Add Bedroom1/Slam3r1_ScanVideo1 (SLAM3R offline pipeline)

.gitattributes

@@ -1589,3 +1589,4 @@ P64/Solv3r2_ScanVideo1/solve.html filter=lfs diff=lfs merge=lfs -text
 P64/Solv3r2_ScanVideo1/solve.ply filter=lfs diff=lfs merge=lfs -text
 I87X/Solv3r2_ScanVideo1/solve.html filter=lfs diff=lfs merge=lfs -text
 I87X/Solv3r2_ScanVideo1/solve.ply filter=lfs diff=lfs merge=lfs -text
+Bedroom1/Slam3r1_ScanVideo1/scan.ply filter=lfs diff=lfs merge=lfs -text

Bedroom1/Slam3r1_ScanVideo1/config.txt

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+SLAM3R commit f531d84; recon.py with scripts/demo_wild.sh defaults (keyframe_stride 3, offline pipeline, 1M points saved); input = frames extracted from ScanVideos/Video1 at 960 px wide; per-frame preds not uploaded. monitor.log RAM/GPU are device-wide (shared machine), columns: unix_time ram_used_MB gpu_mem_used_MB,gpu_util_%

Bedroom1/Slam3r1_ScanVideo1/monitor.log

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Bedroom1/Slam3r1_ScanVideo1/run.log

