| # Copyright (c) Facebook, Inc. and its affiliates. | |
| """ | |
| An awesome colormap for really neat visualizations. | |
| Copied from Detectron, and removed gray colors. | |
| """ | |
| import numpy as np | |
| import random | |
| random.seed(0) | |
| __all__ = ["colormap", "random_color", "random_colors"] | |
| # fmt: off | |
| # RGB: | |
| # _COLORS = np.array( | |
| # [ | |
| # 0.000, 0.447, 0.741, | |
| # 0.850, 0.325, 0.098, | |
| # 0.929, 0.694, 0.125, | |
| # 0.494, 0.184, 0.556, | |
| # 0.466, 0.674, 0.188, | |
| # 0.301, 0.745, 0.933, | |
| # 0.635, 0.078, 0.184, | |
| # 0.300, 0.300, 0.300, | |
| # 0.600, 0.600, 0.600, | |
| # 1.000, 0.000, 0.000, | |
| # 1.000, 0.500, 0.000, | |
| # 0.749, 0.749, 0.000, | |
| # 0.000, 1.000, 0.000, | |
| # 0.000, 0.000, 1.000, | |
| # 0.667, 0.000, 1.000, | |
| # 0.333, 0.333, 0.000, | |
| # 0.333, 0.667, 0.000, | |
| # 0.333, 1.000, 0.000, | |
| # 0.667, 0.333, 0.000, | |
| # 0.667, 0.667, 0.000, | |
| # 0.667, 1.000, 0.000, | |
| # 1.000, 0.333, 0.000, | |
| # 1.000, 0.667, 0.000, | |
| # 1.000, 1.000, 0.000, | |
| # 0.000, 0.333, 0.500, | |
| # 0.000, 0.667, 0.500, | |
| # 0.000, 1.000, 0.500, | |
| # 0.333, 0.000, 0.500, | |
| # 0.333, 0.333, 0.500, | |
| # 0.333, 0.667, 0.500, | |
| # 0.333, 1.000, 0.500, | |
| # 0.667, 0.000, 0.500, | |
| # 0.667, 0.333, 0.500, | |
| # 0.667, 0.667, 0.500, | |
| # 0.667, 1.000, 0.500, | |
| # 1.000, 0.000, 0.500, | |
| # 1.000, 0.333, 0.500, | |
| # 1.000, 0.667, 0.500, | |
| # 1.000, 1.000, 0.500, | |
| # 0.000, 0.333, 1.000, | |
| # 0.000, 0.667, 1.000, | |
| # 0.000, 1.000, 1.000, | |
| # 0.333, 0.000, 1.000, | |
| # 0.333, 0.333, 1.000, | |
| # 0.333, 0.667, 1.000, | |
| # 0.333, 1.000, 1.000, | |
| # 0.667, 0.000, 1.000, | |
| # 0.667, 0.333, 1.000, | |
| # 0.667, 0.667, 1.000, | |
| # 0.667, 1.000, 1.000, | |
| # 1.000, 0.000, 1.000, | |
| # 1.000, 0.333, 1.000, | |
| # 1.000, 0.667, 1.000, | |
| # 0.333, 0.000, 0.000, | |
| # 0.500, 0.000, 0.000, | |
| # 0.667, 0.000, 0.000, | |
| # 0.833, 0.000, 0.000, | |
| # 1.000, 0.000, 0.000, | |
| # 0.000, 0.167, 0.000, | |
| # 0.000, 0.333, 0.000, | |
| # 0.000, 0.500, 0.000, | |
| # 0.000, 0.667, 0.000, | |
| # 0.000, 0.833, 0.000, | |
| # 0.000, 1.000, 0.000, | |
| # 0.000, 0.000, 0.167, | |
| # 0.000, 0.000, 0.333, | |
| # 0.000, 0.000, 0.500, | |
| # 0.000, 0.000, 0.667, | |
| # 0.000, 0.000, 0.833, | |
| # 0.000, 0.000, 1.000, | |
| # 0.000, 0.000, 0.000, | |
| # 0.143, 0.143, 0.143, | |
| # 0.857, 0.857, 0.857, | |
| # 1.000, 1.000, 1.000 | |
| # ] | |
| # ).astype(np.float32).reshape(-1, 3) | |
| # fmt: on | |
| _COLORS = [] | |
| def gen_color(): | |
| color = tuple(np.round(np.random.choice(range(256), size=3)/255, 3)) | |
| if color not in _COLORS and np.mean(color) != 0.0: | |
| _COLORS.append(color) | |
| else: | |
| gen_color() | |
| for _ in range(300): | |
| gen_color() | |
| def colormap(rgb=False, maximum=255): | |
| """ | |
| Args: | |
| rgb (bool): whether to return RGB colors or BGR colors. | |
| maximum (int): either 255 or 1 | |
| Returns: | |
| ndarray: a float32 array of Nx3 colors, in range [0, 255] or [0, 1] | |
| """ | |
| assert maximum in [255, 1], maximum | |
| c = _COLORS * maximum | |
| if not rgb: | |
| c = c[:, ::-1] | |
| return c | |
| def random_color(rgb=False, maximum=255): | |
| """ | |
| Args: | |
| rgb (bool): whether to return RGB colors or BGR colors. | |
| maximum (int): either 255 or 1 | |
| Returns: | |
| ndarray: a vector of 3 numbers | |
| """ | |
| idx = np.random.randint(0, len(_COLORS)) | |
| ret = _COLORS[idx] * maximum | |
| if not rgb: | |
| ret = ret[::-1] | |
| return ret | |
| def random_colors(N, rgb=False, maximum=255): | |
| """ | |
| Args: | |
| N (int): number of unique colors needed | |
| rgb (bool): whether to return RGB colors or BGR colors. | |
| maximum (int): either 255 or 1 | |
| Returns: | |
| ndarray: a list of random_color | |
| """ | |
| indices = random.sample(range(len(_COLORS)), N) | |
| ret = [_COLORS[i] * maximum for i in indices] | |
| if not rgb: | |
| ret = [x[::-1] for x in ret] | |
| return ret | |
| if __name__ == "__main__": | |
| import cv2 | |
| size = 100 | |
| H, W = 10, 10 | |
| canvas = np.random.rand(H * size, W * size, 3).astype("float32") | |
| for h in range(H): | |
| for w in range(W): | |
| idx = h * W + w | |
| if idx >= len(_COLORS): | |
| break | |
| canvas[h * size : (h + 1) * size, w * size : (w + 1) * size] = _COLORS[idx] | |
| cv2.imshow("a", canvas) | |
| cv2.waitKey(0) |