updates
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@@ -100,7 +100,8 @@ class load_images_and_labels(): # for training
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ia = self.count * self.batch_size
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ib = min((self.count + 1) * self.batch_size, self.nF)
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if self.augment is True:
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multi_scale = False
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if multi_scale and self.augment:
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# Multi-Scale YOLO Training
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height = random.choice(range(10, 20)) * 32 # 320 - 608 pixels
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else:
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