updates
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@ -11,7 +11,8 @@ gsutil cp gs://ultralytics/yolov3.pt yolov3/weights
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python3 detect.py
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python3 detect.py
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# Test
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# Test
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python3 test.py --img_size 416 --weights weights/latest.pt
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sudo rm -rf yolov3 && git clone https://github.com/ultralytics/yolov3 && cd yolov3
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python3 test.py --weights weights/yolov3.weights
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# Test Darknet
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# Test Darknet
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python3 test.py --img_size 416 --weights ../darknet/backup/yolov3.backup
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python3 test.py --img_size 416 --weights ../darknet/backup/yolov3.backup
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@ -392,6 +392,7 @@ def non_max_suppression(prediction, conf_thres=0.5, nms_thres=0.4):
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# 64 5000 0.619 0.579 0.568
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# 64 5000 0.619 0.579 0.568
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# 96 5000 0.652 0.622 0.613
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# 96 5000 0.652 0.622 0.613
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# 128 5000 0.651 0.625 0.617
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# 128 5000 0.651 0.625 0.617
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# 5000 5000 0.627 0.593 0.584
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elif nms_style == 'AND': # requires overlap, single boxes erased
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elif nms_style == 'AND': # requires overlap, single boxes erased
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while len(dc) > 1:
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while len(dc) > 1:
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@ -405,7 +406,7 @@ def non_max_suppression(prediction, conf_thres=0.5, nms_thres=0.4):
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iou = bbox_iou(dc[:1], dc[0:]) # iou with other boxes
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iou = bbox_iou(dc[:1], dc[0:]) # iou with other boxes
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i = iou > nms_thres
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i = iou > nms_thres
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weights = dc[i, 4:5] * dc[i, 5:6]
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weights = (dc[i, 4:5] * dc[i, 5:6]) ** 0.5
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dc[0, :4] = (weights * dc[i, :4]).sum(0) / weights.sum()
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dc[0, :4] = (weights * dc[i, :4]).sum(0) / weights.sum()
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det_max.append(dc[:1])
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det_max.append(dc[:1])
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dc = dc[iou < nms_thres]
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dc = dc[iou < nms_thres]
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