| import cv2 | |
| from PIL import Image | |
| import numpy as np | |
| def get_concat_h(im1, im2): | |
| dst = Image.new('RGB', (im1.width + im2.width, im1.height)) | |
| dst.paste(im1, (0, 0)) | |
| dst.paste(im2, (im1.width, 0)) | |
| return dst | |
| def get_concat_v(im1, im2): | |
| dst = Image.new('RGB', (im1.width, im1.height + im2.height)) | |
| dst.paste(im1, (0, 0)) | |
| dst.paste(im2, (0, im1.height)) | |
| return dst | |
| def hsv_to_rgb(h, s, v): | |
| bgr = cv2.cvtColor(np.array([[[h, s, v]]], dtype=np.uint8), cv2.COLOR_HSV2BGR)[0][0] | |
| return [bgr[2]/255, bgr[1]/255, bgr[0]/255] | |
| # def remove_bg( | |
| # path, | |
| # BLUR = 21, | |
| # CANNY_THRESH_1 = 10, | |
| # CANNY_THRESH_2 = 200, | |
| # MASK_DILATE_ITER = 10, | |
| # MASK_ERODE_ITER = 10, | |
| # MASK_COLOR = (0.0,0.0,1.0), | |
| # ): | |
| # img = cv2.imread(path) | |
| # gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) | |
| # edges = cv2.Canny(gray, CANNY_THRESH_1, CANNY_THRESH_2) | |
| # edges = cv2.dilate(edges, None) | |
| # edges = cv2.erode(edges, None) | |
| # contour_info = [] | |
| # contours, _ = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE) | |
| # for c in contours: | |
| # contour_info.append(( | |
| # c, | |
| # cv2.isContourConvex(c), | |
| # cv2.contourArea(c), | |
| # )) | |
| # contour_info = sorted(contour_info, key=lambda c: c[2], reverse=True) | |
| # max_contour = contour_info[0] | |
| # mask = np.zeros(edges.shape) | |
| # cv2.fillConvexPoly(mask, max_contour[0], (255)) | |
| # mask = cv2.dilate(mask, None, iterations=MASK_DILATE_ITER) | |
| # mask = cv2.erode(mask, None, iterations=MASK_ERODE_ITER) | |
| # mask = cv2.GaussianBlur(mask, (BLUR, BLUR), 0) | |
| # mask_stack = np.dstack([mask]*3) # Create 3-channel alpha mask | |
| # mask_stack = mask_stack.astype('float32') / 255.0 # Use float matrices, | |
| # img = img.astype('float32') / 255.0 # for easy blending | |
| # masked = (mask_stack * img) + ((1-mask_stack) * MASK_COLOR) # Blend | |
| # masked = (masked * 255).astype('uint8') # Convert back to 8-bit | |
| # c_blue, c_green, c_red = cv2.split(img) | |
| # img_a = cv2.merge((c_red, c_green, c_blue, mask.astype('float32') / 255.0)) | |
| # index = np.where(img_a[:, :, 3] == 0) | |
| # #img_a[index] = [1.0, 1.0, 1.0, 1.0] | |
| # return img_a |