iter [00:07, 38.66iter/s]Best score: 12.3637: : 228iter [00:07, 38.66iter/s]Best score: 12.3637: : 229iter [00:07, 38.66iter/s]Best score: 12.3637: : 230iter [00:07, 39.11iter/s]Best score: 12.3637: : 230iter [00:07, 39.11iter/s]Best score: 12.3637: : 231iter [00:07, 39.11iter/s]Best score: 12.3637: : 232iter [00:07, 39.11iter/s]Best score: 12.3637: : 233iter [00:08, 39.11iter/s]Best score: 12.3637: : 234iter [00:08, 39.11iter/s]Best score: 12.3637: : 235iter [00:08, 39.60iter/s]Best score: 12.3637: : 235iter [00:08, 39.60iter/s]Best score: 12.3637: : 236iter [00:08, 39.60iter/s]Best score: 12.3637: : 237iter [00:08, 39.60iter/s]Best score: 12.3637: : 238iter [00:08, 39.60iter/s]Best score: 12.3637: : 239iter [00:08, 39.60iter/s]Best score: 12.3637: : 240iter [00:08, 39.58iter/s]Best score: 12.3637: : 240iter [00:08, 39.58iter/s]Best score: 12.3637: : 241iter [00:08, 39.58iter/s]Best score: 12.3637: : 242iter [00:08, 39.58iter/s]Best score: 12.3637: : 243iter [00:08, 39.58iter/s]Best score: 12.3637: : 244iter [00:08, 39.58iter/s]Best score: 12.3637: : 245iter [00:08, 39.89iter/s]Best score: 12.3637: : 245iter [00:08, 39.89iter/s]Best score: 12.3637: : 246iter [00:08, 39.89iter/s]Best score: 12.3637: : 247iter [00:08, 39.89iter/s]Best score: 12.3637: : 248iter [00:08, 39.89iter/s]
[ITER 250] Best: 12.3637
[PARAMS] Current best parameters:
  fx: 531.4529
  fy: 531.7136
  px: 998.0033
  py: 760.3874
  k1: 0.03481677
  k2: -0.02212330
  k3: -0.00067973
  k4: 0.00189283
  p1: -0.00996858
  p2: -0.00141540
  p3: 0.00524471
  p4: 0.00953046
  s1: -0.0064
  s2: -0.0012
  s3: 0.0065
  s4: -0.0086
  tilt_x: 0.0136
  tilt_y: 0.0077
  scale: 2.9133
  rotation: -0.1482
Best score: 12.3637: : 249iter [00:08, 39.89iter/s]Best score: 12.3637: : 250iter [00:08, 39.89iter/s]Best score: 12.3637: : 250iter [00:08, 39.89iter/s]Best score: 12.3637: : 251iter [00:08, 39.89iter/s]Best score: 12.3637: : 252iter [00:08, 39.89iter/s]Best score: 12.3637: : 253iter [00:08, 39.89iter/s]Best score: 12.3637: : 254iter [00:08, 33.36iter/s]Best score: 12.3637: : 254iter [00:08, 33.36iter/s]Best score: 12.3637: : 255iter [00:08, 33.36iter/s]Best score: 12.3637: : 256iter [00:08, 33.36iter/s]Best score: 12.3637: : 257iter [00:08, 33.36iter/s]Best score: 12.3637: : 258iter [00:08, 33.36iter/s]Best score: 12.3637: : 259iter [00:08, 35.39iter/s]Best score: 12.3637: : 259iter [00:08, 35.39iter/s]Best score: 12.3637: : 260iter [00:08, 35.39iter/s]Best score: 12.3637: : 261iter [00:08, 35.39iter/s]Best score: 12.3637: : 262iter [00:08, 35.39iter/s]Best score: 12.3637: : 263iter [00:08, 36.44iter/s]Best score: 12.3637: : 263iter [00:08, 36.44iter/s]Best score: 12.3637: : 264iter [00:08, 36.44iter/s]Best score: 12.3637: : 265iter [00:08, 36.44iter/s]Best score: 12.3637: : 266iter [00:08, 36.44iter/s]Best score: 12.3637: : 267iter [00:08, 36.44iter/s]Best score: 12.3637: : 268iter [00:08, 37.59iter/s]Best score: 12.3637: : 268iter [00:08, 37.59iter/s]Best score: 9.8510: : 269iter [00:08, 37.59iter/s] Best score: 9.8510: : 270iter [00:09, 37.59iter/s]Best score: 9.8510: : 271iter [00:09, 37.59iter/s]Best score: 9.8510: : 272iter [00:09, 37.97iter/s]Best score: 9.8510: : 272iter [00:09, 37.97iter/s]Best score: 9.8510: : 273iter [00:09, 37.97iter/s]Best score: 9.8510: : 274iter [00:09, 37.97iter/s]Best score: 9.8510: : 275iter [00:09, 37.97iter/s]Best score: 9.8510: : 276iter [00:09, 37.97iter/s]Best score: 9.8510: : 277iter [00:09, 38.73iter/s]Best score: 9.8510: : 277iter [00:09, 38.73iter/s]Best score: 9.8510: : 278iter [00:09, 38.73iter/s]Best score: 9.8510: : 279iter [00:09, 38.73iter/s]Best score: 9.8510: : 280iter [00:09, 38.73iter/s]Best score: 9.8510: : 281iter [00:09, 38.87iter/s]Best score: 9.8510: : 281iter [00:09, 38.87iter/s]Best score: 9.8510: : 282iter [00:09, 38.87iter/s]Best score: 9.8510: : 283iter [00:09, 38.87iter/s]Best score: 9.8510: : 284iter [00:09, 38.87iter/s]Best score: 9.8510: : 285iter [00:09, 38.87iter/s]Best score: 9.8510: : 286iter [00:09, 39.42iter/s]Best score: 9.8510: : 286iter [00:09, 39.42iter/s]Best score: 9.8510: : 287iter [00:09, 39.42iter/s]Best score: 9.8510: : 288iter [00:09, 39.42iter/s]Best score: 7.6106: : 289iter [00:09, 39.42iter/s]Best score: 7.6106: : 290iter [00:09, 39.52iter/s]Best score: 7.6106: : 290iter [00:09, 39.52iter/s]Best score: 7.6106: : 291iter [00:09, 39.52iter/s]Best score: 7.6106: : 292iter [00:09, 39.52iter/s]Best score: 7.6106: : 293iter [00:09, 39.52iter/s]Best score: 7.6106: : 294iter [00:09, 39.52iter/s]Best score: 7.6106: : 295iter [00:09, 39.99iter/s]Best score: 7.6106: : 295iter [00:09, 39.99iter/s]Best score: 7.6106: : 296iter [00:09, 39.99iter/s]Best score: 7.6106: : 297iter [00:09, 39.99iter/s]Best score: 7.6106: : 298iter [00:09, 39.99iter/s]
[ITER 300] Best: 7.6106
[PARAMS] Current best parameters:
  fx: 515.3180
  fy: 515.4664
  px: 996.1357
  py: 758.2256
  k1: 0.06459799
  k2: -0.02595230
  k3: -0.00963454
  k4: 0.00537417
  p1: -0.00927411
  p2: 0.00336356
  p3: 0.00684830
  p4: 0.00811569
  s1: -0.0292
  s2: 0.0042
  s3: -0.0163
  s4: 0.0021
  tilt_x: 0.0083
  tilt_y: 0.0167
  scale: 2.9124
  rotation: -0.5616
Best score: 7.6106: : 299iter [00:09, 39.99iter/s]Best score: 7.6106: : 300iter [00:09, 39.87iter/s]Best score: 7.6106: : 300iter [00:09, 39.87iter/s]Best score: 7.6106: : 301iter [00:09, 39.87iter/s]Best score: 7.6106: : 302iter [00:09, 39.87iter/s]Best score: 7.6106: : 303iter [00:09, 39.87iter/s]Best score: 7.6106: : 304iter [00:09, 33.23iter/s]Best score: 7.6106: : 304iter [00:09, 33.23iter/s]Best score: 7.6106: : 305iter [00:09, 33.23iter/s]Best score: 7.6106: : 306iter [00:09, 33.23iter/s]Best score: 7.6106: : 307iter [00:10, 33.23iter/s]Best score: 7.6106: : 308iter [00:10, 33.23iter/s]Best score: 7.6106: : 309iter [00:10, 35.29iter/s]Best score: 4.5802: : 309iter [00:10, 35.29iter/s]Best score: 4.5802: : 310iter [00:10, 35.29iter/s]Best score: 4.5802: : 311iter [00:10, 35.29iter/s]Best score: 4.5802: : 312iter [00:10, 35.29iter/s]Best score: 4.5802: : 313iter [00:10, 36.29iter/s]Best score: 4.5802: : 313iter [00:10, 36.29iter/s]Best score: 4.5802: : 314iter [00:10, 36.29iter/s]Best score: 4.5802: : 315iter [00:10, 36.29iter/s]Best score: 4.5802: : 316iter [00:10, 36.29iter/s]Best score: 4.5802: : 317iter [00:10, 36.29iter/s]Best score: 4.5802: : 318iter [00:10, 37.50iter/s]Best score: 4.5802: : 318iter [00:10, 37.50iter/s]Best score: 4.5802: : 319iter [00:10, 37.50iter/s]Best score: 4.5802: : 320iter [00:10, 37.50iter/s]Best score: 4.5802: : 321iter [00:10, 37.50iter/s]Best score: 4.5802: : 322iter [00:10, 37.94iter/s]Best score: 4.5802: : 322iter [00:10, 37.94iter/s]Best score: 4.5802: : 323iter [00:10, 37.94iter/s]Best score: 4.5802: : 324iter [00:10, 37.94iter/s]Best score: 4.5802: : 325iter [00:10, 37.94iter/s]Best score: 4.5802: : 326iter [00:10, 37.94iter/s]Best score: 4.5802: : 327iter [00:10, 38.78iter/s]Best score: 4.5802: : 327iter [00:10, 38.78iter/s]Best score: 4.5802: : 328iter [00:10, 38.78iter/s]Best score: 4.5713: : 329iter [00:10, 38.78iter/s]Best score: 4.5713: : 330iter [00:10, 38.78iter/s]Best score: 4.5713: : 331iter [00:10, 38.91iter/s]Best score: 4.5713: : 331iter [00:10, 38.91iter/s]Best score: 4.5713: : 332iter [00:10, 38.91iter/s]Best score: 4.5713: : 333iter [00:10, 38.91iter/s]Best score: 4.5713: : 334iter [00:10, 38.91iter/s]Best score: 4.5713: : 335iter [00:10, 38.91iter/s]Best score: 4.5713: : 336iter [00:10, 39.28iter/s]Best score: 4.5713: : 336iter [00:10, 39.28iter/s]Best score: 4.5713: : 337iter [00:10, 39.28iter/s]Best score: 4.5713: : 338iter [00:10, 39.28iter/s]Best score: 3.9838: : 339iter [00:10, 39.28iter/s]Best score: 3.9838: : 340iter [00:10, 39.29iter/s]Best score: 3.9838: : 340iter [00:10, 39.29iter/s]Best score: 3.9838: : 341iter [00:10, 39.29iter/s]Best score: 3.9838: : 342iter [00:10, 39.29iter/s]Best score: 3.9838: : 343iter [00:10, 39.29iter/s]Best score: 3.9838: : 344iter [00:10, 39.29iter/s]Best score: 3.9838: : 345iter [00:10, 39.75iter/s]Best score: 3.9838: : 345iter [00:10, 39.75iter/s]Best score: 3.9838: : 346iter [00:10, 39.75iter/s]Best score: 3.9838: : 347iter [00:11, 39.75iter/s]Best score: 3.9838: : 348iter [00:11, 39.75iter/s]
[ITER 350] Best: 3.3035
[PARAMS] Current best parameters:
  fx: 526.1394
  fy: 525.3412
  px: 1008.7365
