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cv2.grabCut(img, labels, (x, y, w, h), None, None, 5, cv2.GC_INIT_WITH_RECT) + +show_img = np.copy(img) +show_img[(labels == cv2.GC_PR_BGD) | (labels == cv2.GC_BGD)] //= 3 + +cv2.imshow('image', show_img) +cv2.waitKey() +cv2.destroyAllWindows() + + +label = cv2.GC_BGD +lbl_clrs = {cv2.GC_BGD: (0, 0, 0), cv2.GC_FGD: (255, 255, 255)} + + +def mouse_callback(event, x, y, flags, param): + global mouse_pressed + + if event == cv2.EVENT_LBUTTONDOWN: + mouse_pressed = True + cv2.circle(labels, (x, y), 5, label, cv2.FILLED) + cv2.circle(show_img, (x, y), 5, lbl_clrs[label], cv2.FILLED) + + elif event == cv2.EVENT_MOUSEMOVE: + if mouse_pressed: + cv2.circle(labels, (x, y), 5, label, cv2.FILLED) + cv2.circle(show_img, (x, y), 5, lbl_clrs[label], cv2.FILLED) + + elif event == cv2.EVENT_LBUTTONUP: + mouse_pressed = False + + +cv2.namedWindow('image') +cv2.setMouseCallback('image', mouse_callback) + +while True: + cv2.imshow('image', show_img) + k = cv2.waitKey(1) + + if k == ord('a') and not mouse_pressed: + break + + elif k == ord('1'): + label = cv2.GC_FGD - label + +cv2.destroyAllWindows() + + +labels, bgdModel, fgdModel = cv2.grabCut(img, labels, None, bgdModel, fgdModel, 5, cv2.GC_INIT_WITH_MASK) +show_img = np.copy(img) +show_img[(labels == cv2.GC_PR_BGD) | (labels == cv2.GC_BGD)] //= 3 + +cv2.imshow('image', show_img) +cv2.waitKey() +cv2.destroyAllWindows() \ No newline at end of file diff --git a/k-means.py b/k-means.py new file mode 100644 index 0000000..356d276 --- /dev/null +++ b/k-means.py @@ -0,0 +1,25 @@ +import cv2 +import numpy as np +import matplotlib.pyplot as plt + +image = cv2.imread('./Lenna.png').astype(np.float32) / 255. +image_lab = cv2.cvtColor(image, cv2.COLOR_BGR2Lab) + +data = image_lab.reshape((-1, 3)) + +num_classes = 8 +criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 50, 0.1) +_, labels, centers = cv2.kmeans(data, num_classes, None, criteria, 10, cv2.KMEANS_RANDOM_CENTERS) + +segmented_lab = centers[labels.flatten()].reshape(image.shape) +segmented = cv2.cvtColor(segmented_lab, cv2.COLOR_Lab2RGB) + +plt.subplot(121) +plt.axis('off') +plt.title('original') +plt.imshow(image[:,:,[2,1,0]]) +plt.subplot(122) +plt.axis('off') +plt.title('segmented') +plt.imshow(segmented) +plt.show() \ No newline at end of file diff --git a/watershed.py b/watershed.py new file mode 100644 index 0000000..eeb2616 --- /dev/null +++ b/watershed.py @@ -0,0 +1,71 @@ +import cv2 +import numpy as np +from random import randint + +img = cv2.imread('./lenna.png') +show_img = np.copy(img) + +seeds = np.full(img.shape[0:2], 0, np.int32) +segmentation = np.full(img.shape, 0, np.uint8) + +n_seeds = 9 + +colors = [] +for m in range(n_seeds): + colors.append((255 * m / n_seeds, randint(0, 255), randint(0, 255))) + + +mouse_pressed = False +current_seed = 1 +seeds_updated = False + + +def mouse_callback(event, x, y, flags, param): + global mouse_pressed, seeds_updated + + if event == cv2.EVENT_LBUTTONDOWN: + mouse_pressed = True + cv2.circle(seeds, (x, y), 5, (current_seed), cv2.FILLED) + cv2.circle(show_img, (x, y), 5, colors[current_seed - 1], cv2.FILLED) + seeds_updated = True + + elif event == cv2.EVENT_MOUSEMOVE: + if mouse_pressed: + cv2.circle(seeds, (x, y), 5, (current_seed), cv2.FILLED) + cv2.circle(show_img, (x, y), 5, colors[current_seed - 1], cv2.FILLED) + seeds_updated = True + + elif event == cv2.EVENT_LBUTTONUP: + mouse_pressed = False + + +cv2.namedWindow('image') +cv2.setMouseCallback('image', mouse_callback) + +while True: + cv2.imshow('segmentation', segmentation) + cv2.imshow('image', show_img) + + k = cv2.waitKey(1) + + if k == 27: + break; + elif k == ord('c'): + show_img = np.copy(img) + seeds = np.full(img.shape[0:2], 0, np.int32) + segmentation = np.full(img.shape, 0, np.uint8) + elif k > 0 and chr(k).isdigit(): + n = int(chr(k)) + if 1 <= n <= n_seeds and not mouse_pressed: + current_seed = n + + if seeds_updated and not mouse_pressed: + seeds_copy = np.copy(seeds) + cv2.watershed(img, seeds_copy) + segmentation = np.full(img.shape, 0, np.uint8) + for m in range(n_seeds): + segmentation[seeds_copy == (m + 1)] = colors[m] + + seeds_updated = False + +cv2.destroyAllWindows() \ No newline at end of file