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| """ | |
| 有一些png图像下部也会有一些透明的区域，使得图像无法对其底部边框 | |
| 本程序实现移动图像，使其下部与png图像实际大小相对齐 | |
| """ | |
| import os | |
| import cv2 | |
| import numpy as np | |
| from ..utils import get_box_pro | |
| path_pre = os.path.join(os.getcwd(), 'pre') | |
| path_final = os.path.join(os.getcwd(), 'final') | |
| def merge(boxes): | |
| """ | |
| 生成的边框可能不止只有一个，需要将边框合并 | |
| """ | |
| x, y, h, w = boxes[0] | |
| # x和y应该是整个boxes里面最小的值 | |
| if len(boxes) > 1: | |
| for tmp in boxes: | |
| x_tmp, y_tmp, h_tmp, w_tmp = tmp | |
| if x > x_tmp: | |
| x_max = x_tmp + w_tmp if x_tmp + w_tmp > x + w else x + w | |
| x = x_tmp | |
| w = x_max - x | |
| if y > y_tmp: | |
| y_max = y_tmp + h_tmp if y_tmp + h_tmp > y + h else y + h | |
| y = y_tmp | |
| h = y_max - y | |
| return tuple((x, y, h, w)) | |
| def get_box(png_img): | |
| """ | |
| 获取矩形边框最终返回一个元组(x,y,h,w)，分别对应矩形左上角的坐标和矩形的高和宽 | |
| """ | |
| r, g, b , a = cv2.split(png_img) | |
| gray_img = a | |
| th, binary = cv2.threshold(gray_img, 127 , 255, cv2.THRESH_BINARY) # 二值化 | |
| # cv2.imshow("name", binary) | |
| # cv2.waitKey(0) | |
| contours, hierarchy = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # 得到轮廓列表contours | |
| bounding_boxes = merge([cv2.boundingRect(cnt) for cnt in contours]) # 轮廓合并 | |
| # print(bounding_boxes) | |
| return bounding_boxes | |
| def get_box_2(png_img): | |
| """ | |
| 不用opencv内置算法生成矩形了，改用自己的算法（for循环） | |
| """ | |
| _, _, _, a = cv2.split(png_img) | |
| _, a = cv2.threshold(a, 127, 255, cv2.THRESH_BINARY) | |
| # 将r，g，b通道丢弃，只留下透明度通道 | |
| # cv2.imshow("name", a) | |
| # cv2.waitKey(0) | |
| # 在透明度矩阵中，0代表完全透明 | |
| height,width=a.shape # 高和宽 | |
| f=0 | |
| tmp1 = 0 | |
| """ | |
| 获取上下 | |
| """ | |
| for tmp1 in range(0,height): | |
| tmp_a_high= a[tmp1:tmp1+1,:][0] | |
| for tmp2 in range(width): | |
| # a = tmp_a_low[tmp2] | |
| if tmp_a_high[tmp2]!=0: | |
| f=1 | |
| if f == 1: | |
| break | |
| delta_y_high = tmp1 + 1 | |
| f = 0 | |
| for tmp1 in range(height,-1, -1): | |
| tmp_a_low= a[tmp1-1:tmp1+1,:][0] | |
| for tmp2 in range(width): | |
| # a = tmp_a_low[tmp2] | |
| if tmp_a_low[tmp2]!=0: | |
| f=1 | |
| if f == 1: | |
| break | |
| delta_y_bottom = height - tmp1 + 3 | |
| """ | |
| 获取左右 | |
| """ | |
| f = 0 | |
| for tmp1 in range(width): | |
| tmp_a_left = a[:, tmp1:tmp1+1] | |
| for tmp2 in range(height): | |
| if tmp_a_left[tmp2] != 0: | |
| f = 1 | |
| if f==1: | |
| break | |
| delta_x_left = tmp1 + 1 | |
| f = 0 | |
| for tmp1 in range(width, -1, -1): | |
| tmp_a_left = a[:, tmp1-1:tmp1] | |
| for tmp2 in range(height): | |
| if tmp_a_left[tmp2] != 0: | |
| f = 1 | |
| if f==1: | |
| break | |
| delta_x_right = width - tmp1 + 1 | |
| return delta_y_high, delta_y_bottom, delta_x_left, delta_x_right | |
| def move(input_image): | |
| """ | |
| 裁剪主函数，输入一张png图像，该图像周围是透明的 | |
| """ | |
| png_img = input_image # 获取图像 | |
| height, width, channels = png_img.shape # 高y、宽x | |
| y_low,y_high, _, _ = get_box_pro(png_img, model=2) # for循环 | |
| base = np.zeros((y_high, width, channels),dtype=np.uint8) # for循环 | |
| png_img = png_img[0:height - y_high, :, :] # for循环 | |
| png_img = np.concatenate((base, png_img), axis=0) | |
| return png_img | |
| if __name__ == "__main__": | |
| pass | |