def test_bg_probability(self): im3 = cv2.imread('tests/reddot_seed.jpg', cv.CV_LOAD_IMAGE_COLOR) f1 = SeparateObjectFilter() meta_img = MetaImg(im3, {}) hsv = cv2.cvtColor(meta_img.img, cv.CV_BGR2HSV) mask = f1._create_bg_probe_mask(im3) probab = f1._bg_probability(mask, hsv[:,:,2]) _, ret = cv2.threshold((probab*10000).astype(np.uint8), 70 , 255, cv2.THRESH_BINARY_INV) cv2.imshow('asd1', ret) probab += f1._bg_probability(mask, hsv[:,:,0]) probab *= 10000 probab = probab.astype(np.uint8) print np.max(probab) _, ret = cv2.threshold(probab, 140 , 255, cv2.THRESH_BINARY_INV)
def test_bg_probability(self): im3 = cv2.imread('tests/reddot_seed.jpg', cv.CV_LOAD_IMAGE_COLOR) f1 = SeparateObjectFilter() meta_img = MetaImg(im3, {}) hsv = cv2.cvtColor(meta_img.img, cv.CV_BGR2HSV) mask = f1._create_bg_probe_mask(im3) probab = f1._bg_probability(mask, hsv[:, :, 2]) _, ret = cv2.threshold((probab * 10000).astype(np.uint8), 70, 255, cv2.THRESH_BINARY_INV) cv2.imshow('asd1', ret) probab += f1._bg_probability(mask, hsv[:, :, 0]) probab *= 10000 probab = probab.astype(np.uint8) print np.max(probab) _, ret = cv2.threshold(probab, 140, 255, cv2.THRESH_BINARY_INV)
def test_probe_mask(self): f = SeparateObjectFilter() im3 = cv2.imread('tests/reddot.jpg', cv.CV_LOAD_IMAGE_COLOR) mask = f._create_bg_probe_mask(im3) self.assertGreater(np.sum(mask) / 255, 400)
def test_probe_mask(self): f = SeparateObjectFilter() im3 = cv2.imread('tests/reddot.jpg', cv.CV_LOAD_IMAGE_COLOR) mask = f._create_bg_probe_mask(im3) self.assertGreater(np.sum(mask)/255, 400)