updates
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@ -269,7 +269,7 @@ class LoadImagesAndLabels(Dataset): # for training/testing
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# Augment image and labels
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# Augment image and labels
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if self.augment:
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if self.augment:
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img, labels = random_affine(img, labels, degrees=(-5, 5), translate=(0.10, 0.10), scale=(0.90, 1.10))
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img, labels = random_affine(img, labels, degrees=(-5, 5), translate=(0.0, 0.0), scale=(1.0, 1.0))
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nL = len(labels) # number of labels
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nL = len(labels) # number of labels
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if nL:
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if nL:
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@ -80,7 +80,7 @@ sudo shutdown
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./darknet detector train ../supermarket2/supermarket2.data ../yolov3-tiny-sm2-1cls.cfg yolov3-tiny.conv.15 -map -dont_show # train tiny
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./darknet detector train ../supermarket2/supermarket2.data ../yolov3-tiny-sm2-1cls.cfg yolov3-tiny.conv.15 -map -dont_show # train tiny
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./darknet detector train ../supermarket2/supermarket2.data cfg/yolov3-spp-sm2-1cls.cfg backup/yolov3-spp-sm2-1cls_last.weights # resume
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./darknet detector train ../supermarket2/supermarket2.data cfg/yolov3-spp-sm2-1cls.cfg backup/yolov3-spp-sm2-1cls_last.weights # resume
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python3 train.py --data ../supermarket2/supermarket2.data --cfg cfg/yolov3-spp-sm2-1cls.cfg --epochs 100 --num-workers 8 --img-size 320 # train ultralytics
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python3 train.py --data ../supermarket2/supermarket2.data --cfg ../yolov3-spp-sm2-1cls.cfg --epochs 100 --num-workers 8 --img-size 320 --nosave # train ultralytics
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python3 test.py --data ../supermarket2/supermarket2.data --weights ../darknet/backup/yolov3-spp-sm2-1cls_5000.weights --cfg cfg/yolov3-spp-sm2-1cls.cfg # test
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python3 test.py --data ../supermarket2/supermarket2.data --weights ../darknet/backup/yolov3-spp-sm2-1cls_5000.weights --cfg cfg/yolov3-spp-sm2-1cls.cfg # test
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gsutil cp -r backup/*.weights gs://sm6/weights # weights to bucket
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gsutil cp -r backup/*.weights gs://sm6/weights # weights to bucket
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