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[HAMI-core Msg(119598:140316509199232:libvgpu.c:837)]: Initializing.....
2026-05-08 11:04:23,210 [unified] INFO: [init] Using ultralytics built-in dataset: VisDrone.yaml
2026-05-08 11:04:23,210 [unified] INFO: [init] Val images: /home/jovyan/work/jupyter/content/SemanticSlicer/datasets/VisDrone/images/val
2026-05-08 11:04:23,210 [unified] INFO: [init] Val labels: /home/jovyan/work/jupyter/content/SemanticSlicer/datasets/VisDrone/labels/val
2026-05-08 11:04:23,210 [unified] INFO: [init] Train images: content/SemanticSlicer/datasets/VisDrone/images/train
2026-05-08 11:04:23,210 [unified] INFO: [init] Train labels: content/SemanticSlicer/datasets/VisDrone/labels/train
2026-05-08 11:04:23,211 [unified] INFO: Skipping YOLO training, using weights: /home/jovyan/work/jupyter/content/results/yolov8l-p2-visdrone-v10/weights/best.pt
2026-05-08 11:04:23,213 [unified] INFO: Using existing ObjSeeker weights: /home/jovyan/work/jupyter/content/results/yolov8l-p2-visdrone-objseeker/objseeker/objseeker_best.pth
2026-05-08 11:04:29,021 [unified] INFO: ======================================================================
2026-05-08 11:04:29,021 [unified] INFO: Phase 2: Standard mAP Evaluation (Multi-Scale)
2026-05-08 11:04:29,021 [unified] INFO: ======================================================================
[HAMI-core Msg(119598:140316509199232:libvgpu.c:856)]: Initialized
Ultralytics 8.4.41 πŸš€ Python-3.12.13 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24564MiB)
YOLOv8l-p2 summary (fused): 139 layers, 42,827,064 parameters, 0 gradients, 204.8 GFLOPs
val: Fast image access βœ… (ping: 0.4Β±0.2 ms, read: 208.4Β±100.5 MB/s, size: 188.4 KB)
val: Scanning /home/jovyan/work/jupyter/content/SemanticSlicer/datasets/VisDrone/labels/val.cache... 548 images, 0 backgrounds, 0 corrupt: 100% ━━━━━━━━━━━━ 548/548 46.9Mit/s 0.0s
Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 35/35 2.2it/s 15.9s0.2s
all 548 38759 0.653 0.564 0.581 0.358
pedestrian 520 8844 0.743 0.641 0.696 0.351
people 482 5125 0.704 0.532 0.565 0.252
bicycle 364 1287 0.477 0.417 0.402 0.205
car 515 14064 0.84 0.873 0.898 0.649
van 421 1975 0.653 0.577 0.599 0.432
truck 266 750 0.638 0.527 0.55 0.376
tricycle 337 1045 0.584 0.473 0.474 0.281
awning-tricycle 220 532 0.41 0.278 0.25 0.159
bus 131 251 0.776 0.665 0.699 0.529
motor 485 4886 0.701 0.653 0.677 0.342
Speed: 1.2ms preprocess, 9.7ms inference, 0.0ms loss, 12.4ms postprocess per image
Results saved to /home/jovyan/work/jupyter/runs/detect/val-53
2026-05-08 11:04:57,937 [unified] INFO: Standard@1024: mAP50=0.5810 P=0.6527 R=0.5637
Ultralytics 8.4.41 πŸš€ Python-3.12.13 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24564MiB)
YOLOv8l-p2 summary (fused): 139 layers, 42,827,064 parameters, 0 gradients, 204.8 GFLOPs
val: Fast image access βœ… (ping: 0.0Β±0.0 ms, read: 473.6Β±116.1 MB/s, size: 110.4 KB)
val: Scanning /home/jovyan/work/jupyter/content/SemanticSlicer/datasets/VisDrone/labels/val.cache... 548 images, 0 backgrounds, 0 corrupt: 100% ━━━━━━━━━━━━ 548/548 114.9Mit/s 0.0s
Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 35/35 1.8it/s 19.2s0.3ss
all 548 38759 0.657 0.587 0.604 0.377
pedestrian 520 8844 0.749 0.672 0.725 0.38
people 482 5125 0.709 0.568 0.589 0.268
bicycle 364 1287 0.5 0.448 0.426 0.222
car 515 14064 0.843 0.885 0.91 0.666
van 421 1975 0.653 0.587 0.617 0.455
truck 266 750 0.633 0.533 0.543 0.375
tricycle 337 1045 0.59 0.522 0.505 0.305
awning-tricycle 220 532 0.413 0.274 0.264 0.173
bus 131 251 0.78 0.708 0.762 0.568
motor 485 4886 0.704 0.675 0.7 0.361
