Bienqq
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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2018-09-10 16:41:02 +02:00
parent ff04315f96
commit 300e2b5dfc
3 changed files with 10 additions and 2 deletions
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2
test.py
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@ -11,7 +11,7 @@ parser.add_argument('-weights_path', type=str, default='checkpoints/yolov3.weigh
parser.add_argument('-class_path', type=str, default='data/coco.names', help='path to class label file') parser.add_argument('-class_path', type=str, default='data/coco.names', help='path to class label file')
parser.add_argument('-iou_thres', type=float, default=0.5, help='iou threshold required to qualify as detected') parser.add_argument('-iou_thres', type=float, default=0.5, help='iou threshold required to qualify as detected')
parser.add_argument('-conf_thres', type=float, default=0.5, help='object confidence threshold') parser.add_argument('-conf_thres', type=float, default=0.5, help='object confidence threshold')
parser.add_argument('-nms_thres', type=float, default=0.45, help='iou threshold for non-maximum suppression') parser.add_argument('-nms_thres', type=float, default=0.4, help='iou threshold for non-maximum suppression')
parser.add_argument('-n_cpu', type=int, default=0, help='number of cpu threads to use during batch generation') parser.add_argument('-n_cpu', type=int, default=0, help='number of cpu threads to use during batch generation')
parser.add_argument('-img_size', type=int, default=416, help='size of each image dimension') parser.add_argument('-img_size', type=int, default=416, help='size of each image dimension')
parser.add_argument('-use_cuda', type=bool, default=True, help='whether to use cuda if available') parser.add_argument('-use_cuda', type=bool, default=True, help='whether to use cuda if available')

8
utils/gcp.sh
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@ -12,3 +12,11 @@ python3 detect.py
# Test # Test
python3 test.py -img_size 416 -weights_path checkpoints/yolov3.weights python3 test.py -img_size 416 -weights_path checkpoints/yolov3.weights
sudo rm -rf yolov3 && git clone https://github.com/ultralytics/yolov3
cd yolov3
cd checkpoints
wget https://pjreddie.com/media/files/yolov3.weights
cd ..
python3 test.py -img_size 416 -weights_path checkpoints/yolov3.weights

2
utils/utils.py
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@ -99,7 +99,7 @@ def ap_per_class(tp, conf, pred_cls, target_cls):
tp, conf, pred_cls = tp[i], conf[i], pred_cls[i] tp, conf, pred_cls = tp[i], conf[i], pred_cls[i]
# Find unique classes # Find unique classes
unique_classes = target_cls# np.unique(np.concatenate((pred_cls, target_cls), 0)) unique_classes = np.unique(np.concatenate((pred_cls, target_cls), 0))
# Create Precision-Recall curve and compute AP for each class # Create Precision-Recall curve and compute AP for each class
ap = [] ap = []