  py: 762.6551
  k1: 0.05255325
  k2: -0.06031106
  k3: 0.02993038
  k4: -0.00581545
  p1: 0.00082248
  p2: 0.01313743
  p3: 0.00586132
  p4: -0.00161983
  s1: -0.0098
  s2: 0.0021
  s3: 0.0033
  s4: -0.0002
  tilt_x: 0.0016
  tilt_y: -0.0200
  scale: 2.9440
  rotation: -0.6607
Best score: 3.3035: : 349iter [00:11, 39.75iter/s]Best score: 3.3035: : 350iter [00:11, 39.71iter/s]Best score: 3.3035: : 350iter [00:11, 39.71iter/s]Best score: 3.3035: : 351iter [00:11, 39.71iter/s]Best score: 3.3035: : 352iter [00:11, 39.71iter/s]Best score: 3.3035: : 353iter [00:11, 39.71iter/s]Best score: 3.3035: : 354iter [00:11, 33.03iter/s]Best score: 3.3035: : 354iter [00:11, 33.03iter/s]Best score: 3.3035: : 355iter [00:11, 33.03iter/s]Best score: 3.3035: : 356iter [00:11, 33.03iter/s]Best score: 3.3035: : 357iter [00:11, 33.03iter/s]Best score: 3.3035: : 358iter [00:11, 33.03iter/s]Best score: 3.3035: : 359iter [00:11, 34.87iter/s]Best score: 3.3035: : 359iter [00:11, 34.87iter/s]Best score: 3.3035: : 360iter [00:11, 34.87iter/s]Best score: 3.3035: : 361iter [00:11, 34.87iter/s]Best score: 3.3035: : 362iter [00:11, 34.87iter/s]Best score: 3.3035: : 363iter [00:11, 28.78iter/s]Best score: 3.3035: : 363iter [00:11, 28.78iter/s]Best score: 3.3035: : 364iter [00:11, 28.78iter/s]Best score: 3.3035: : 365iter [00:11, 28.78iter/s]Best score: 3.3035: : 366iter [00:11, 28.78iter/s]Best score: 3.3035: : 367iter [00:11, 28.78iter/s]Best score: 3.3035: : 368iter [00:11, 31.67iter/s]Best score: 3.3035: : 368iter [00:11, 31.67iter/s]Best score: 3.3035: : 369iter [00:11, 31.67iter/s]Best score: 3.3035: : 370iter [00:11, 31.67iter/s]Best score: 3.3035: : 371iter [00:11, 31.67iter/s]Best score: 3.3035: : 372iter [00:11, 33.44iter/s]Best score: 3.3035: : 372iter [00:11, 33.44iter/s]Best score: 3.3035: : 373iter [00:11, 33.44iter/s]Best score: 3.3035: : 374iter [00:11, 33.44iter/s]Best score: 3.3035: : 375iter [00:11, 33.44iter/s]Best score: 3.3035: : 376iter [00:11, 33.44iter/s]Best score: 3.3035: : 377iter [00:11, 35.48iter/s]Best score: 3.3035: : 377iter [00:11, 35.48iter/s]Best score: 3.3035: : 378iter [00:11, 35.48iter/s]Best score: 2.6428: : 379iter [00:12, 35.48iter/s]Best score: 2.6428: : 380iter [00:12, 35.48iter/s]Best score: 2.6428: : 381iter [00:12, 36.52iter/s]Best score: 2.6428: : 381iter [00:12, 36.52iter/s]Best score: 2.6428: : 382iter [00:12, 36.52iter/s]Best score: 2.6428: : 383iter [00:12, 36.52iter/s]Best score: 2.6428: : 384iter [00:12, 36.52iter/s]Best score: 2.6428: : 385iter [00:12, 36.52iter/s]Best score: 2.6428: : 386iter [00:12, 37.76iter/s]Best score: 2.6428: : 386iter [00:12, 37.76iter/s]Best score: 2.6428: : 387iter [00:12, 37.76iter/s]Best score: 2.6428: : 388iter [00:12, 37.76iter/s]Best score: 2.2824: : 389iter [00:12, 37.76iter/s]Best score: 2.2824: : 390iter [00:12, 38.32iter/s]Best score: 2.2824: : 390iter [00:12, 38.32iter/s]Best score: 2.2824: : 391iter [00:12, 38.32iter/s]Best score: 2.2824: : 392iter [00:12, 38.32iter/s]Best score: 2.2824: : 393iter [00:12, 38.32iter/s]Best score: 2.2824: : 394iter [00:12, 38.32iter/s]Best score: 2.2824: : 395iter [00:12, 39.08iter/s]Best score: 2.2824: : 395iter [00:12, 39.08iter/s]Best score: 2.2824: : 396iter [00:12, 39.08iter/s]Best score: 2.2824: : 397iter [00:12, 39.08iter/s]Best score: 2.2824: : 398iter [00:12, 39.08iter/s]
[ITER 400] Best: 2.2824
[PARAMS] Current best parameters:
  fx: 522.0235
  fy: 521.9542
  px: 1004.3555
  py: 758.9688
  k1: 0.05252510
  k2: -0.02686807
  k3: -0.00011121
  k4: 0.00126297
  p1: -0.00222971
  p2: 0.01844906
  p3: 0.01181900
  p4: -0.00805160
  s1: -0.0166
  s2: 0.0047
  s3: -0.0042
  s4: 0.0043
  tilt_x: -0.0025
  tilt_y: 0.0142
  scale: 2.9095
  rotation: -0.5004
Best score: 2.2824: : 399iter [00:12, 39.08iter/s]Best score: 2.2824: : 400iter [00:12, 39.12iter/s]Best score: 2.2824: : 400iter [00:12, 39.12iter/s]Best score: 2.2824: : 401iter [00:12, 39.12iter/s]Best score: 2.2824: : 402iter [00:12, 39.12iter/s]Best score: 2.2824: : 403iter [00:12, 39.12iter/s]Best score: 2.2824: : 404iter [00:12, 32.65iter/s]Best score: 2.2824: : 404iter [00:12, 32.65iter/s]Best score: 2.2824: : 405iter [00:12, 32.65iter/s]Best score: 2.2824: : 406iter [00:12, 32.65iter/s]Best score: 2.2824: : 407iter [00:12, 32.65iter/s]Best score: 2.2824: : 408iter [00:12, 32.65iter/s]Best score: 2.2824: : 409iter [00:12, 34.83iter/s]Best score: 1.5317: : 409iter [00:12, 34.83iter/s]Best score: 1.5317: : 410iter [00:12, 34.83iter/s]Best score: 1.5317: : 411iter [00:12, 34.83iter/s]Best score: 1.5317: : 412iter [00:12, 34.83iter/s]Best score: 1.5317: : 413iter [00:12, 35.99iter/s]Best score: 1.5317: : 413iter [00:12, 35.99iter/s]Best score: 1.5317: : 414iter [00:12, 35.99iter/s]Best score: 1.5317: : 415iter [00:12, 35.99iter/s]Best score: 1.5317: : 416iter [00:13, 35.99iter/s]Best score: 1.5317: : 417iter [00:13, 35.99iter/s]Best score: 1.5317: : 418iter [00:13, 37.28iter/s]Best score: 1.5317: : 418iter [00:13, 37.28iter/s]Best score: 1.5317: : 419iter [00:13, 37.28iter/s]Best score: 1.5317: : 420iter [00:13, 37.28iter/s]Best score: 1.5317: : 421iter [00:13, 37.28iter/s]Best score: 1.5317: : 422iter [00:13, 37.71iter/s]Best score: 1.5317: : 422iter [00:13, 37.71iter/s]Best score: 1.5317: : 423iter [00:13, 37.71iter/s]Best score: 1.5317: : 424iter [00:13, 37.71iter/s]Best score: 1.5317: : 425iter [00:13, 37.71iter/s]Best score: 1.5317: : 426iter [00:13, 38.27iter/s]Best score: 1.5317: : 426iter [00:13, 38.27iter/s]Best score: 1.5317: : 427iter [00:13, 38.27iter/s]Best score: 1.5317: : 428iter [00:13, 38.27iter/s]Best score: 1.5317: : 429iter [00:13, 38.27iter/s]Best score: 1.5317: : 430iter [00:13, 38.56iter/s]Best score: 1.5317: : 430iter [00:13, 38.56iter/s]Best score: 1.5317: : 431iter [00:13, 38.56iter/s]Best score: 1.5317: : 432iter [00:13, 38.56iter/s]Best score: 1.5317: : 433iter [00:13, 38.56iter/s]Best score: 1.5317: : 434iter [00:13, 38.56iter/s]Best score: 1.5317: : 435iter [00:13, 39.13iter/s]Best score: 1.5317: : 435iter [00:13, 39.13iter/s]Best score: 1.5317: : 436iter [00:13, 39.13iter/s]Best score: 1.5317: : 437iter [00:13, 39.13iter/s]Best score: 1.5317: : 438iter [00:13, 39.13iter/s]Best score: 1.2731: : 439iter [00:13, 39.13iter/s]Best score: 1.2731: : 440iter [00:13, 39.34iter/s]Best score: 1.2731: : 440iter [00:13, 39.34iter/s]Best score: 1.2731: : 441iter [00:13, 39.34iter/s]Best score: 1.2731: : 442iter [00:13, 39.34iter/s]Best score: 1.2731: : 443iter [00:13, 39.34iter/s]Best score: 1.2731: : 444iter [00:13, 39.34iter/s]Best score: 1.2731: : 445iter [00:13, 39.60iter/s]Best score: 1.2731: : 445iter [00:13, 39.60iter/s]Best score: 1.2731: : 446iter [00:13, 39.60iter/s]Best score: 1.2731: : 447iter [00:13, 39.60iter/s]Best score: 1.2731: : 448iter [00:13, 39.60iter/s]
[ITER 450] Best: 1.2731
[PARAMS] Current best parameters:
  fx: 510.5758
  fy: 509.5913
  px: 1006.0523
  py: 758.2895
  k1: 0.05929995
  k2: -0.04779257
  k3: 0.02046545
  k4: -0.00355119
  p1: -0.00968172
  p2: 0.00870716
  p3: 0.01501794
  p4: -0.00512350
  s1: -0.0110
  s2: 0.0001
  s3: 0.0012
  s4: 0.0021
  tilt_x: 0.0028
  tilt_y: -0.0165
  scale: 3.0077
  rotation: -0.6110
