mirror of https://github.com/WongKinYiu/yolov7.git
Merge 40c8731b50
into 44f30af0da
commit
d558bf24de
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@ -485,7 +485,7 @@ class LoadImagesAndLabels(Dataset):
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self.im_files = list(cache.keys()) # update
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self.label_files = img2label_paths(cache.keys()) # update
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n = len(shapes) # number of images
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bi = np.floor(np.arange(n) / batch_size).astype(np.int) # batch index
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bi = np.floor(np.arange(n) / batch_size).astype(int) # batch index
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nb = bi[-1] + 1 # number of batches
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self.batch = bi # batch index of image
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self.n = n
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@ -528,7 +528,7 @@ class LoadImagesAndLabels(Dataset):
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elif mini > 1:
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shapes[i] = [1, 1 / mini]
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self.batch_shapes = np.ceil(np.array(shapes) * img_size / stride + pad).astype(np.int) * stride
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self.batch_shapes = np.ceil(np.array(shapes) * img_size / stride + pad).astype(int) * stride
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# Cache images into RAM/disk for faster training (WARNING: large datasets may exceed system resources)
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self.ims = [None] * n
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@ -137,7 +137,7 @@ def plot_images_and_masks(images, targets, masks, paths=None, fname='images.jpg'
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if mh != h or mw != w:
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mask = image_masks[j].astype(np.uint8)
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mask = cv2.resize(mask, (w, h))
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mask = mask.astype(np.bool)
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mask = mask.astype(bool)
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else:
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mask = image_masks[j].astype(np.bool)
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with contextlib.suppress(Exception):
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