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import cv2
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import torch
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import numpy as np
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from PIL import Image
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import copy
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import time
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def colormap(rgb=True):
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color_list = np.array(
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[
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0.000, 0.000, 0.000,
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1.000, 1.000, 1.000,
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1.000, 0.498, 0.313,
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0.392, 0.581, 0.929,
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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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0.167, 0.000, 0.000,
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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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0.143, 0.143, 0.143,
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0.286, 0.286, 0.286,
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0.429, 0.429, 0.429,
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0.571, 0.571, 0.571,
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0.714, 0.714, 0.714,
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0.857, 0.857, 0.857
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]
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).astype(np.float32)
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color_list = color_list.reshape((-1, 3)) * 255
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if not rgb:
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color_list = color_list[:, ::-1]
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return color_list
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color_list = colormap()
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color_list = color_list.astype('uint8').tolist()
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def vis_add_mask(image, mask, color, alpha):
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color = np.array(color_list[color])
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mask = mask > 0.5
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image[mask] = image[mask] * (1-alpha) + color * alpha
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return image.astype('uint8')
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def point_painter(input_image, input_points, point_color=5, point_alpha=0.9, point_radius=15, contour_color=2, contour_width=5):
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h, w = input_image.shape[:2]
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point_mask = np.zeros((h, w)).astype('uint8')
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for point in input_points:
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point_mask[point[1], point[0]] = 1
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kernel = cv2.getStructuringElement(2, (point_radius, point_radius))
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point_mask = cv2.dilate(point_mask, kernel)
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contour_radius = (contour_width - 1) // 2
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dist_transform_fore = cv2.distanceTransform(point_mask, cv2.DIST_L2, 3)
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dist_transform_back = cv2.distanceTransform(1-point_mask, cv2.DIST_L2, 3)
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dist_map = dist_transform_fore - dist_transform_back
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contour_radius += 2
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contour_mask = np.abs(np.clip(dist_map, -contour_radius, contour_radius))
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contour_mask = contour_mask / np.max(contour_mask)
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contour_mask[contour_mask>0.5] = 1.
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painted_image = vis_add_mask(input_image.copy(), point_mask, point_color, point_alpha)
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painted_image = vis_add_mask(painted_image.copy(), 1-contour_mask, contour_color, 1)
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return painted_image
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def mask_painter(input_image, input_mask, mask_color=5, mask_alpha=0.7, contour_color=1, contour_width=3):
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assert input_image.shape[:2] == input_mask.shape, 'different shape between image and mask'
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mask = np.clip(input_mask, 0, 1)
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contour_radius = (contour_width - 1) // 2
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dist_transform_fore = cv2.distanceTransform(mask, cv2.DIST_L2, 3)
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dist_transform_back = cv2.distanceTransform(1-mask, cv2.DIST_L2, 3)
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dist_map = dist_transform_fore - dist_transform_back
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contour_radius += 2
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contour_mask = np.abs(np.clip(dist_map, -contour_radius, contour_radius))
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contour_mask = contour_mask / np.max(contour_mask)
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contour_mask[contour_mask>0.5] = 1.
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painted_image = vis_add_mask(input_image.copy(), mask.copy(), mask_color, mask_alpha)
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painted_image = vis_add_mask(painted_image.copy(), 1-contour_mask, contour_color, 1)
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return painted_image
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def background_remover(input_image, input_mask):
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"""
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input_image: H, W, 3, np.array
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input_mask: H, W, np.array
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image_wo_background: PIL.Image
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"""
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assert input_image.shape[:2] == input_mask.shape, 'different shape between image and mask'
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mask = np.expand_dims(np.clip(input_mask, 0, 1), axis=2)*255
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image_wo_background = np.concatenate([input_image, mask], axis=2)
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image_wo_background = Image.fromarray(image_wo_background).convert('RGBA')
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return image_wo_background
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if __name__ == '__main__':
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input_image = np.array(Image.open('images/painter_input_image.jpg').convert('RGB'))
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input_mask = np.array(Image.open('images/painter_input_mask.jpg').convert('P'))
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mask_color = 3
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mask_alpha = 0.7
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contour_color = 1
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contour_width = 5
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painted_image = Image.fromarray(input_image)
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painted_image.save('images/original.png')
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painted_image = mask_painter(input_image, input_mask, mask_color, mask_alpha, contour_color, contour_width)
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painted_image = Image.fromarray(input_image)
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painted_image.save('images/original1.png')
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input_image = np.array(Image.open('images/painter_input_image.jpg').convert('RGB'))
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input_points = np.array([[500, 375], [70, 600]])
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point_color = 5
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point_alpha = 0.9
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point_radius = 15
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contour_color = 2
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contour_width = 5
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painted_image_1 = point_painter(input_image, input_points, point_color, point_alpha, point_radius, contour_color, contour_width)
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painted_image = Image.fromarray(painted_image_1)
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painted_image.save('images/point_painter_1.png')
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input_image = np.array(Image.open('images/painter_input_image.jpg').convert('RGB'))
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painted_image_2 = point_painter(input_image, input_points, point_color=9, point_radius=20, contour_color=29)
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painted_image = Image.fromarray(painted_image_2)
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painted_image.save('images/point_painter_2.png')
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input_image = np.array(Image.open('images/original.png').convert('RGB'))
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image_wo_background = background_remover(input_image, input_mask)
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image_wo_background.save('images/image_wo_background.png')
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