Speed: 1.8ms preprocess, 14.4ms inference, 0.0ms loss, 12.5ms postprocess per image
Results saved to /home/jovyan/work/jupyter/runs/detect/val-54
2026-05-08 11:05:24,169 [unified] INFO: Standard@1280: mAP50=0.6040 P=0.6574 R=0.5873
Ultralytics 8.4.41 πŸš€ Python-3.12.13 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24564MiB)
YOLOv8l-p2 summary (fused): 139 layers, 42,827,064 parameters, 0 gradients, 204.8 GFLOPs
val: Fast image access βœ… (ping: 0.0Β±0.0 ms, read: 600.0Β±217.1 MB/s, size: 165.1 KB)
val: Scanning /home/jovyan/work/jupyter/content/SemanticSlicer/datasets/VisDrone/labels/val.cache... 548 images, 0 backgrounds, 0 corrupt: 100% ━━━━━━━━━━━━ 548/548 143.7Mit/s 0.0s
Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 35/35 1.5it/s 23.1s0.4ss
all 548 38759 0.665 0.591 0.611 0.384
pedestrian 520 8844 0.762 0.674 0.733 0.385
people 482 5125 0.714 0.564 0.591 0.271
bicycle 364 1287 0.527 0.472 0.443 0.233
car 515 14064 0.849 0.88 0.905 0.668
van 421 1975 0.649 0.585 0.615 0.459
truck 266 750 0.626 0.541 0.551 0.374
tricycle 337 1045 0.561 0.513 0.504 0.307
awning-tricycle 220 532 0.474 0.276 0.304 0.205
bus 131 251 0.779 0.725 0.768 0.576
motor 485 4886 0.712 0.675 0.701 0.362
Speed: 2.4ms preprocess, 21.1ms inference, 0.2ms loss, 11.8ms postprocess per image
Results saved to /home/jovyan/work/jupyter/runs/detect/val-55
2026-05-08 11:05:55,480 [unified] INFO: Standard@1536: mAP50=0.6114 P=0.6654 R=0.5905
2026-05-08 11:05:55,727 [unified] INFO: Standard best: {
"imgsz": 1536,
"mAP50": 0.611387921157732,
"mAP50_95": 0.3837783327235838,
"precision": 0.6653775463907172,
"recall": 0.5905031273406116
}
2026-05-08 11:05:55,729 [unified] INFO: ======================================================================
2026-05-08 11:05:55,730 [unified] INFO: Phase 3a: SAHI Baseline (Uniform 640Β² + CDN)
2026-05-08 11:05:55,730 [unified] INFO: ======================================================================
2026-05-08 11:06:09,303 [unified] INFO: [50/548] tp=1946 fp=1610 gt=2466
2026-05-08 11:06:16,806 [unified] INFO: [100/548] tp=4229 fp=3391 gt=5429
2026-05-08 11:06:26,792 [unified] INFO: [150/548] tp=7107 fp=5516 gt=9041
2026-05-08 11:06:35,528 [unified] INFO: [200/548] tp=9574 fp=7377 gt=12330
2026-05-08 11:06:47,669 [unified] INFO: [250/548] tp=11864 fp=8855 gt=15156
2026-05-08 11:06:59,449 [unified] INFO: [300/548] tp=14666 fp=10784 gt=18642
2026-05-08 11:07:11,197 [unified] INFO: [350/548] tp=17785 fp=13274 gt=22609
2026-05-08 11:07:28,899 [unified] INFO: [400/548] tp=23120 fp=17306 gt=29302
2026-05-08 11:07:40,443 [unified] INFO: [450/548] tp=26093 fp=19162 gt=32923
2026-05-08 11:07:51,870 [unified] INFO: [500/548] tp=28749 fp=20850 gt=36125
2026-05-08 11:08:01,631 [unified] INFO: mAP50=0.5587
2026-05-08 11:08:01,634 [unified] INFO: SAHI: F1=0.6702 P=0.5782 R=0.7971 tiles=5.19
2026-05-08 11:08:01,635 [unified] INFO: ======================================================================
2026-05-08 11:08:01,635 [unified] INFO: Phase 3b: Accuracy Mode (低conf + 高overlap + CDN)
2026-05-08 11:08:01,635 [unified] INFO: ======================================================================
2026-05-08 11:08:13,400 [unified] INFO: [50/548] tp=1946 fp=1610 gt=2466
2026-05-08 11:08:21,050 [unified] INFO: [100/548] tp=4229 fp=3391 gt=5429
2026-05-08 11:08:29,138 [unified] INFO: [150/548] tp=7107 fp=5516 gt=9041
2026-05-08 11:08:35,879 [unified] INFO: [200/548] tp=9574 fp=7377 gt=12330
2026-05-08 11:08:46,425 [unified] INFO: [250/548] tp=11864 fp=8855 gt=15156
2026-05-08 11:08:57,689 [unified] INFO: [300/548] tp=14666 fp=10784 gt=18642
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