Best score: 1.2731: : 449iter [00:13, 39.60iter/s]Best score: 1.2731: : 450iter [00:13, 39.47iter/s]Best score: 1.2731: : 450iter [00:13, 39.47iter/s]Best score: 1.2731: : 451iter [00:13, 39.47iter/s]Best score: 1.2731: : 452iter [00:13, 39.47iter/s]Best score: 1.2731: : 453iter [00:14, 39.47iter/s]Best score: 1.2731: : 454iter [00:14, 32.95iter/s]Best score: 1.2731: : 454iter [00:14, 32.95iter/s]Best score: 1.2731: : 455iter [00:14, 32.95iter/s]Best score: 1.2731: : 456iter [00:14, 32.95iter/s]Best score: 1.2731: : 457iter [00:14, 32.95iter/s]Best score: 1.2731: : 458iter [00:14, 32.95iter/s]Best score: 1.2731: : 459iter [00:14, 35.04iter/s]Best score: 0.8370: : 459iter [00:14, 35.04iter/s]Best score: 0.8370: : 460iter [00:14, 35.04iter/s]Best score: 0.8370: : 461iter [00:14, 35.04iter/s]Best score: 0.8370: : 462iter [00:14, 35.04iter/s]Best score: 0.8370: : 463iter [00:14, 36.04iter/s]Best score: 0.8370: : 463iter [00:14, 36.04iter/s]Best score: 0.8370: : 464iter [00:14, 36.04iter/s]Best score: 0.8370: : 465iter [00:14, 36.04iter/s]Best score: 0.8370: : 466iter [00:14, 36.04iter/s]Best score: 0.8370: : 467iter [00:14, 36.04iter/s]Best score: 0.8370: : 468iter [00:14, 37.06iter/s]Best score: 0.8370: : 468iter [00:14, 37.06iter/s]Best score: 0.7558: : 469iter [00:14, 37.06iter/s]Best score: 0.7558: : 470iter [00:14, 37.06iter/s]Best score: 0.7558: : 471iter [00:14, 37.06iter/s]Best score: 0.7558: : 472iter [00:14, 37.72iter/s]Best score: 0.7558: : 472iter [00:14, 37.72iter/s]Best score: 0.7558: : 473iter [00:14, 37.72iter/s]Best score: 0.7558: : 474iter [00:14, 37.72iter/s]Best score: 0.7558: : 475iter [00:14, 37.72iter/s]Best score: 0.7558: : 476iter [00:14, 37.72iter/s]Best score: 0.7558: : 477iter [00:14, 38.44iter/s]Best score: 0.7558: : 477iter [00:14, 38.44iter/s]Best score: 0.7558: : 478iter [00:14, 38.44iter/s]Best score: 0.7558: : 479iter [00:14, 38.44iter/s]Best score: 0.7558: : 480iter [00:14, 38.44iter/s]Best score: 0.7558: : 481iter [00:14, 38.60iter/s]Best score: 0.7558: : 481iter [00:14, 38.60iter/s]Best score: 0.7558: : 482iter [00:14, 38.60iter/s]Best score: 0.7558: : 483iter [00:14, 38.60iter/s]Best score: 0.7558: : 484iter [00:14, 38.60iter/s]Best score: 0.7558: : 485iter [00:14, 38.60iter/s]Best score: 0.7558: : 486iter [00:14, 39.18iter/s]Best score: 0.7558: : 486iter [00:14, 39.18iter/s]Best score: 0.7558: : 487iter [00:14, 39.18iter/s]Best score: 0.7558: : 488iter [00:14, 39.18iter/s]Best score: 0.7558: : 489iter [00:14, 39.18iter/s]Best score: 0.7558: : 490iter [00:14, 39.19iter/s]Best score: 0.7558: : 490iter [00:14, 39.19iter/s]Best score: 0.7558: : 491iter [00:14, 39.19iter/s]Best score: 0.7558: : 492iter [00:14, 39.19iter/s]Best score: 0.7558: : 493iter [00:15, 39.19iter/s]Best score: 0.7558: : 494iter [00:15, 39.19iter/s]Best score: 0.7558: : 495iter [00:15, 39.66iter/s]Best score: 0.7558: : 495iter [00:15, 39.66iter/s]Best score: 0.7558: : 496iter [00:15, 39.66iter/s]Best score: 0.7558: : 497iter [00:15, 39.66iter/s]Best score: 0.7558: : 498iter [00:15, 39.66iter/s]
[ITER 500] Best: 0.7553
[PARAMS] Current best parameters:
  fx: 508.2556
  fy: 507.8161
  px: 1006.6601
  py: 757.9876
  k1: 0.07347000
  k2: -0.05973128
  k3: 0.02763094
  k4: -0.00573693
  p1: -0.00885437
  p2: 0.00753153
  p3: 0.01100993
  p4: -0.00226445
  s1: -0.0089
  s2: -0.0002
  s3: -0.0002
  s4: 0.0008
  tilt_x: 0.0004
  tilt_y: -0.0196
  scale: 2.9622
  rotation: -0.6184
Best score: 0.7553: : 499iter [00:15, 39.66iter/s]Best score: 0.7553: : 500iter [00:15, 39.61iter/s]Best score: 0.7553: : 500iter [00:15, 39.61iter/s]Best score: 0.7553: : 501iter [00:15, 39.61iter/s]Best score: 0.7553: : 502iter [00:15, 39.61iter/s]Best score: 0.7553: : 503iter [00:15, 39.61iter/s]Best score: 0.7553: : 504iter [00:15, 32.81iter/s]Best score: 0.7553: : 504iter [00:15, 32.81iter/s]Best score: 0.7553: : 505iter [00:15, 32.81iter/s]Best score: 0.7553: : 506iter [00:15, 32.81iter/s]Best score: 0.7553: : 507iter [00:15, 32.81iter/s]Best score: 0.7553: : 508iter [00:15, 32.81iter/s]Best score: 0.7553: : 509iter [00:15, 34.94iter/s]Best score: 0.6511: : 509iter [00:15, 34.94iter/s]Best score: 0.6511: : 510iter [00:15, 34.94iter/s]Best score: 0.6511: : 511iter [00:15, 34.94iter/s]Best score: 0.6511: : 512iter [00:15, 34.94iter/s]Best score: 0.6511: : 513iter [00:15, 36.10iter/s]Best score: 0.6511: : 513iter [00:15, 36.10iter/s]Best score: 0.6511: : 514iter [00:15, 36.10iter/s]Best score: 0.6511: : 515iter [00:15, 36.10iter/s]Best score: 0.6511: : 516iter [00:15, 36.10iter/s]Best score: 0.6511: : 517iter [00:15, 36.10iter/s]Best score: 0.6511: : 518iter [00:15, 37.39iter/s]Best score: 0.6511: : 518iter [00:15, 37.39iter/s]Best score: 0.5197: : 519iter [00:15, 37.39iter/s]Best score: 0.5197: : 520iter [00:15, 37.39iter/s]Best score: 0.5197: : 521iter [00:15, 37.39iter/s]Best score: 0.5197: : 522iter [00:15, 37.90iter/s]Best score: 0.5197: : 522iter [00:15, 37.90iter/s]Best score: 0.5197: : 523iter [00:15, 37.90iter/s]Best score: 0.5197: : 524iter [00:15, 37.90iter/s]Best score: 0.5197: : 525iter [00:15, 37.90iter/s]Best score: 0.5197: : 526iter [00:15, 37.90iter/s]Best score: 0.5197: : 527iter [00:15, 38.85iter/s]Best score: 0.5197: : 527iter [00:15, 38.85iter/s]Best score: 0.5197: : 528iter [00:15, 38.85iter/s]Best score: 0.5197: : 529iter [00:16, 38.85iter/s]Best score: 0.5197: : 530iter [00:16, 38.85iter/s]Best score: 0.5197: : 531iter [00:16, 39.04iter/s]Best score: 0.5197: : 531iter [00:16, 39.04iter/s]Best score: 0.5197: : 532iter [00:16, 39.04iter/s]Best score: 0.5197: : 533iter [00:16, 39.04iter/s]Best score: 0.5197: : 534iter [00:16, 39.04iter/s]Best score: 0.5197: : 535iter [00:16, 39.04iter/s]Best score: 0.5197: : 536iter [00:16, 39.59iter/s]Best score: 0.5197: : 536iter [00:16, 39.59iter/s]Best score: 0.5197: : 537iter [00:16, 39.59iter/s]Best score: 0.5197: : 538iter [00:16, 39.59iter/s]Best score: 0.5197: : 539iter [00:16, 39.59iter/s]Best score: 0.5197: : 540iter [00:16, 39.57iter/s]Best score: 0.5197: : 540iter [00:16, 39.57iter/s]Best score: 0.5197: : 541iter [00:16, 39.57iter/s]Best score: 0.5197: : 542iter [00:16, 39.57iter/s]Best score: 0.5197: : 543iter [00:16, 39.57iter/s]Best score: 0.5197: : 544iter [00:16, 39.57iter/s]Best score: 0.5197: : 545iter [00:16, 39.93iter/s]Best score: 0.5197: : 545iter [00:16, 39.93iter/s]Best score: 0.5197: : 546iter [00:16, 39.93iter/s]Best score: 0.5197: : 547iter [00:16, 39.93iter/s]Best score: 0.5197: : 548iter [00:16, 39.93iter/s]
[ITER 550] Best: 0.5197
[PARAMS] Current best parameters:
  fx: 501.7158
  fy: 500.7230
  px: 999.9791
  py: 755.6457
  k1: 0.06712904
  k2: -0.04664334
  k3: 0.02367034
  k4: -0.00555359
  p1: -0.01580726
  p2: -0.00109605
  p3: 0.00244773
  p4: 0.00231138
  s1: 0.0020
  s2: -0.0037
  s3: 0.0127
  s4: -0.0033
  tilt_x: 0.0030
  tilt_y: -0.0064
  scale: 2.9912
  rotation: -0.5865
Best score: 0.5197: : 549iter [00:16, 39.93iter/s]Best score: 0.5197: : 550iter [00:16, 39.86iter/s]
[Periodic outlier @ iter 450] Removing 1000 frame 5 (score=3.27, threshold=2.81)
  Remaining frames: 19
Best score: 0.5197: : 550iter [00:16, 39.86iter/s]Best score: 0.5197: : 551iter [00:16, 39.86iter/s]Best score: 0.5197: : 552iter [00:16, 39.86iter/s]Best score: 0.5197: : 553iter [00:16, 39.86iter/s]Best score: 0.5197: : 554iter [00:16, 30.70iter/s]Best score: 0.5197: : 554iter [00:16, 30.70iter/s]Best score: 0.5197: : 555iter [00:16, 30.70iter/s]Best score: 0.5197: : 556iter [00:16, 30.70iter/s]Best score: 0.5197: : 557iter [00:16, 30.70iter/s]Best score: 0.5197: : 558iter [00:16, 30.70iter/s]Best score: 0.5197: : 559iter [00:16, 33.40iter/s]Best score: 0.3742: : 559iter [00:16, 33.40iter/s]Best score: 0.3742: : 560iter [00:16, 33.40iter/s]Best score: 0.3742: : 561iter [00:16, 33.40iter/s]Best score: 0.3742: : 562iter [00:16, 33.40iter/s]Best score: 0.3742: : 563iter [00:16, 33.40iter/s]Best score: 0.3742: : 564iter [00:16, 35.36iter/s]Best score: 0.3742: : 564iter [00:16, 35.36iter/s]Best score: 0.3742: : 565iter [00:17, 35.36iter/s]Best score: 0.3742: : 566iter [00:17, 35.36iter/s]Best score: 0.3742: : 567iter [00:17, 35.36iter/s]Best score: 0.3742: : 568iter [00:17, 35.36iter/s]Best score: 0.3742: : 569iter [00:17, 36.97iter/s]Best score: 0.3742: : 569iter [00:17, 36.97iter/s]Best score: 0.3742: : 570iter [00:17, 36.97iter/s]Best score: 0.3742: : 571iter [00:17, 36.97iter/s]Best score: 0.3742: : 572iter [00:17, 36.97iter/s]Best score: 0.3742: : 573iter [00:17, 36.97iter/s]Best score: 0.3742: : 574iter [00:17, 38.08iter/s]Best score: 0.3742: : 574iter [00:17, 38.08iter/s]Best score: 0.3742: : 575iter [00:17, 38.08iter/s]Best score: 0.3742: : 576iter [00:17, 38.08iter/s]Best score: 0.3742: : 577iter [00:17, 38.08iter/s]Best score: 0.3742: : 578iter [00:17, 38.10iter/s]Best score: 0.3742: : 578iter [00:17, 38.10iter/s]Best score: 0.3742: : 579iter [00:17, 38.10iter/s]Best score: 0.3742: : 580iter [00:17, 38.10iter/s]Best score: 0.3742: : 581iter [00:17, 38.10iter/s]Best score: 0.3742: : 582iter [00:17, 38.10iter/s]Best score: 0.3742: : 583iter [00:17, 38.87iter/s]Best score: 0.3742: : 583iter [00:17, 38.87iter/s]Best score: 0.3742: : 584iter [00:17, 38.87iter/s]Best score: 0.3742: : 585iter [00:17, 38.87iter/s]Best score: 0.3742: : 586iter [00:17, 38.87iter/s]Best score: 0.3742: : 587iter [00:17, 38.87iter/s]Best score: 0.3742: : 588iter [00:17, 39.52iter/s]Best score: 0.3742: : 588iter [00:17, 39.52iter/s]Best score: 0.3742: : 589iter [00:17, 39.52iter/s]Best score: 0.3742: : 590iter [00:17, 39.52iter/s]Best score: 0.3742: : 591iter [00:17, 39.52iter/s]Best score: 0.3742: : 592iter [00:17, 39.52iter/s]Best score: 0.3742: : 593iter [00:17, 39.92iter/s]Best score: 0.3742: : 593iter [00:17, 39.92iter/s]Best score: 0.3742: : 594iter [00:17, 39.92iter/s]Best score: 0.3742: : 595iter [00:17, 39.92iter/s]Best score: 0.3742: : 596iter [00:17, 39.92iter/s]Best score: 0.3742: : 597iter [00:17, 39.92iter/s]Best score: 0.3742: : 598iter [00:17, 40.53iter/s]Best score: 0.3742: : 598iter [00:17, 40.53iter/s]