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+No totally free GPU found! Choose the most free one.
+using gpu:  0
+Loading dataset:  /home/lehoangan/LHAN/solv3r_test/runs/bedroom1_slam3r/frames
+>> Loading images from /home/lehoangan/LHAN/solv3r_test/runs/bedroom1_slam3r/frames
+
+ (742 images loaded)
+
+finish pre-extracting img tokens
+initialize scene with 5 views, with a mean confidence of 8.59
+
+finish recovering pcds of 742 frames in their local coordinates, with a mean confidence of 8.58
+
+finish aligning 12 head frames, with a max mean confidence of 22.01
+
+mean confidence for whole scene reconstruction: 13.90
+395 views with low confidence:  {4: 1.13, 5: 7.9, 7: 3.2, 13: 4.52, 15: 5.83, 24: 7.02, 28: 5.75, 29: 5.2, 30: 5.37, 119: 8.18, 120: 7.18, 121: 6.51, 122: 5.9, 123: 5.19, 124: 9.87, 125: 9.64, 126: 8.69, 170: 5.45, 171: 6.83, 172: 7.94, 173: 5.14, 174: 3.71, 175: 1.76, 176: 4.7, 177: 5.4, 178: 4.92, 180: 6.65, 181: 8.92, 183: 9.55, 184: 7.66, 185: 6.33, 186: 4.24, 188: 2.49, 189: 1.06, 190: 5.79, 191: 1.17, 192: 1.02, 193: 5.83, 194: 1.39, 195: 3.89, 197: 2.76, 198: 3.15, 200: 3.07, 201: 3.31, 202: 6.86, 203: 2.28, 204: 1.06, 205: 4.88, 206: 4.75, 207: 3.38, 210: 8.91, 211: 8.79, 212: 5.96, 213: 1.11, 214: 1.03, 215: 1.65, 216: 3.12, 217: 4.84, 218: 8.0, 220: 7.03, 226: 6.99, 227: 6.96, 228: 2.31, 229: 2.42, 230: 1.9, 231: 6.15, 232: 9.81, 233: 5.69, 234: 4.01, 235: 7.37, 236: 3.64, 237: 2.25, 238: 2.96, 239: 2.56, 240: 2.44, 241: 2.67, 242: 1.96, 243: 3.03, 248: 7.53, 277: 4.63, 278: 6.6, 279: 1.9, 280: 1.31, 285: 1.02, 286: 1.03, 287: 1.37, 290: 4.52, 296: 9.5, 297: 1.0, 298: 2.89, 300: 1.0, 318: 8.99, 331: 9.48, 335: 7.32, 337: 6.47, 338: 6.59, 340: 3.44, 341: 3.91, 342: 6.35, 343: 4.39, 344: 3.24, 345: 2.19, 346: 1.66, 347: 1.37, 348: 1.48, 349: 3.75, 350: 1.19, 351: 1.58, 352: 1.28, 353: 1.05, 354: 1.31, 355: 1.01, 356: 1.81, 357: 2.67, 358: 4.32, 359: 4.68, 360: 4.26, 361: 4.22, 362: 4.37, 363: 3.49, 364: 2.58, 365: 3.47, 366: 3.31, 367: 2.6, 368: 2.63, 369: 3.11, 370: 3.97, 371: 3.73, 372: 3.31, 373: 3.37, 374: 3.88, 375: 3.48, 376: 3.8, 377: 2.93, 378: 2.52, 379: 3.12, 380: 3.13, 381: 2.61, 382: 2.97, 383: 2.9, 384: 2.72, 385: 2.66, 386: 2.52, 387: 2.7, 388: 2.84, 389: 3.0, 390: 2.43, 391: 5.57, 392: 5.8, 393: 5.95, 394: 7.03, 395: 3.62, 396: 1.8, 397: 1.03, 398: 3.54, 399: 2.76, 400: 2.69, 401: 1.29, 402: 2.43, 403: 2.53, 404: 2.24, 405: 1.0, 449: 9.48, 450: 9.33, 454: 8.69, 455: 7.16, 456: 6.14, 457: 5.26, 458: 4.46, 459: 3.05, 460: 4.78, 461: 3.76, 462: 2.81, 463: 2.95, 464: 2.41, 465: 1.99, 466: 1.96, 467: 1.19, 468: 1.28, 469: 1.03, 470: 1.02, 471: 1.0, 472: 2.7, 473: 2.71, 474: 2.61, 475: 1.73, 476: 1.45, 477: 1.27, 478: 1.27, 479: 2.45, 480: 2.28, 481: 2.08, 482: 1.93, 483: 2.66, 484: 2.17, 485: 2.04, 486: 2.72, 487: 1.67, 488: 1.55, 489: 1.54, 490: 1.79, 491: 1.28, 492: 1.39, 493: 1.23, 494: 1.26, 495: 1.12, 496: 1.02, 497: 1.01, 498: 1.01, 499: 1.02, 500: 1.0, 501: 1.0, 502: 1.0, 503: 1.0, 504: 1.0, 505: 1.0, 506: 1.0, 507: 1.0, 508: 1.0, 509: 1.0, 510: 1.0, 511: 1.0, 512: 1.0, 513: 1.0, 514: 1.0, 515: 1.0, 516: 1.0, 517: 1.0, 518: 1.0, 519: 1.0, 520: 1.0, 521: 1.0, 522: 1.0, 523: 1.0, 524: 1.0, 525: 1.0, 526: 1.0, 527: 1.0, 528: 1.0, 529: 1.0, 530: 1.0, 531: 1.0, 532: 1.16, 533: 1.26, 534: 1.0, 535: 1.49, 536: 1.23, 537: 1.33, 538: 2.39, 539: 1.5, 540: 1.03, 541: 5.07, 542: 5.06, 543: 4.74, 544: 7.26, 545: 7.57, 546: 8.21, 556: 9.84, 559: 8.17, 560: 7.47, 561: 8.1, 562: 6.57, 563: 5.74, 564: 8.08, 565: 6.38, 566: 4.5, 567: 5.58, 568: 5.35, 569: 4.9, 570: 5.37, 571: 5.16, 572: 4.73, 573: 6.63, 574: 6.95, 575: 6.06, 576: 5.72, 577: 3.73, 578: 3.17, 579: 3.33, 580: 4.01, 581: 4.13, 582: 4.15, 583: 4.35, 584: 4.8, 585: 4.87, 586: 8.01, 587: 8.25, 588: 8.25, 589: 8.19, 590: 8.96, 591: 4.83, 592: 4.69, 593: 5.48, 594: 8.36, 595: 9.63, 596: 8.89, 597: 7.2, 598: 7.85, 599: 7.75, 600: 5.43, 601: 8.13, 602: 6.32, 603: 6.64, 604: 7.11, 605: 5.27, 606: 4.59, 607: 7.46, 608: 7.51, 609: 4.9, 610: 4.11, 611: 4.71, 612: 2.81, 613: 5.27, 614: 5.67, 615: 4.89, 616: 7.55, 617: 4.03, 618: 5.03, 632: 9.5, 633: 8.82, 639: 8.75, 642: 8.96, 643: 8.11, 644: 4.23, 645: 2.82, 646: 6.38, 647: 2.41, 648: 1.94, 649: 1.39, 650: 1.0, 651: 1.0, 652: 1.08, 653: 1.2, 657: 2.86, 672: 8.63, 673: 2.92, 674: 3.34, 675: 3.95, 676: 1.0, 677: 3.25, 678: 1.03, 679: 5.79, 680: 3.68, 681: 1.0, 682: 2.0, 683: 1.0, 684: 1.0, 685: 1.0, 686: 1.0, 687: 1.0, 688: 1.0, 689: 1.0, 690: 1.0, 691: 1.0, 692: 1.03, 693: 1.0, 694: 1.0, 695: 1.04, 696: 1.36, 697: 1.0, 698: 1.0, 699: 1.03, 700: 1.0, 701: 1.0, 702: 1.0, 703: 1.01, 704: 1.0, 705: 1.0, 706: 1.0, 707: 1.0, 708: 1.0, 709: 1.0, 710: 1.0, 711: 1.0, 712: 1.0, 713: 1.0, 714: 1.0, 715: 1.93, 716: 3.14, 717: 4.91, 718: 1.89, 719: 4.0, 720: 2.96, 721: 7.57, 722: 7.61, 723: 7.4, 724: 7.47, 725: 5.39, 726: 7.01, 727: 6.11, 729: 5.98, 730: 4.97, 731: 7.58, 732: 2.6, 738: 7.04}
+ratio of points filered out: 58.89%
+resampling 1000000 points from 15304551 points
+>> save_to /home/lehoangan/LHAN/solv3r_test/runs/bedroom1_slam3r/out/bedroom1_slam3r/bedroom1_slam3r_frames_recon.ply
+>> saving per-frame predictions to /home/lehoangan/LHAN/solv3r_test/runs/bedroom1_slam3r/out/bedroom1_slam3r/preds
+wall_seconds=61
+done

Bedroom1/Slam3r1_ScanVideo1/scan.ply

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