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import cv2 |
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import numpy as np |
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from utils.ops import minmax |
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def read_gray_array(path, div_255=False, to_normalize=False, thr=-1, dtype=np.float32) -> np.ndarray: |
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""" |
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1. read the binary image with the suffix `.jpg` or `.png` |
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into a grayscale ndarray |
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2. (to_normalize=True) rescale the ndarray to [0, 1] |
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3. (thr >= 0) binarize the ndarray with `thr` |
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4. return a gray ndarray (np.float32) |
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""" |
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assert path.endswith(".jpg") or path.endswith(".png"), path |
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assert not div_255 or not to_normalize, path |
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gray_array = cv2.imread(path, cv2.IMREAD_GRAYSCALE) |
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assert gray_array is not None, f"Image Not Found: {path}" |
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if div_255: |
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gray_array = gray_array / 255 |
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if to_normalize: |
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gray_array = minmax(gray_array, up_bound=255) |
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if thr >= 0: |
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gray_array = gray_array > thr |
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return gray_array.astype(dtype) |
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def read_color_array(path: str): |
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assert path.endswith(".jpg") or path.endswith(".png") |
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bgr_array = cv2.imread(path, cv2.IMREAD_COLOR) |
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assert bgr_array is not None, f"Image Not Found: {path}" |
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rgb_array = cv2.cvtColor(bgr_array, cv2.COLOR_BGR2RGB) |
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return rgb_array |
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