[ITER 600] Best: 0.3742
[PARAMS] Current best parameters:
  fx: 501.7158
  fy: 500.7230
  px: 999.9791
  py: 755.6457
  k1: 0.06712904
  k2: -0.04664334
  k3: 0.02367034
  k4: -0.00555359
  p1: -0.01580726
  p2: -0.00109605
  p3: 0.00244773
  p4: 0.00231138
  s1: 0.0020
  s2: -0.0037
  s3: 0.0127
  s4: -0.0033
  tilt_x: 0.0030
  tilt_y: -0.0064
  scale: 2.9912
  rotation: -0.5865
Best score: 0.3742: : 599iter [00:17, 40.53iter/s]Best score: 0.3742: : 600iter [00:17, 40.53iter/s]Best score: 0.3742: : 601iter [00:17, 40.53iter/s]Best score: 0.3742: : 602iter [00:17, 40.53iter/s]Best score: 0.3742: : 603iter [00:17, 34.11iter/s]Best score: 0.3742: : 603iter [00:18, 34.11iter/s]Best score: 0.3742: : 604iter [00:18, 34.11iter/s]Best score: 0.3742: : 605iter [00:18, 34.11iter/s]Best score: 0.3742: : 606iter [00:18, 34.11iter/s]Best score: 0.3742: : 607iter [00:18, 34.11iter/s]Best score: 0.3742: : 608iter [00:18, 35.97iter/s]Best score: 0.3742: : 608iter [00:18, 35.97iter/s]Best score: 0.3742: : 609iter [00:18, 35.97iter/s]Best score: 0.3742: : 610iter [00:18, 35.97iter/s]Best score: 0.3742: : 611iter [00:18, 35.97iter/s]Best score: 0.3742: : 612iter [00:18, 35.97iter/s]Best score: 0.3742: : 613iter [00:18, 37.27iter/s]Best score: 0.3742: : 613iter [00:18, 37.27iter/s]Best score: 0.3742: : 614iter [00:18, 37.27iter/s]Best score: 0.3742: : 615iter [00:18, 37.27iter/s]Best score: 0.3742: : 616iter [00:18, 37.27iter/s]Best score: 0.3742: : 617iter [00:18, 37.27iter/s]Best score: 0.3742: : 618iter [00:18, 38.66iter/s]Best score: 0.3742: : 618iter [00:18, 38.66iter/s]Best score: 0.3742: : 619iter [00:18, 38.66iter/s]Best score: 0.3742: : 620iter [00:18, 38.66iter/s]Best score: 0.3742: : 621iter [00:18, 38.66iter/s]Best score: 0.3742: : 622iter [00:18, 38.66iter/s]Best score: 0.3742: : 623iter [00:18, 39.38iter/s]Best score: 0.3742: : 623iter [00:18, 39.38iter/s]Best score: 0.3742: : 624iter [00:18, 39.38iter/s]Best score: 0.3742: : 625iter [00:18, 39.38iter/s]Best score: 0.3742: : 626iter [00:18, 39.38iter/s]Best score: 0.3742: : 627iter [00:18, 39.38iter/s]Best score: 0.3742: : 628iter [00:18, 40.20iter/s]Best score: 0.3742: : 628iter [00:18, 40.20iter/s]Best score: 0.3742: : 629iter [00:18, 40.20iter/s]Best score: 0.3742: : 630iter [00:18, 40.20iter/s]Best score: 0.3742: : 631iter [00:18, 40.20iter/s]Best score: 0.3742: : 632iter [00:18, 40.20iter/s]Best score: 0.3742: : 633iter [00:18, 40.49iter/s]Best score: 0.3742: : 633iter [00:18, 40.49iter/s]Best score: 0.3742: : 634iter [00:18, 40.49iter/s]Best score: 0.3742: : 635iter [00:18, 40.49iter/s]Best score: 0.3742: : 636iter [00:18, 40.49iter/s]Best score: 0.3742: : 637iter [00:18, 40.49iter/s]Best score: 0.3742: : 638iter [00:18, 40.96iter/s]Best score: 0.3742: : 638iter [00:18, 40.96iter/s]Best score: 0.3742: : 639iter [00:18, 40.96iter/s]Best score: 0.3742: : 640iter [00:18, 40.96iter/s]Best score: 0.3742: : 641iter [00:18, 40.96iter/s]Best score: 0.3742: : 642iter [00:18, 40.96iter/s]Best score: 0.3742: : 643iter [00:18, 41.18iter/s]Best score: 0.3742: : 643iter [00:18, 41.18iter/s]Best score: 0.3742: : 644iter [00:19, 41.18iter/s]Best score: 0.3742: : 645iter [00:19, 41.18iter/s]Best score: 0.3742: : 646iter [00:19, 41.18iter/s]Best score: 0.3742: : 647iter [00:19, 41.18iter/s]Best score: 0.3742: : 648iter [00:19, 41.51iter/s]Best score: 0.3742: : 648iter [00:19, 41.51iter/s]
[ITER 650] Best: 0.3742
[PARAMS] Current best parameters:
  fx: 501.7158
  fy: 500.7230
  px: 999.9791
  py: 755.6457
  k1: 0.06712904
  k2: -0.04664334
  k3: 0.02367034
  k4: -0.00555359
  p1: -0.01580726
  p2: -0.00109605
  p3: 0.00244773
  p4: 0.00231138
  s1: 0.0020
  s2: -0.0037
  s3: 0.0127
  s4: -0.0033
  tilt_x: 0.0030
  tilt_y: -0.0064
  scale: 2.9912
  rotation: -0.5865
Best score: 0.3742: : 649iter [00:19, 41.51iter/s]Best score: 0.3742: : 650iter [00:19, 41.51iter/s]Best score: 0.3742: : 651iter [00:19, 41.51iter/s]Best score: 0.3742: : 652iter [00:19, 41.51iter/s]Best score: 0.3742: : 653iter [00:19, 34.86iter/s]Best score: 0.3742: : 653iter [00:19, 34.86iter/s]Best score: 0.3742: : 654iter [00:19, 34.86iter/s]Best score: 0.3742: : 655iter [00:19, 34.86iter/s]Best score: 0.3742: : 656iter [00:19, 34.86iter/s]Best score: 0.3742: : 657iter [00:19, 34.86iter/s]Best score: 0.3742: : 658iter [00:19, 36.91iter/s]Best score: 0.3742: : 658iter [00:19, 36.91iter/s]Best score: 0.3742: : 659iter [00:19, 36.91iter/s]Best score: 0.3742: : 660iter [00:19, 36.91iter/s]Best score: 0.3742: : 661iter [00:19, 36.91iter/s]Best score: 0.3742: : 662iter [00:19, 36.91iter/s]Best score: 0.3742: : 663iter [00:19, 38.17iter/s]Best score: 0.3742: : 663iter [00:19, 38.17iter/s]Best score: 0.3742: : 664iter [00:19, 38.17iter/s]Best score: 0.3742: : 665iter [00:19, 38.17iter/s]Best score: 0.3742: : 666iter [00:19, 38.17iter/s]Best score: 0.3742: : 667iter [00:19, 38.17iter/s]Best score: 0.3742: : 668iter [00:19, 39.37iter/s]Best score: 0.3742: : 668iter [00:19, 39.37iter/s]Best score: 0.3742: : 669iter [00:19, 39.37iter/s]Best score: 0.3742: : 670iter [00:19, 39.37iter/s]Best score: 0.3742: : 671iter [00:19, 39.37iter/s]Best score: 0.3742: : 672iter [00:19, 39.37iter/s]Best score: 0.3742: : 673iter [00:19, 39.95iter/s]Best score: 0.3742: : 673iter [00:19, 39.95iter/s]Best score: 0.3742: : 674iter [00:19, 39.95iter/s]Best score: 0.3742: : 675iter [00:19, 39.95iter/s]Best score: 0.3742: : 676iter [00:19, 39.95iter/s]Best score: 0.3742: : 677iter [00:19, 39.95iter/s]Best score: 0.3742: : 678iter [00:19, 40.69iter/s]Best score: 0.3742: : 678iter [00:19, 40.69iter/s]Best score: 0.3742: : 679iter [00:19, 40.69iter/s]Best score: 0.3742: : 680iter [00:19, 40.69iter/s]Best score: 0.3742: : 681iter [00:19, 40.69iter/s]Best score: 0.3742: : 682iter [00:20, 40.69iter/s]Best score: 0.3742: : 683iter [00:20, 32.70iter/s]Best score: 0.3742: : 683iter [00:20, 32.70iter/s]Best score: 0.3742: : 684iter [00:20, 32.70iter/s]Best score: 0.3742: : 685iter [00:20, 32.70iter/s]Best score: 0.3742: : 686iter [00:20, 32.70iter/s]Best score: 0.3742: : 687iter [00:20, 32.70iter/s]Best score: 0.3742: : 688iter [00:20, 35.11iter/s]Best score: 0.3742: : 688iter [00:20, 35.11iter/s]Best score: 0.3742: : 689iter [00:20, 35.11iter/s]Best score: 0.3742: : 690iter [00:20, 35.11iter/s]Best score: 0.3742: : 691iter [00:20, 35.11iter/s]Best score: 0.3742: : 692iter [00:20, 35.11iter/s]Best score: 0.3742: : 693iter [00:20, 36.77iter/s]Best score: 0.3742: : 693iter [00:20, 36.77iter/s]Best score: 0.3742: : 694iter [00:20, 36.77iter/s]Best score: 0.3742: : 695iter [00:20, 36.77iter/s]Best score: 0.3742: : 696iter [00:20, 36.77iter/s]Best score: 0.3742: : 697iter [00:20, 36.77iter/s]Best score: 0.3742: : 698iter [00:20, 38.33iter/s]Best score: 0.3742: : 698iter [00:20, 38.33iter/s]
[ITER 700] Best: 0.3742
[PARAMS] Current best parameters:
  fx: 501.7158
  fy: 500.7230
  px: 999.9791
  py: 755.6457
  k1: 0.06712904
  k2: -0.04664334
  k3: 0.02367034
  k4: -0.00555359
  p1: -0.01580726
  p2: -0.00109605
  p3: 0.00244773
  p4: 0.00231138
  s1: 0.0020
  s2: -0.0037
  s3: 0.0127
  s4: -0.0033
  tilt_x: 0.0030
  tilt_y: -0.0064
  scale: 2.9912
  rotation: -0.5865
