mirror of https://github.com/AlexeyAB/darknet.git
Fixed new_coords=1 scale_x_y = 2.0 for yolov4x-mish.cfg and yolov4-csp.cfg
This commit is contained in:
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eb208de417
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6d5addd176
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@ -26,7 +26,7 @@ mosaic=1
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letter_box=1
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letter_box=1
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optimized_memory=1
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#optimized_memory=1
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#23:104x104 54:52x52 85:26x26 104:13x13 for 416
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#23:104x104 54:52x52 85:26x26 104:13x13 for 416
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@ -1032,6 +1032,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
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classes=80
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classes=80
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num=9
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num=9
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jitter=.1
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jitter=.1
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scale_x_y = 2.0
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objectness_smooth=0
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objectness_smooth=0
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ignore_thresh = .7
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ignore_thresh = .7
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truth_thresh = 1
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truth_thresh = 1
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@ -1145,6 +1146,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
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classes=80
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classes=80
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num=9
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num=9
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jitter=.1
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jitter=.1
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scale_x_y = 2.0
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objectness_smooth=1
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objectness_smooth=1
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ignore_thresh = .7
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ignore_thresh = .7
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truth_thresh = 1
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truth_thresh = 1
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@ -1258,6 +1260,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
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classes=80
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classes=80
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num=9
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num=9
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jitter=.1
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jitter=.1
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scale_x_y = 2.0
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objectness_smooth=1
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objectness_smooth=1
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ignore_thresh = .7
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ignore_thresh = .7
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truth_thresh = 1
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truth_thresh = 1
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@ -26,7 +26,7 @@ mosaic=1
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letter_box=1
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letter_box=1
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optimized_memory=1
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#optimized_memory=1
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[convolutional]
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[convolutional]
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batch_normalize=1
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batch_normalize=1
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@ -1159,6 +1159,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
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classes=80
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classes=80
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num=9
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num=9
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jitter=.1
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jitter=.1
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scale_x_y = 2.0
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objectness_smooth=0
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objectness_smooth=0
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ignore_thresh = .7
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ignore_thresh = .7
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truth_thresh = 1
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truth_thresh = 1
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@ -1288,6 +1289,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
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classes=80
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classes=80
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num=9
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num=9
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jitter=.1
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jitter=.1
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scale_x_y = 2.0
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objectness_smooth=1
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objectness_smooth=1
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ignore_thresh = .7
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ignore_thresh = .7
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truth_thresh = 1
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truth_thresh = 1
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@ -1417,6 +1419,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
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classes=80
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classes=80
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num=9
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num=9
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jitter=.1
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jitter=.1
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scale_x_y = 2.0
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objectness_smooth=1
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objectness_smooth=1
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ignore_thresh = .7
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ignore_thresh = .7
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truth_thresh = 1
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truth_thresh = 1
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@ -26,7 +26,7 @@ mosaic=1
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letter_box=1
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letter_box=1
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optimized_memory=1
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#optimized_memory=1
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#23:104x104 54:52x52 85:26x26 104:13x13 for 416
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#23:104x104 54:52x52 85:26x26 104:13x13 for 416
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@ -1032,6 +1032,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
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classes=80
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classes=80
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num=9
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num=9
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jitter=.1
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jitter=.1
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scale_x_y = 2.0
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objectness_smooth=0
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objectness_smooth=0
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ignore_thresh = .7
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ignore_thresh = .7
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truth_thresh = 1
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truth_thresh = 1
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@ -1145,6 +1146,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
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classes=80
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classes=80
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num=9
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num=9
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jitter=.1
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jitter=.1
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scale_x_y = 2.0
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objectness_smooth=1
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objectness_smooth=1
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ignore_thresh = .7
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ignore_thresh = .7
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truth_thresh = 1
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truth_thresh = 1
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@ -1258,6 +1260,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
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classes=80
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classes=80
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num=9
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num=9
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jitter=.1
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jitter=.1
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scale_x_y = 2.0
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objectness_smooth=1
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objectness_smooth=1
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ignore_thresh = .7
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ignore_thresh = .7
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truth_thresh = 1
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truth_thresh = 1
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@ -26,7 +26,7 @@ mosaic=1
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letter_box=1
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letter_box=1
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optimized_memory=1
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#optimized_memory=1
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[convolutional]
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[convolutional]
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batch_normalize=1
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batch_normalize=1
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@ -1159,6 +1159,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
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classes=80
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classes=80
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num=9
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num=9
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jitter=.1
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jitter=.1
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scale_x_y = 2.0
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objectness_smooth=0
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objectness_smooth=0
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ignore_thresh = .7
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ignore_thresh = .7
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truth_thresh = 1
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truth_thresh = 1
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@ -1288,6 +1289,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
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classes=80
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classes=80
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num=9
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num=9
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jitter=.1
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jitter=.1
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scale_x_y = 2.0
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objectness_smooth=1
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objectness_smooth=1
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ignore_thresh = .7
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ignore_thresh = .7
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truth_thresh = 1
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truth_thresh = 1
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@ -1417,6 +1419,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
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classes=80
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classes=80
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num=9
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num=9
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jitter=.1
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jitter=.1
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scale_x_y = 2.0
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objectness_smooth=1
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objectness_smooth=1
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ignore_thresh = .7
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ignore_thresh = .7
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truth_thresh = 1
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truth_thresh = 1
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@ -138,8 +138,8 @@ box get_yolo_box(float *x, float *biases, int n, int index, int i, int j, int lw
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// w = ln(t.w * net.w / anchors_w); // w - output of previous conv-layer
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// w = ln(t.w * net.w / anchors_w); // w - output of previous conv-layer
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// h = ln(t.h * net.h / anchors_h); // h - output of previous conv-layer
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// h = ln(t.h * net.h / anchors_h); // h - output of previous conv-layer
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if (new_coords) {
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if (new_coords) {
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b.x = (i + x[index + 0 * stride] * 2 - 0.5) / lw;
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b.x = (i + x[index + 0 * stride]) / lw;
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b.y = (j + x[index + 1 * stride] * 2 - 0.5) / lh;
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b.y = (j + x[index + 1 * stride]) / lh;
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b.w = x[index + 2 * stride] * x[index + 2 * stride] * 4 * biases[2 * n] / w;
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b.w = x[index + 2 * stride] * x[index + 2 * stride] * 4 * biases[2 * n] / w;
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b.h = x[index + 3 * stride] * x[index + 3 * stride] * 4 * biases[2 * n + 1] / h;
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b.h = x[index + 3 * stride] * x[index + 3 * stride] * 4 * biases[2 * n + 1] / h;
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}
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}
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@ -197,8 +197,8 @@ ious delta_yolo_box(box truth, float *x, float *biases, int n, int index, int i,
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float th = log(truth.h*h / biases[2 * n + 1]);
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float th = log(truth.h*h / biases[2 * n + 1]);
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if (new_coords) {
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if (new_coords) {
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tx = (truth.x*lw - i + 0.5) / 2;
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//tx = (truth.x*lw - i + 0.5) / 2;
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ty = (truth.y*lh - j + 0.5) / 2;
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//ty = (truth.y*lh - j + 0.5) / 2;
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tw = sqrt(truth.w*w / (4 * biases[2 * n]));
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tw = sqrt(truth.w*w / (4 * biases[2 * n]));
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th = sqrt(truth.h*h / (4 * biases[2 * n + 1]));
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th = sqrt(truth.h*h / (4 * biases[2 * n + 1]));
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}
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}
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