Bienqq
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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2020-03-13 11:03:39 -07:00
parent 6aae5aca64
commit 0de07da612
2 changed files with 2 additions and 2 deletions
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2
README.md
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@ -174,7 +174,7 @@ Using CUDA device0 _CudaDeviceProperties(name='Tesla V100-SXM2-16GB', total_memo
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.649
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.735
Speed: 6.6/1.6/8.2 ms inference/NMS/total per 608x608 image at batch-size 32
Speed: 6.6/1.5/8.1 ms inference/NMS/total per 608x608 image at batch-size 32
```
# Reproduce Our Results

2
utils/utils.py
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@ -325,7 +325,7 @@ def box_iou(boxes1, boxes2):
lt = torch.max(boxes1[:, None, :2], boxes2[:, :2]) # [N,M,2]
rb = torch.min(boxes1[:, None, 2:], boxes2[:, 2:]) # [N,M,2]
inter = (rb - lt).clamp(min=0).prod(2) # [N,M]
inter = (rb - lt).clamp(0).prod(2) # [N,M]
return inter / (area1[:, None] + area2 - inter) # iou = inter / (area1 + area2 - inter)