Best score: 0.3742: : 699iter [00:20, 38.33iter/s]Best score: 0.3742: : 700iter [00:20, 38.33iter/s]Best score: 0.3742: : 701iter [00:20, 38.33iter/s]Best score: 0.3742: : 702iter [00:20, 32.62iter/s]Best score: 0.3742: : 702iter [00:20, 32.62iter/s]Best score: 0.3742: : 703iter [00:20, 32.62iter/s]Best score: 0.3742: : 704iter [00:20, 32.62iter/s]Best score: 0.3742: : 705iter [00:20, 32.62iter/s]Best score: 0.3742: : 706iter [00:20, 32.62iter/s]Best score: 0.3742: : 707iter [00:20, 35.29iter/s]Best score: 0.3742: : 707iter [00:20, 35.29iter/s]Best score: 0.3742: : 708iter [00:20, 35.29iter/s]Best score: 0.3742: : 709iter [00:20, 35.29iter/s]Best score: 0.3742: : 710iter [00:20, 35.29iter/s]Best score: 0.3742: : 711iter [00:20, 35.29iter/s]Best score: 0.3742: : 712iter [00:20, 36.97iter/s]Best score: 0.3742: : 712iter [00:20, 36.97iter/s]Best score: 0.3742: : 713iter [00:20, 36.97iter/s]Best score: 0.3742: : 714iter [00:20, 36.97iter/s]Best score: 0.3742: : 715iter [00:20, 36.97iter/s]Best score: 0.3742: : 716iter [00:20, 36.97iter/s]Best score: 0.3742: : 717iter [00:20, 38.46iter/s]Best score: 0.3742: : 717iter [00:20, 38.46iter/s]Best score: 0.3742: : 718iter [00:21, 38.46iter/s]Best score: 0.3742: : 719iter [00:21, 38.46iter/s]Best score: 0.3742: : 720iter [00:21, 38.46iter/s]Best score: 0.3742: : 721iter [00:21, 38.46iter/s]Best score: 0.3742: : 722iter [00:21, 39.22iter/s]Best score: 0.3742: : 722iter [00:21, 39.22iter/s]Best score: 0.3742: : 723iter [00:21, 39.22iter/s]Best score: 0.3742: : 724iter [00:21, 39.22iter/s]Best score: 0.3742: : 725iter [00:21, 39.22iter/s]Best score: 0.3742: : 726iter [00:21, 39.22iter/s]Best score: 0.3742: : 727iter [00:21, 40.14iter/s]Best score: 0.3742: : 727iter [00:21, 40.14iter/s]Best score: 0.3742: : 728iter [00:21, 40.14iter/s]Best score: 0.3742: : 729iter [00:21, 40.14iter/s]Best score: 0.3742: : 730iter [00:21, 40.14iter/s]Best score: 0.3742: : 731iter [00:21, 40.14iter/s]Best score: 0.3742: : 732iter [00:21, 40.47iter/s]Best score: 0.3742: : 732iter [00:21, 40.47iter/s]Best score: 0.3742: : 733iter [00:21, 40.47iter/s]Best score: 0.3742: : 734iter [00:21, 40.47iter/s]Best score: 0.3742: : 735iter [00:21, 40.47iter/s]Best score: 0.3742: : 736iter [00:21, 40.47iter/s]Best score: 0.3742: : 737iter [00:21, 41.08iter/s]Best score: 0.3742: : 737iter [00:21, 41.08iter/s]Best score: 0.3742: : 738iter [00:21, 41.08iter/s]Best score: 0.3742: : 739iter [00:21, 41.08iter/s]Best score: 0.3742: : 740iter [00:21, 41.08iter/s]Best score: 0.3742: : 741iter [00:21, 41.08iter/s]Best score: 0.3742: : 742iter [00:21, 41.14iter/s]Best score: 0.3742: : 742iter [00:21, 41.14iter/s]Best score: 0.3742: : 743iter [00:21, 41.14iter/s]Best score: 0.3742: : 744iter [00:21, 41.14iter/s]Best score: 0.3742: : 745iter [00:21, 41.14iter/s]Best score: 0.3742: : 746iter [00:21, 41.14iter/s]Best score: 0.3742: : 747iter [00:21, 41.42iter/s]Best score: 0.3742: : 747iter [00:21, 41.42iter/s]Best score: 0.3742: : 748iter [00:21, 41.42iter/s]
[ITER 750] Best: 0.3742
[PARAMS] Current best parameters:
  fx: 501.7158
  fy: 500.7230
  px: 999.9791
  py: 755.6457
  k1: 0.06712904
  k2: -0.04664334
  k3: 0.02367034
  k4: -0.00555359
  p1: -0.01580726
  p2: -0.00109605
  p3: 0.00244773
  p4: 0.00231138
  s1: 0.0020
  s2: -0.0037
  s3: 0.0127
  s4: -0.0033
  tilt_x: 0.0030
  tilt_y: -0.0064
  scale: 2.9912
  rotation: -0.5865
Best score: 0.3742: : 749iter [00:21, 41.42iter/s]Best score: 0.3742: : 750iter [00:21, 41.42iter/s]Best score: 0.3742: : 751iter [00:21, 41.42iter/s]Best score: 0.3742: : 752iter [00:21, 34.73iter/s]Best score: 0.3742: : 752iter [00:21, 34.73iter/s]Best score: 0.3742: : 753iter [00:21, 34.73iter/s]Best score: 0.3742: : 754iter [00:21, 34.73iter/s]Best score: 0.3742: : 755iter [00:21, 34.73iter/s]Best score: 0.3742: : 756iter [00:22, 34.73iter/s]Best score: 0.3742: : 757iter [00:22, 36.66iter/s]Best score: 0.3742: : 757iter [00:22, 36.66iter/s]Best score: 0.3742: : 758iter [00:22, 36.66iter/s]Best score: 0.3742: : 759iter [00:22, 36.66iter/s]Best score: 0.3742: : 760iter [00:22, 36.66iter/s]Best score: 0.3742: : 761iter [00:22, 36.66iter/s]Best score: 0.3742: : 762iter [00:22, 37.96iter/s]Best score: 0.3742: : 762iter [00:22, 37.96iter/s]Best score: 0.3742: : 763iter [00:22, 37.96iter/s]Best score: 0.3742: : 764iter [00:22, 37.96iter/s]Best score: 0.3742: : 765iter [00:22, 37.96iter/s]Best score: 0.3742: : 766iter [00:22, 37.96iter/s]Best score: 0.3742: : 767iter [00:22, 39.05iter/s]Best score: 0.3742: : 767iter [00:22, 39.05iter/s]Best score: 0.3742: : 768iter [00:22, 39.05iter/s]Best score: 0.3742: : 769iter [00:22, 39.05iter/s]Best score: 0.3742: : 770iter [00:22, 39.05iter/s]Best score: 0.3742: : 771iter [00:22, 39.05iter/s]Best score: 0.3742: : 772iter [00:22, 39.65iter/s]Best score: 0.3742: : 772iter [00:22, 39.65iter/s]Best score: 0.3742: : 773iter [00:22, 39.65iter/s]Best score: 0.3742: : 774iter [00:22, 39.65iter/s]Best score: 0.3742: : 775iter [00:22, 39.65iter/s]Best score: 0.3742: : 776iter [00:22, 39.65iter/s]Best score: 0.3742: : 777iter [00:22, 40.33iter/s]Best score: 0.3742: : 777iter [00:22, 40.33iter/s]Best score: 0.3742: : 778iter [00:22, 40.33iter/s]Best score: 0.3742: : 779iter [00:22, 40.33iter/s]Best score: 0.3742: : 780iter [00:22, 40.33iter/s]Best score: 0.3742: : 781iter [00:22, 40.33iter/s]Best score: 0.3742: : 782iter [00:22, 40.70iter/s]Best score: 0.3742: : 782iter [00:22, 40.70iter/s]Best score: 0.3742: : 783iter [00:22, 40.70iter/s]Best score: 0.3742: : 784iter [00:22, 40.70iter/s]Best score: 0.3742: : 785iter [00:22, 40.70iter/s]Best score: 0.3742: : 786iter [00:22, 40.70iter/s]Best score: 0.3742: : 787iter [00:22, 41.28iter/s]Best score: 0.3742: : 787iter [00:22, 41.28iter/s]Best score: 0.3742: : 788iter [00:22, 41.28iter/s]Best score: 0.3742: : 789iter [00:22, 41.28iter/s]Best score: 0.3742: : 790iter [00:22, 41.28iter/s]Best score: 0.3742: : 791iter [00:22, 41.28iter/s]Best score: 0.3742: : 792iter [00:22, 41.02iter/s]Best score: 0.3742: : 792iter [00:22, 41.02iter/s]Best score: 0.3742: : 793iter [00:22, 41.02iter/s]Best score: 0.3742: : 794iter [00:22, 41.02iter/s]Best score: 0.3742: : 795iter [00:22, 41.02iter/s]Best score: 0.3742: : 796iter [00:22, 41.02iter/s]Best score: 0.3742: : 797iter [00:22, 41.24iter/s]Best score: 0.3742: : 797iter [00:22, 41.24iter/s]Best score: 0.3742: : 798iter [00:23, 41.24iter/s]
[ITER 800] Best: 0.3742
[PARAMS] Current best parameters:
  fx: 501.7158
  fy: 500.7230
  px: 999.9791
  py: 755.6457
  k1: 0.06712904
  k2: -0.04664334
  k3: 0.02367034
  k4: -0.00555359
  p1: -0.01580726
  p2: -0.00109605
  p3: 0.00244773
  p4: 0.00231138
  s1: 0.0020
  s2: -0.0037
  s3: 0.0127
  s4: -0.0033
  tilt_x: 0.0030
  tilt_y: -0.0064
  scale: 2.9912
  rotation: -0.5865
Best score: 0.3742: : 799iter [00:23, 41.24iter/s]Best score: 0.3742: : 800iter [00:23, 41.24iter/s]Best score: 0.3742: : 801iter [00:23, 41.24iter/s]Best score: 0.3742: : 802iter [00:23, 34.56iter/s]Best score: 0.3742: : 802iter [00:23, 34.56iter/s]Best score: 0.3742: : 803iter [00:23, 34.56iter/s]Best score: 0.3742: : 804iter [00:23, 34.56iter/s]Best score: 0.3742: : 805iter [00:23, 34.56iter/s]Best score: 0.3742: : 806iter [00:23, 34.56iter/s]Best score: 0.3742: : 807iter [00:23, 36.58iter/s]Best score: 0.3742: : 807iter [00:23, 36.58iter/s]Best score: 0.3742: : 808iter [00:23, 36.58iter/s]Best score: 0.3742: : 809iter [00:23, 36.58iter/s]Best score: 0.3742: : 810iter [00:23, 36.58iter/s]Best score: 0.3742: : 811iter [00:23, 36.58iter/s]Best score: 0.3742: : 812iter [00:23, 37.89iter/s]Best score: 0.3742: : 812iter [00:23, 37.89iter/s]Best score: 0.3742: : 813iter [00:23, 37.89iter/s]Best score: 0.3742: : 814iter [00:23, 37.89iter/s]Best score: 0.3742: : 815iter [00:23, 37.89iter/s]Best score: 0.3742: : 816iter [00:23, 37.89iter/s]Best score: 0.3742: : 817iter [00:23, 39.07iter/s]Best score: 0.3742: : 817iter [00:23, 39.07iter/s]Best score: 0.3742: : 818iter [00:23, 39.07iter/s]Best score: 0.3718: : 819iter [00:23, 39.07iter/s]Best score: 0.3718: : 820iter [00:23, 39.07iter/s]Best score: 0.3718: : 821iter [00:23, 39.07iter/s]Best score: 0.3718: : 822iter [00:23, 39.86iter/s]Best score: 0.3718: : 822iter [00:23, 39.86iter/s]Best score: 0.3718: : 823iter [00:23, 39.86iter/s]Best score: 0.3718: : 824iter [00:23, 39.86iter/s]Best score: 0.3718: : 825iter [00:23, 39.86iter/s]Best score: 0.3718: : 826iter [00:23, 39.86iter/s]Best score: 0.3718: : 827iter [00:23, 40.57iter/s]Best score: 0.3718: : 827iter [00:23, 40.57iter/s]Best score: 0.3718: : 828iter [00:23, 40.57iter/s]Best score: 0.3683: : 829iter [00:23, 40.57iter/s]Best score: 0.3683: : 830iter [00:23, 40.57iter/s]Best score: 0.3683: : 831iter [00:23, 40.57iter/s]Best score: 0.3683: : 832iter [00:23, 40.91iter/s]Best score: 0.3683: : 832iter [00:23, 40.91iter/s]Best score: 0.3683: : 833iter [00:23, 40.91iter/s]Best score: 0.3683: : 834iter [00:23, 40.91iter/s]Best score: 0.3683: : 835iter [00:23, 40.91iter/s]Best score: 0.3683: : 836iter [00:24, 40.91iter/s]Best score: 0.3683: : 837iter [00:24, 41.38iter/s]Best score: 0.3683: : 837iter [00:24, 41.38iter/s]Best score: 0.3683: : 838iter [00:24, 41.38iter/s]Best score: 0.3489: : 839iter [00:24, 41.38iter/s]Best score: 0.3489: : 840iter [00:24, 41.38iter/s]Best score: 0.3489: : 841iter [00:24, 41.38iter/s]Best score: 0.3489: : 842iter [00:24, 41.53iter/s]Best score: 0.3489: : 842iter [00:24, 41.53iter/s]Best score: 0.3489: : 843iter [00:24, 41.53iter/s]Best score: 0.3489: : 844iter [00:24, 41.53iter/s]Best score: 0.3489: : 845iter [00:24, 41.53iter/s]Best score: 0.3489: : 846iter [00:24, 41.53iter/s]Best score: 0.3489: : 847iter [00:24, 41.82iter/s]Best score: 0.3489: : 847iter [00:24, 41.82iter/s]Best score: 0.3489: : 848iter [00:24, 41.82iter/s]
