dataset.py: cleanup
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6ba2cd9e5d
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11959eef61
19
dataset.py
19
dataset.py
@ -267,26 +267,14 @@ class CTDDataset(Dataset):
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def __getitem__(self, index):
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# find path
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left_path = self.imgs[index]
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prefix = left_path[: left_path.rfind("_")]
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# right_path = prefix + "_right.jpg"
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left_disp_path = left_path.replace('im', 'disp')
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# right_disp_path = prefix + "_right.disp.png"
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# read img, disp
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# left_img = cv2.imread(left_path, cv2.IMREAD_COLOR)
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# right_img = cv2.imread(right_path, cv2.IMREAD_COLOR)
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# left_img = np.load(left_path).transpose(1,2,0)
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left_img = np.load(left_path)
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# left_img = cv2.cvtColor(left_img, cv2.COLOR_GRAY2RGB)
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# FIXME DO WE NEED THIS? OTHERWISE IT's PRETTY DARK
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left_img = cv2.normalize(left_img, None, 0, 255, cv2.NORM_MINMAX, cv2.CV_8U)
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# left_img = cv2.merge([left_img, left_img, left_img]).reshape((3, 480, 640))
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left_img = cv2.merge([left_img, left_img, left_img]).reshape((480, 640, 3))
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right_img = self.pattern
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# right_img = cv2.merge([right_img, right_img, right_img]).reshape((3, 480, 640))
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left_disp = self.get_disp(left_disp_path)
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# right_disp = self.get_disp(right_disp_path)
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if False: # self.rng.binomial(1, 0.5):
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left_img, right_img = np.fliplr(right_img), np.fliplr(left_img)
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@ -308,12 +296,7 @@ class CTDDataset(Dataset):
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left_img, right_img, left_disp
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)
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# left_img = left_img.transpose(2, 0, 1).astype("uint8")
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# left_img = left_img.transpose(2, 0, 1).astype("float32")
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# left_img = left_img.astype("float32")
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right_img = right_img.transpose(2, 0, 1).astype("uint8")
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# right_img = right_img.astype("float32")
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# print('post_augment', left_img)
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right_img = right_img.transpose((2, 0, 1)).astype("uint8")
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return {
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"left": left_img,
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