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""" |
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An awesome colormap for really neat visualizations. |
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Copied from Detectron, and removed gray colors. |
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""" |
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import numpy as np |
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import random |
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__all__ = ["colormap", "random_color", "random_colors"] |
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_COLORS = np.array( |
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[ |
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0.000, 0.447, 0.741, |
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0.850, 0.325, 0.098, |
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0.929, 0.694, 0.125, |
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0.494, 0.184, 0.556, |
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0.466, 0.674, 0.188, |
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0.301, 0.745, 0.933, |
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0.635, 0.078, 0.184, |
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0.300, 0.300, 0.300, |
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0.600, 0.600, 0.600, |
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1.000, 0.000, 0.000, |
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1.000, 0.500, 0.000, |
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0.749, 0.749, 0.000, |
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0.000, 1.000, 0.000, |
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0.000, 0.000, 1.000, |
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0.667, 0.000, 1.000, |
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0.333, 0.333, 0.000, |
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0.333, 0.667, 0.000, |
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0.333, 1.000, 0.000, |
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0.667, 0.333, 0.000, |
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0.667, 0.667, 0.000, |
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0.667, 1.000, 0.000, |
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1.000, 0.333, 0.000, |
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1.000, 0.667, 0.000, |
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1.000, 1.000, 0.000, |
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0.000, 0.333, 0.500, |
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0.000, 0.667, 0.500, |
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0.000, 1.000, 0.500, |
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0.333, 0.000, 0.500, |
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0.333, 0.333, 0.500, |
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0.333, 0.667, 0.500, |
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0.333, 1.000, 0.500, |
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0.667, 0.000, 0.500, |
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0.667, 0.333, 0.500, |
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0.667, 0.667, 0.500, |
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0.667, 1.000, 0.500, |
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1.000, 0.000, 0.500, |
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1.000, 0.333, 0.500, |
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1.000, 0.667, 0.500, |
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1.000, 1.000, 0.500, |
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0.000, 0.333, 1.000, |
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0.000, 0.667, 1.000, |
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0.000, 1.000, 1.000, |
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0.333, 0.000, 1.000, |
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0.333, 0.333, 1.000, |
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0.333, 0.667, 1.000, |
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0.333, 1.000, 1.000, |
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0.667, 0.000, 1.000, |
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0.667, 0.333, 1.000, |
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0.667, 0.667, 1.000, |
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0.667, 1.000, 1.000, |
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1.000, 0.000, 1.000, |
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1.000, 0.333, 1.000, |
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1.000, 0.667, 1.000, |
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0.333, 0.000, 0.000, |
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0.500, 0.000, 0.000, |
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0.667, 0.000, 0.000, |
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0.833, 0.000, 0.000, |
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1.000, 0.000, 0.000, |
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0.000, 0.167, 0.000, |
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0.000, 0.333, 0.000, |
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0.000, 0.500, 0.000, |
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0.000, 0.667, 0.000, |
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0.000, 0.833, 0.000, |
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0.000, 1.000, 0.000, |
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0.000, 0.000, 0.167, |
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0.000, 0.000, 0.333, |
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0.000, 0.000, 0.500, |
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0.000, 0.000, 0.667, |
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0.000, 0.000, 0.833, |
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0.000, 0.000, 1.000, |
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0.000, 0.000, 0.000, |
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0.143, 0.143, 0.143, |
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0.857, 0.857, 0.857, |
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1.000, 1.000, 1.000 |
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] |
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).astype(np.float32).reshape(-1, 3) |
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def colormap(rgb=False, maximum=255): |
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""" |
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Args: |
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rgb (bool): whether to return RGB colors or BGR colors. |
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maximum (int): either 255 or 1 |
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Returns: |
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ndarray: a float32 array of Nx3 colors, in range [0, 255] or [0, 1] |
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""" |
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assert maximum in [255, 1], maximum |
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c = _COLORS * maximum |
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if not rgb: |
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c = c[:, ::-1] |
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return c |
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def random_color(rgb=False, maximum=255): |
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""" |
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Args: |
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rgb (bool): whether to return RGB colors or BGR colors. |
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maximum (int): either 255 or 1 |
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Returns: |
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ndarray: a vector of 3 numbers |
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""" |
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idx = np.random.randint(0, len(_COLORS)) |
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ret = _COLORS[idx] * maximum |
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if not rgb: |
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ret = ret[::-1] |
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return ret |
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def random_colors(N, rgb=False, maximum=255): |
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""" |
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Args: |
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N (int): number of unique colors needed |
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rgb (bool): whether to return RGB colors or BGR colors. |
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maximum (int): either 255 or 1 |
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Returns: |
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ndarray: a list of random_color |
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""" |
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indices = random.sample(range(len(_COLORS)), N) |
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ret = [_COLORS[i] * maximum for i in indices] |
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if not rgb: |
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ret = [x[::-1] for x in ret] |
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return ret |
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if __name__ == "__main__": |
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import cv2 |
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size = 100 |
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H, W = 10, 10 |
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canvas = np.random.rand(H * size, W * size, 3).astype("float32") |
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for h in range(H): |
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for w in range(W): |
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idx = h * W + w |
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if idx >= len(_COLORS): |
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break |
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canvas[h * size : (h + 1) * size, w * size : (w + 1) * size] = _COLORS[idx] |
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cv2.imshow("a", canvas) |
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cv2.waitKey(0) |
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