inference speed and mAP updates

This commit is contained in:
Glenn Jocher 2020-04-08 10:02:20 -07:00
parent f54d28ba63
commit 9f41b7601a
1 changed files with 7 additions and 7 deletions

View File

@ -138,24 +138,24 @@ Namespace(augment=True, batch_size=16, cfg='cfg/yolov3-spp.cfg', conf_thres=0.00
Using CUDA device0 _CudaDeviceProperties(name='Tesla V100-SXM2-16GB', total_memory=16130MB)
Class Images Targets P R mAP@0.5 F1: 100%|█████████| 313/313 [03:00<00:00, 1.74it/s]
all 5e+03 3.51e+04 0.375 0.743 0.639 0.493
all 5e+03 3.51e+04 0.375 0.743 0.64 0.492
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.455
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.646
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.496
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.263
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.500
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.501
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.596
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.362
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.361
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.597
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.666
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.491
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.492
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.719
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.808
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.810
Speed: 21.3/3.0/24.4 ms inference/NMS/total per 640x640 image at batch-size 16
Speed: 17.5/2.5/20.1 ms inference/NMS/total per 640x640 image at batch-size 16
```
<!-- Speed: 12.2/2.3/14.5 ms inference/NMS/total per 608x608 image at batch-size 1
<!-- Speed: 11.5/2.1/13.6 ms inference/NMS/total per 608x608 image at batch-size 1
# Reproduce Our Results