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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,135 @@ | ||
| # SLIC (Simple Linear Iterative Clustering) segmentation algorithm. | ||
| # Original link: https://stackoverflow.com/a/57746835/7550928 | ||
| import numpy as np | ||
| import cv2 | ||
| from skimage import segmentation | ||
| from skimage.segmentation import mark_boundaries | ||
| from skimage.data import astronaut | ||
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| def slic_segmentation(image, segments): | ||
| """ Calculate average color of a superpixel in scikit-image library """ | ||
| reshaped = image.reshape((image.shape[0]*image.shape[1], image.shape[2])) | ||
| slic_1d = np.reshape(segments, -1) | ||
| uni = np.unique(slic_1d) | ||
| mask = np.zeros(reshaped.shape) | ||
| for i in uni: | ||
| loc = np.where(slic_1d==i)[0] | ||
| mask[loc, :] = np.mean(reshaped[loc, :], axis=0) | ||
| return np.reshape(mask, [image.shape[0], image.shape[1], image.shape[2]]).astype('uint8') | ||
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| input = cv2.cvtColor(astronaut(), cv2.COLOR_BGR2RGB) | ||
| segments = segmentation.slic(input, compactness=10, n_segments=1000, sigma=3) | ||
| output = slic_segmentation(input, segments) | ||
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| cv2.imshow('Original image', input) | ||
| cv2.imshow('SLIC segmentation', output) | ||
| cv2.imshow('With boundaries', mark_boundaries(input, segments)) | ||
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| cv2.waitKey(0) # press any key to close the window | ||
| cv2.destroyAllWindows() | ||
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| if __name__ == '__main__': | ||
| def nothing(*arg): | ||
| pass | ||
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| cv2.namedWindow('SEEDS') | ||
| cv2.createTrackbar('Number of Superpixels', 'SEEDS', 400, 1000, nothing) | ||
| cv2.createTrackbar('Iterations', 'SEEDS', 4, 12, nothing) | ||
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| seeds = None | ||
| display_mode = 0 | ||
| num_superpixels = 400 | ||
| prior = 2 | ||
| num_levels = 4 | ||
| num_histogram_bins = 5 | ||
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| cap = cv2.VideoCapture(0) # get default camera | ||
| while True: | ||
| flag, img = cap.read() | ||
| converted_img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) | ||
| height, width, channels = converted_img.shape | ||
| num_superpixels_new = cv2.getTrackbarPos('Number of Superpixels', 'SEEDS') | ||
| num_iterations = cv2.getTrackbarPos('Iterations', 'SEEDS') | ||
|
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| if not seeds or num_superpixels_new != num_superpixels: | ||
| num_superpixels = num_superpixels_new | ||
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| seeds = cv2.ximgproc.createSuperpixelSEEDS( | ||
| width, height, channels, num_superpixels, num_levels, prior, num_histogram_bins) | ||
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| color_img = np.zeros((height, width, 3), np.uint8) | ||
| color_img[:] = (0, 0, 255) | ||
| seeds.iterate(converted_img, num_iterations) | ||
| mask = seeds.getLabelContourMask(False) | ||
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| if display_mode == 0: | ||
| # Stitch foreground & background together | ||
| mask_inv = cv2.bitwise_not(mask) | ||
| result_bg = cv2.bitwise_and(img, img, mask=mask_inv) | ||
| result_fg = cv2.bitwise_and(color_img, color_img, mask=mask) | ||
| result = cv2.add(result_bg, result_fg) | ||
| cv2.imshow('SEEDS', result) | ||
| elif display_mode == 1: | ||
| labels = seeds.getLabels() | ||
| segments = slic_segmentation(img, labels) | ||
| cv2.imshow('SEEDS', segments) | ||
| else: | ||
| cv2.imshow('SEEDS', mask) | ||
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| ch = cv2.waitKey(1) | ||
| if ch == 27: | ||
| break | ||
| elif ch & 0xff == ord(' '): | ||
| display_mode = (display_mode + 1) % 3 | ||
| cv2.destroyAllWindows() | ||
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| def nothing(*arg): | ||
| pass | ||
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| cv2.namedWindow('SLIC') | ||
| cv2.createTrackbar('Region Size', 'SLIC', 32, 100, nothing) | ||
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| seeds = None | ||
| display_mode = 0 | ||
| region_size = 32 | ||
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| cap = cv2.VideoCapture(0) # get default camera | ||
| while True: | ||
| flag, img = cap.read() | ||
| converted_img = cv2.GaussianBlur(img, (5, 5), 0) # gaussian blur | ||
| converted_img = cv2.cvtColor(converted_img, cv2.COLOR_BGR2LAB) # convert to LAB | ||
| height, width, channels = converted_img.shape | ||
| region_size_new = cv2.getTrackbarPos('Region Size', 'SLIC') | ||
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| if not seeds or region_size_new != region_size: | ||
| region_size = region_size_new | ||
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| seeds = cv_slic = cv2.ximgproc.createSuperpixelSLIC( | ||
| converted_img, algorithm=cv2.ximgproc.SLICO, region_size=region_size) | ||
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| color_img = np.zeros((height, width, 3), np.uint8) | ||
| color_img[:] = (0, 0, 255) | ||
| seeds.iterate() | ||
| mask = seeds.getLabelContourMask(False) | ||
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| # Stitch foreground & background together | ||
| mask_inv = cv2.bitwise_not(mask) | ||
| result_bg = cv2.bitwise_and(img, img, mask=mask_inv) | ||
| result_fg = cv2.bitwise_and(color_img, color_img, mask=mask) | ||
| result = cv2.add(result_bg, result_fg) | ||
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| if display_mode == 0: | ||
| cv2.imshow('SLIC', result) | ||
| else: | ||
| cv2.imshow('SLIC', mask) | ||
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| ch = cv2.waitKey(1) | ||
| if ch == 27: | ||
| break | ||
| elif ch & 0xff == ord(' '): | ||
| display_mode = (display_mode + 1) % 2 | ||
| cv2.destroyAllWindows() |