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@ -177,20 +177,18 @@ class LoadImagesAndLabels(Dataset): # for training/testing
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# Rectangular Training https://github.com/ultralytics/yolov3/issues/232
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if self.rect:
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# Read image shapes
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s = np.array([exif_size(Image.open(f)) for f in tqdm(self.img_files, desc='Reading image shapes')],
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dtype=np.float64)
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# sp = 'data' + os.sep + path.replace('.txt', '.shapes').split(os.sep)[-1] # shapefile path
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# if not os.path.exists(sp): # read shapes using PIL and write shapefile for next time (faster)
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# s = [exif_size(Image.open(f)) for f in tqdm(self.img_files, desc='Reading image shapes')]
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# np.savetxt(sp, s, fmt='%g')
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#
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# try:
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# with open(sp, 'r') as f: # read existing shapefile
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# s = np.array([x.split() for x in f.read().splitlines()], dtype=np.float64)
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# assert len(s) == n, 'Shapefile out of sync'
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# except:
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# os.remove(sp)
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# print('Shapefile deleted: %s. Please rerun again.' % sp)
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sp = 'data' + os.sep + path.replace('.txt', '.shapes').split(os.sep)[-1] # shapefile path
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if not os.path.exists(sp): # read shapes using PIL and write shapefile for next time (faster)
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s = [exif_size(Image.open(f)) for f in tqdm(self.img_files, desc='Reading image shapes')]
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np.savetxt(sp, s, fmt='%g')
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try:
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with open(sp, 'r') as f: # read existing shapefile
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s = np.array([x.split() for x in f.read().splitlines()], dtype=np.float64)
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assert len(s) == n, 'Shapefile out of sync'
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except:
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os.remove(sp)
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print('Shapefile deleted: %s. Please rerun again.' % sp)
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# Sort by aspect ratio
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ar = s[:, 1] / s[:, 0] # aspect ratio
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