[ITER 850] Best: 0.3488
[PARAMS] Current best parameters:
  fx: 505.1279
  fy: 504.5749
  px: 997.8173
  py: 758.7566
  k1: 0.07677077
  k2: -0.05630374
  k3: 0.02293389
  k4: -0.00428120
  p1: -0.01259622
  p2: -0.00290302
  p3: 0.00484983
  p4: 0.00407635
  s1: 0.0004
  s2: -0.0056
  s3: 0.0102
  s4: -0.0052
  tilt_x: 0.0113
  tilt_y: 0.0013
  scale: 2.9698
  rotation: -0.6102
Best score: 0.3488: : 849iter [00:24, 41.82iter/s]
[Periodic outlier @ iter 750] Removing 1000 frame 2 (score=1.90, threshold=1.76)
  Remaining frames: 18
Best score: 0.3488: : 850iter [00:24, 41.82iter/s]Best score: 0.3488: : 851iter [00:24, 41.82iter/s]Best score: 0.3488: : 852iter [00:24, 32.72iter/s]Best score: 0.3488: : 852iter [00:24, 32.72iter/s]Best score: 0.3488: : 853iter [00:24, 32.72iter/s]Best score: 0.3488: : 854iter [00:24, 32.72iter/s]Best score: 0.3488: : 855iter [00:24, 32.72iter/s]Best score: 0.3488: : 856iter [00:24, 32.72iter/s]Best score: 0.3488: : 857iter [00:24, 35.33iter/s]Best score: 0.3488: : 857iter [00:24, 35.33iter/s]Best score: 0.3488: : 858iter [00:24, 35.33iter/s]Best score: 0.2625: : 859iter [00:24, 35.33iter/s]Best score: 0.2625: : 860iter [00:24, 35.33iter/s]Best score: 0.2625: : 861iter [00:24, 35.33iter/s]Best score: 0.2625: : 862iter [00:24, 37.27iter/s]Best score: 0.2625: : 862iter [00:24, 37.27iter/s]Best score: 0.2625: : 863iter [00:24, 37.27iter/s]Best score: 0.2625: : 864iter [00:24, 37.27iter/s]Best score: 0.2625: : 865iter [00:24, 37.27iter/s]Best score: 0.2625: : 866iter [00:24, 37.27iter/s]Best score: 0.2625: : 867iter [00:24, 38.87iter/s]Best score: 0.2625: : 867iter [00:24, 38.87iter/s]Best score: 0.2625: : 868iter [00:24, 38.87iter/s]Best score: 0.2625: : 869iter [00:24, 38.87iter/s]Best score: 0.2625: : 870iter [00:24, 38.87iter/s]Best score: 0.2625: : 871iter [00:24, 38.87iter/s]Best score: 0.2625: : 872iter [00:24, 39.86iter/s]Best score: 0.2625: : 872iter [00:24, 39.86iter/s]Best score: 0.2625: : 873iter [00:24, 39.86iter/s]Best score: 0.2625: : 874iter [00:25, 39.86iter/s]Best score: 0.2625: : 875iter [00:25, 39.86iter/s]Best score: 0.2625: : 876iter [00:25, 39.86iter/s]Best score: 0.2625: : 877iter [00:25, 40.90iter/s]Best score: 0.2625: : 877iter [00:25, 40.90iter/s]Best score: 0.2625: : 878iter [00:25, 40.90iter/s]Best score: 0.2625: : 879iter [00:25, 40.90iter/s]Best score: 0.2625: : 880iter [00:25, 40.90iter/s]Best score: 0.2625: : 881iter [00:25, 40.90iter/s]Best score: 0.2625: : 882iter [00:25, 41.36iter/s]Best score: 0.2625: : 882iter [00:25, 41.36iter/s]Best score: 0.2625: : 883iter [00:25, 41.36iter/s]Best score: 0.2625: : 884iter [00:25, 41.36iter/s]Best score: 0.2625: : 885iter [00:25, 41.36iter/s]Best score: 0.2625: : 886iter [00:25, 41.36iter/s]Best score: 0.2625: : 887iter [00:25, 42.10iter/s]Best score: 0.2625: : 887iter [00:25, 42.10iter/s]Best score: 0.2625: : 888iter [00:25, 42.10iter/s]Best score: 0.2625: : 889iter [00:25, 42.10iter/s]Best score: 0.2625: : 890iter [00:25, 42.10iter/s]Best score: 0.2625: : 891iter [00:25, 42.10iter/s]Best score: 0.2625: : 892iter [00:25, 42.03iter/s]Best score: 0.2625: : 892iter [00:25, 42.03iter/s]Best score: 0.2625: : 893iter [00:25, 42.03iter/s]Best score: 0.2625: : 894iter [00:25, 42.03iter/s]Best score: 0.2625: : 895iter [00:25, 42.03iter/s]Best score: 0.2625: : 896iter [00:25, 42.03iter/s]Best score: 0.2625: : 897iter [00:25, 42.41iter/s]Best score: 0.2625: : 897iter [00:25, 42.41iter/s]Best score: 0.2625: : 898iter [00:25, 42.41iter/s]
[ITER 900] Best: 0.2625
[PARAMS] Current best parameters:
  fx: 505.1279
  fy: 504.5749
  px: 997.8173
  py: 758.7566
  k1: 0.07677077
  k2: -0.05630374
  k3: 0.02293389
  k4: -0.00428120
  p1: -0.01259622
  p2: -0.00290302
  p3: 0.00484983
  p4: 0.00407635
  s1: 0.0004
  s2: -0.0056
  s3: 0.0102
  s4: -0.0052
  tilt_x: 0.0113
  tilt_y: 0.0013
  scale: 2.9698
  rotation: -0.6102
Best score: 0.2625: : 899iter [00:25, 42.41iter/s]Best score: 0.2625: : 900iter [00:25, 42.41iter/s]Best score: 0.2625: : 901iter [00:25, 42.41iter/s]Best score: 0.2625: : 902iter [00:25, 35.60iter/s]Best score: 0.2625: : 902iter [00:25, 35.60iter/s]Best score: 0.2625: : 903iter [00:25, 35.60iter/s]Best score: 0.2625: : 904iter [00:25, 35.60iter/s]Best score: 0.2625: : 905iter [00:25, 35.60iter/s]Best score: 0.2625: : 906iter [00:25, 35.60iter/s]Best score: 0.2625: : 907iter [00:25, 37.65iter/s]Best score: 0.2625: : 907iter [00:25, 37.65iter/s]Best score: 0.2625: : 908iter [00:25, 37.65iter/s]Best score: 0.2625: : 909iter [00:25, 37.65iter/s]Best score: 0.2625: : 910iter [00:25, 37.65iter/s]Best score: 0.2625: : 911iter [00:25, 37.65iter/s]Best score: 0.2625: : 912iter [00:25, 39.05iter/s]Best score: 0.2625: : 912iter [00:25, 39.05iter/s]Best score: 0.2625: : 913iter [00:25, 39.05iter/s]Best score: 0.2625: : 914iter [00:26, 39.05iter/s]Best score: 0.2625: : 915iter [00:26, 39.05iter/s]Best score: 0.2625: : 916iter [00:26, 39.05iter/s]Best score: 0.2625: : 917iter [00:26, 40.25iter/s]Best score: 0.2625: : 917iter [00:26, 40.25iter/s]Best score: 0.2625: : 918iter [00:26, 40.25iter/s]Best score: 0.2625: : 919iter [00:26, 40.25iter/s]Best score: 0.2625: : 920iter [00:26, 40.25iter/s]Best score: 0.2625: : 921iter [00:26, 40.25iter/s]Best score: 0.2625: : 922iter [00:26, 40.90iter/s]Best score: 0.2625: : 922iter [00:26, 40.90iter/s]Best score: 0.2625: : 923iter [00:26, 40.90iter/s]Best score: 0.2625: : 924iter [00:26, 40.90iter/s]Best score: 0.2625: : 925iter [00:26, 40.90iter/s]Best score: 0.2625: : 926iter [00:26, 40.90iter/s]Best score: 0.2625: : 927iter [00:26, 41.59iter/s]Best score: 0.2625: : 927iter [00:26, 41.59iter/s]Best score: 0.2625: : 928iter [00:26, 41.59iter/s]Best score: 0.2625: : 929iter [00:26, 41.59iter/s]Best score: 0.2625: : 930iter [00:26, 41.59iter/s]Best score: 0.2625: : 931iter [00:26, 41.59iter/s]Best score: 0.2625: : 932iter [00:26, 41.80iter/s]Best score: 0.2625: : 932iter [00:26, 41.80iter/s]Best score: 0.2625: : 933iter [00:26, 41.80iter/s]Best score: 0.2625: : 934iter [00:26, 41.80iter/s]Best score: 0.2625: : 935iter [00:26, 41.80iter/s]Best score: 0.2625: : 936iter [00:26, 41.80iter/s]Best score: 0.2625: : 937iter [00:26, 42.27iter/s]Best score: 0.2625: : 937iter [00:26, 42.27iter/s]Best score: 0.2625: : 938iter [00:26, 42.27iter/s]Best score: 0.2625: : 939iter [00:26, 42.27iter/s]Best score: 0.2625: : 940iter [00:26, 42.27iter/s]Best score: 0.2625: : 941iter [00:26, 42.27iter/s]Best score: 0.2625: : 942iter [00:26, 42.33iter/s]Best score: 0.2625: : 942iter [00:26, 42.33iter/s]Best score: 0.2625: : 943iter [00:26, 42.33iter/s]Best score: 0.2625: : 944iter [00:26, 42.33iter/s]Best score: 0.2625: : 945iter [00:26, 42.33iter/s]Best score: 0.2625: : 946iter [00:26, 42.33iter/s]Best score: 0.2625: : 947iter [00:26, 42.70iter/s]Best score: 0.2625: : 947iter [00:26, 42.70iter/s]Best score: 0.2625: : 948iter [00:26, 42.70iter/s]
[ITER 950] Best: 0.2625
[PARAMS] Current best parameters:
  fx: 505.1279
  fy: 504.5749
  px: 997.8173
  py: 758.7566
  k1: 0.07677077
  k2: -0.05630374
  k3: 0.02293389
  k4: -0.00428120
  p1: -0.01259622
  p2: -0.00290302
  p3: 0.00484983
  p4: 0.00407635
  s1: 0.0004
  s2: -0.0056
  s3: 0.0102
  s4: -0.0052
  tilt_x: 0.0113
  tilt_y: 0.0013
  scale: 2.9698
  rotation: -0.6102
Best score: 0.2625: : 949iter [00:26, 42.70iter/s]Best score: 0.2625: : 950iter [00:26, 42.70iter/s]Best score: 0.2625: : 951iter [00:26, 42.70iter/s]Best score: 0.2625: : 952iter [00:26, 35.95iter/s]Best score: 0.2625: : 952iter [00:26, 35.95iter/s]Best score: 0.2625: : 953iter [00:26, 35.95iter/s]Best score: 0.2625: : 954iter [00:27, 35.95iter/s]Best score: 0.2625: : 955iter [00:27, 35.95iter/s]Best score: 0.2625: : 956iter [00:27, 35.95iter/s]Best score: 0.2625: : 957iter [00:27, 37.99iter/s]Best score: 0.2625: : 957iter [00:27, 37.99iter/s]Best score: 0.2625: : 958iter [00:27, 37.99iter/s]Best score: 0.2625: : 959iter [00:27, 37.99iter/s]Best score: 0.2625: : 960iter [00:27, 37.99iter/s]Best score: 0.2625: : 961iter [00:27, 37.99iter/s]Best score: 0.2625: : 962iter [00:27, 39.41iter/s]Best score: 0.2625: : 962iter [00:27, 39.41iter/s]Best score: 0.2625: : 963iter [00:27, 39.41iter/s]Best score: 0.2625: : 964iter [00:27, 39.41iter/s]Best score: 0.2625: : 965iter [00:27, 39.41iter/s]Best score: 0.2625: : 966iter [00:27, 39.41iter/s]Best score: 0.2625: : 967iter [00:27, 40.68iter/s]Best score: 0.2625: : 967iter [00:27, 40.68iter/s]Best score: 0.2625: : 968iter [00:27, 40.68iter/s]Best score: 0.2625: : 969iter [00:27, 40.68iter/s]Best score: 0.2625: : 970iter [00:27, 40.68iter/s]Best score: 0.2625: : 971iter [00:27, 40.68iter/s]Best score: 0.2625: : 972iter [00:27, 41.23iter/s]Best score: 0.2625: : 972iter [00:27, 41.23iter/s]Best score: 0.2625: : 973iter [00:27, 41.23iter/s]Best score: 0.2625: : 974iter [00:27, 41.23iter/s]Best score: 0.2625: : 975iter [00:27, 41.23iter/s]Best score: 0.2625: : 976iter [00:27, 41.23iter/s]Best score: 0.2625: : 977iter [00:27, 41.99iter/s]Best score: 0.2625: : 977iter [00:27, 41.99iter/s]Best score: 0.2625: : 978iter [00:27, 41.99iter/s]Best score: 0.2625: : 979iter [00:27, 41.99iter/s]Best score: 0.2625: : 980iter [00:27, 41.99iter/s]Best score: 0.2625: : 981iter [00:27, 41.99iter/s]Best score: 0.2625: : 982iter [00:27, 42.42iter/s]Best score: 0.2625: : 982iter [00:27, 42.42iter/s]Best score: 0.2625: : 983iter [00:27, 42.42iter/s]Best score: 0.2625: : 984iter [00:27, 42.42iter/s]Best score: 0.2625: : 985iter [00:27, 42.42iter/s]Best score: 0.2625: : 986iter [00:27, 42.42iter/s]Best score: 0.2625: : 987iter [00:27, 42.87iter/s]Best score: 0.2625: : 987iter [00:27, 42.87iter/s]Best score: 0.2625: : 988iter [00:27, 42.87iter/s]Best score: 0.2625: : 989iter [00:27, 42.87iter/s]Best score: 0.2625: : 990iter [00:27, 42.87iter/s]Best score: 0.2625: : 991iter [00:27, 42.87iter/s]Best score: 0.2625: : 992iter [00:27, 42.69iter/s]Best score: 0.2625: : 992iter [00:27, 42.69iter/s]Best score: 0.2625: : 993iter [00:27, 42.69iter/s]Best score: 0.2625: : 994iter [00:27, 42.69iter/s]Best score: 0.2625: : 995iter [00:27, 42.69iter/s]Best score: 0.2625: : 996iter [00:27, 42.69iter/s]Best score: 0.2625: : 997iter [00:27, 42.97iter/s]Best score: 0.2625: : 997iter [00:28, 42.97iter/s]Best score: 0.2625: : 998iter [00:28, 42.97iter/s]
[ITER 1000] Best: 0.2625
[PARAMS] Current best parameters:
  fx: 505.1279
  fy: 504.5749
  px: 997.8173
  py: 758.7566
  k1: 0.07677077
  k2: -0.05630374
  k3: 0.02293389
  k4: -0.00428120
  p1: -0.01259622
  p2: -0.00290302
  p3: 0.00484983
  p4: 0.00407635
  s1: 0.0004
  s2: -0.0056
  s3: 0.0102
  s4: -0.0052
  tilt_x: 0.0113
  tilt_y: 0.0013
  scale: 2.9698
  rotation: -0.6102
Best score: 0.2625: : 999iter [00:28, 42.97iter/s]Best score: 0.2625: : 1000iter [00:28, 42.97iter/s]Best score: 0.2625: : 1001iter [00:28, 42.97iter/s]Best score: 0.2625: : 1002iter [00:28, 36.01iter/s]Best score: 0.2625: : 1002iter [00:28, 36.01iter/s]Best score: 0.2625: : 1003iter [00:28, 36.01iter/s]Best score: 0.2625: : 1004iter [00:28, 36.01iter/s]Best score: 0.2625: : 1005iter [00:28, 36.01iter/s]Best score: 0.2625: : 1006iter [00:28, 30.40iter/s]Best score: 0.2625: : 1006iter [00:28, 30.40iter/s]Best score: 0.2625: : 1007iter [00:28, 30.40iter/s]Best score: 0.2625: : 1008iter [00:28, 30.40iter/s]Best score: 0.2625: : 1009iter [00:28, 30.40iter/s]Best score: 0.2625: : 1010iter [00:28, 30.40iter/s]Best score: 0.2625: : 1011iter [00:28, 33.47iter/s]Best score: 0.2625: : 1011iter [00:28, 33.47iter/s]Best score: 0.2625: : 1012iter [00:28, 33.47iter/s]Best score: 0.2625: : 1013iter [00:28, 33.47iter/s]Best score: 0.2625: : 1014iter [00:28, 33.47iter/s]Best score: 0.2625: : 1015iter [00:28, 33.47iter/s]Best score: 0.2625: : 1016iter [00:28, 36.20iter/s]Best score: 0.2625: : 1016iter [00:28, 36.20iter/s]Best score: 0.2625: : 1017iter [00:28, 36.20iter/s]Best score: 0.2625: : 1018iter [00:28, 36.20iter/s]Best score: 0.2625: : 1019iter [00:28, 36.20iter/s]Best score: 0.2625: : 1020iter [00:28, 36.20iter/s]Best score: 0.2625: : 1021iter [00:28, 38.02iter/s]Best score: 0.2625: : 1021iter [00:28, 38.02iter/s]Best score: 0.2625: : 1022iter [00:28, 38.02iter/s]Best score: 0.2625: : 1023iter [00:28, 38.02iter/s]Best score: 0.2625: : 1024iter [00:28, 38.02iter/s]Best score: 0.2625: : 1025iter [00:28, 38.02iter/s]Best score: 0.2625: : 1026iter [00:28, 39.77iter/s]Best score: 0.2625: : 1026iter [00:28, 39.77iter/s]Best score: 0.2625: : 1027iter [00:28, 39.77iter/s]Best score: 0.2625: : 1028iter [00:28, 39.77iter/s]Best score: 0.2625: : 1029iter [00:28, 39.77iter/s]Best score: 0.2625: : 1030iter [00:28, 39.77iter/s]Best score: 0.2625: : 1031iter [00:28, 40.86iter/s]Best score: 0.2625: : 1031iter [00:28, 40.86iter/s]Best score: 0.2625: : 1032iter [00:28, 40.86iter/s]Best score: 0.2625: : 1033iter [00:29, 40.86iter/s]Best score: 0.2625: : 1034iter [00:29, 40.86iter/s]Best score: 0.2625: : 1035iter [00:29, 40.86iter/s]Best score: 0.2625: : 1036iter [00:29, 41.95iter/s]Best score: 0.2625: : 1036iter [00:29, 41.95iter/s]Best score: 0.2625: : 1037iter [00:29, 41.95iter/s]Best score: 0.2625: : 1038iter [00:29, 41.95iter/s]Best score: 0.2625: : 1039iter [00:29, 41.95iter/s]Best score: 0.2625: : 1040iter [00:29, 41.95iter/s]Best score: 0.2625: : 1041iter [00:29, 42.58iter/s]Best score: 0.2625: : 1041iter [00:29, 42.58iter/s]Best score: 0.2625: : 1042iter [00:29, 42.58iter/s]Best score: 0.2625: : 1043iter [00:29, 42.58iter/s]Best score: 0.2625: : 1044iter [00:29, 42.58iter/s]Best score: 0.2625: : 1045iter [00:29, 42.58iter/s]Best score: 0.2625: : 1046iter [00:29, 43.20iter/s]Best score: 0.2625: : 1046iter [00:29, 43.20iter/s]Best score: 0.2625: : 1047iter [00:29, 43.20iter/s]Best score: 0.2625: : 1048iter [00:29, 43.20iter/s]
[ITER 1050] Best: 0.2625
[PARAMS] Current best parameters:
  fx: 505.1279
  fy: 504.5749
  px: 997.8173
  py: 758.7566
  k1: 0.07677077
  k2: -0.05630374
  k3: 0.02293389
  k4: -0.00428120
  p1: -0.01259622
  p2: -0.00290302
  p3: 0.00484983
  p4: 0.00407635
  s1: 0.0004
  s2: -0.0056
  s3: 0.0102
  s4: -0.0052
  tilt_x: 0.0113
  tilt_y: 0.0013
  scale: 2.9698
  rotation: -0.6102
Best score: 0.2625: : 1049iter [00:29, 43.20iter/s]Best score: 0.2625: : 1050iter [00:29, 43.20iter/s]Best score: 0.2625: : 1051iter [00:29, 36.24iter/s]Best score: 0.2625: : 1051iter [00:29, 36.24iter/s]Best score: 0.2625: : 1052iter [00:29, 36.24iter/s]Best score: 0.2625: : 1053iter [00:29, 36.24iter/s]Best score: 0.2625: : 1054iter [00:29, 36.24iter/s]Best score: 0.2625: : 1055iter [00:29, 36.24iter/s]Best score: 0.2625: : 1056iter [00:29, 38.31iter/s]Best score: 0.2625: : 1056iter [00:29, 38.31iter/s]Best score: 0.2625: : 1057iter [00:29, 38.31iter/s]Best score: 0.2625: : 1058iter [00:29, 38.31iter/s]Best score: 0.2625: : 1059iter [00:29, 38.31iter/s]Best score: 0.2625: : 1060iter [00:29, 38.31iter/s]Best score: 0.2625: : 1061iter [00:29, 39.72iter/s]Best score: 0.2625: : 1061iter [00:29, 39.72iter/s]Best score: 0.2625: : 1062iter [00:29, 39.72iter/s]Best score: 0.2625: : 1063iter [00:29, 39.72iter/s]Best score: 0.2625: : 1064iter [00:29, 39.72iter/s]Best score: 0.2625: : 1065iter [00:29, 39.72iter/s]Best score: 0.2625: : 1066iter [00:29, 40.81iter/s]Best score: 0.2625: : 1066iter [00:29, 40.81iter/s]Best score: 0.2625: : 1067iter [00:29, 40.81iter/s]Best score: 0.2625: : 1068iter [00:29, 40.81iter/s]Best score: 0.2625: : 1069iter [00:29, 40.81iter/s]Best score: 0.2625: : 1070iter [00:29, 40.81iter/s]Best score: 0.2625: : 1071iter [00:29, 41.52iter/s]Best score: 0.2625: : 1071iter [00:29, 41.52iter/s]Best score: 0.2625: : 1072iter [00:29, 41.52iter/s]Best score: 0.2625: : 1073iter [00:29, 41.52iter/s]Best score: 0.2625: : 1074iter [00:30, 41.52iter/s]Best score: 0.2625: : 1075iter [00:30, 41.52iter/s]Best score: 0.2625: : 1076iter [00:30, 42.26iter/s]Best score: 0.2625: : 1076iter [00:30, 42.26iter/s]Best score: 0.2625: : 1077iter [00:30, 42.26iter/s]Best score: 0.2625: : 1078iter [00:30, 42.26iter/s]Best score: 0.2625: : 1079iter [00:30, 42.26iter/s]Best score: 0.2625: : 1080iter [00:30, 42.26iter/s]Best score: 0.2625: : 1081iter [00:30, 42.57iter/s]Best score: 0.2625: : 1081iter [00:30, 42.57iter/s]Best score: 0.2625: : 1082iter [00:30, 42.57iter/s]Best score: 0.2625: : 1083iter [00:30, 42.57iter/s]Best score: 0.2625: : 1084iter [00:30, 42.57iter/s]Best score: 0.2625: : 1085iter [00:30, 42.57iter/s]Best score: 0.2625: : 1086iter [00:30, 43.02iter/s]Best score: 0.2625: : 1086iter [00:30, 43.02iter/s]Best score: 0.2625: : 1087iter [00:30, 43.02iter/s]Best score: 0.2625: : 1088iter [00:30, 43.02iter/s]Best score: 0.2625: : 1089iter [00:30, 43.02iter/s]Best score: 0.2625: : 1090iter [00:30, 43.02iter/s]Best score: 0.2625: : 1091iter [00:30, 43.17iter/s]Best score: 0.2625: : 1091iter [00:30, 43.17iter/s]Best score: 0.2625: : 1092iter [00:30, 43.17iter/s]Best score: 0.2625: : 1093iter [00:30, 43.17iter/s]Best score: 0.2625: : 1094iter [00:30, 43.17iter/s]Best score: 0.2625: : 1095iter [00:30, 43.17iter/s]Best score: 0.2625: : 1096iter [00:30, 43.41iter/s]Best score: 0.2625: : 1096iter [00:30, 43.41iter/s]Best score: 0.2625: : 1097iter [00:30, 43.41iter/s]Best score: 0.2625: : 1098iter [00:30, 43.41iter/s]
[ITER 1100] Best: 0.2625
[PARAMS] Current best parameters:
  fx: 505.1279
  fy: 504.5749
  px: 997.8173
  py: 758.7566
  k1: 0.07677077
  k2: -0.05630374
  k3: 0.02293389
  k4: -0.00428120
  p1: -0.01259622
  p2: -0.00290302
  p3: 0.00484983
  p4: 0.00407635
  s1: 0.0004
  s2: -0.0056
  s3: 0.0102
  s4: -0.0052
  tilt_x: 0.0113
  tilt_y: 0.0013
  scale: 2.9698
  rotation: -0.6102
Best score: 0.2625: : 1099iter [00:30, 43.41iter/s]
[📈] Running L-BFGS-B polish after 1100 DE iterations...
Best score: 0.2625: : 1100iter [00:30, 35.87iter/s]
  Polish improved score: 0.262513 -> 0.240533

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 23,330 → 23,330 within 3500mm ring
  Ring polish improved score: 0.240533 -> 0.234960
  Success: True
  Tangential distortion: p1=-0.012061, p2=-0.002980, p3=0.004277, p4=0.004814
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.2350
[✅] Parameters copied to: /working/MDC026_W024_2026-08-25/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 505.1282465098659
    fy: 504.57428202279675
    px: 997.8172424839405
    py: 758.7566116579628
    k1: 0.07657535795398832
    k2: -0.056104931235032594
    k3: 0.023156366132047405
    k4: -0.004417861458196764
    p1: -0.012060837891861548
    p2: -0.0029798288731394773
    p3: 0.004277066528180165
    p4: 0.00481353859911092
    scale: 2.9674646296573264
    rotation: -0.6102483513607061
    mmpp: 1.2865837404917249

[🔄] Converting 1280 frames to PTD, creating debug images for 200 calibration frames...
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   🔄 500: 100%|█████████▉| 607/609 [00:03<00:00, 176.57frame/s][A
                                                                [A📁 Rigs: 100%|██████████| 2/2 [00:12<00:00,  6.39s/rig]📁 Rigs: 100%|██████████| 2/2 [00:12<00:00,  6.48s/rig]
[✅] Saved PTDs: /working/MDC026_W024_2026-08-25/calibration/debug/4_undistorted/output/ptd
📁 Rigs:   0%|          | 0/2 [00:00<?, ?rig/s]
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   🔄 1000:  90%|█████████ | 90/100 [00:00<00:00, 175.98frame/s][A
                                                                [A📁 Rigs:  50%|█████     | 1/2 [00:01<00:01,  1.04s/rig]
   🔄 500:   0%|          | 0/100 [00:00<?, ?frame/s][A
   🔄 500:  18%|█▊        | 18/100 [00:00<00:00, 175.58frame/s][A
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   🔄 500:  72%|███████▏  | 72/100 [00:00<00:00, 175.41frame/s][A
   🔄 500:  90%|█████████ | 90/100 [00:00<00:00, 175.85frame/s][A
                                                               [A📁 Rigs: 100%|██████████| 2/2 [00:02<00:00,  1.05s/rig]📁 Rigs: 100%|██████████| 2/2 [00:02<00:00,  1.04s/rig]
[✅] Saved PTDs: /working/MDC026_W024_2026-08-25/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%|▎         | 78645/3080448 [00:00<00:03, 786447.00px/s]📤 Writing LUT:   5%|▌         | 164010/3080448 [00:00<00:03, 825972.79px/s]📤 Writing LUT:   8%|▊         | 249768/3080448 [00:00<00:03, 840403.78px/s]📤 Writing LUT:  11%|█         | 335220/3080448 [00:00<00:03, 845976.21px/s]📤 Writing LUT:  14%|█▍        | 427417/3080448 [00:00<00:03, 873377.34px/s]📤 Writing LUT:  17%|█▋        | 515796/3080448 [00:00<00:02, 876915.08px/s]📤 Writing LUT:  20%|█▉        | 606181/3080448 [00:00<00:02, 885719.60px/s]📤 Writing LUT:  23%|██▎       | 695802/3080448 [00:00<00:02, 889057.47px/s]📤 Writing LUT:  25%|██▌       | 784708/3080448 [00:00<00:02, 887038.10px/s]📤 Writing LUT:  28%|██▊       | 873413/3080448 [00:01<00:02, 883093.01px/s]📤 Writing LUT:  31%|███       | 962008/3080448 [00:01<00:02, 883960.79px/s]📤 Writing LUT:  34%|███▍      | 1050408/3080448 [00:01<00:02, 882946.82px/s]📤 Writing LUT:  37%|███▋      | 1140004/3080448 [00:01<00:02, 886877.38px/s]📤 Writing LUT:  40%|███▉      | 1228712/3080448 [00:01<00:02, 886938.07px/s]📤 Writing LUT:  43%|████▎     | 1320339/3080448 [00:01<00:01, 895766.32px/s]📤 Writing LUT:  46%|████▌     | 1410971/3080448 [00:01<00:01, 898937.57px/s]📤 Writing LUT:  49%|████▉     | 1503311/3080448 [00:01<00:01, 906285.41px/s]📤 Writing LUT:  52%|█████▏    | 1593942/3080448 [00:01<00:01, 903711.66px/s]📤 Writing LUT:  55%|█████▍    | 1684317/3080448 [00:01<00:01, 901655.69px/s]📤 Writing LUT:  58%|█████▊    | 1774486/3080448 [00:02<00:01, 901282.94px/s]📤 Writing LUT:  61%|██████    | 1864617/3080448 [00:02<00:01, 895929.44px/s]📤 Writing LUT:  63%|██████▎   | 1954218/3080448 [00:02<00:01, 891149.79px/s]📤 Writing LUT:  66%|██████▋   | 2043342/3080448 [00:02<00:01, 891071.91px/s]📤 Writing LUT:  69%|██████▉   | 2132455/3080448 [00:02<00:01, 888833.53px/s]📤 Writing LUT:  72%|███████▏  | 2223532/3080448 [00:02<00:00, 895376.01px/s]📤 Writing LUT:  75%|███████▌  | 2313077/3080448 [00:02<00:00, 894499.16px/s]📤 Writing LUT:  78%|███████▊  | 2402532/3080448 [00:02<00:00, 892872.63px/s]📤 Writing LUT:  81%|████████  | 2491823/3080448 [00:02<00:00, 891031.89px/s]📤 Writing LUT:  84%|████████▍ | 2580929/3080448 [00:02<00:00, 889502.68px/s]📤 Writing LUT:  87%|████████▋ | 2670512/3080448 [00:03<00:00, 891392.82px/s]📤 Writing LUT:  90%|████████▉ | 2764004/3080448 [00:03<00:00, 904411.02px/s]📤 Writing LUT:  93%|█████████▎| 2856258/3080448 [00:03<00:00, 909838.51px/s]📤 Writing LUT:  96%|█████████▌| 2947526/3080448 [00:03<00:00, 910688.73px/s]📤 Writing LUT:  99%|█████████▊| 3040584/3080448 [00:03<00:00, 916647.93px/s]📤 Writing LUT: 100%|██████████| 3080448/3080448 [00:03<00:00, 891793.31px/s]
[✅] LUT written to: /working/MDC026_W024_2026-08-25/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'MDC026_W024_2026-08-25' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDC026_W024_2026-08-25/calibration/MDC026_W024_2026-08-25_unknown.lut

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

[ℹ️] Detected device type: MD (rigs: [500, 1000]mm)
📁 Rigs (heatmap):   0%|          | 0/2 [00:00<?, ?rig/s]
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                                                                [A[✅] 1000: /working/MDC026_W024_2026-08-25/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDC026_W024_2026-08-25/calibration/debug/5_heatmap/1000_heatmap_fitted.png
📁 Rigs (heatmap):  50%|█████     | 1/2 [00:10<00:10, 10.88s/rig]
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                                                               [A[✅] 500: /working/MDC026_W024_2026-08-25/calibration/debug/5_heatmap/500_heatmap.png
[✅] 500 (fitted): /working/MDC026_W024_2026-08-25/calibration/debug/5_heatmap/500_heatmap_fitted.png
📁 Rigs (heatmap): 100%|██████████| 2/2 [00:19<00:00,  9.69s/rig]📁 Rigs (heatmap): 100%|██████████| 2/2 [00:19<00:00,  9.87s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MDC026_W024_2026-08-25/calibration/debug/5_heatmap
[🏁] Finished processing MDC026_W024_2026-08-25


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