目的:为了解决密集文本的分割问题

代码:

# -*- coding=utf-8 -*-
import os
import cv2
import Polygon as plg
import pyclipper
import numpy as npdef dist(a, b):return np.sqrt(np.sum((a - b) ** 2))#计算周长
def perimeter(bbox):peri = 0.0for i in range(bbox.shape[0]):# print('==bbox[i], bbox[i + 1]:', bbox[i], bbox[(i + 1) % bbox.shape[0]])peri += dist(bbox[i], bbox[(i + 1) % bbox.shape[0]])return peridef shrink(bboxes, rate, max_shr=20):rate = rate * rateshrinked_bboxes = []for bbox in bboxes:area = plg.Polygon(bbox).area()print('===bbox:', bbox)peri = perimeter(bbox)pco = pyclipper.PyclipperOffset()pco.AddPath(bbox, pyclipper.JT_ROUND, pyclipper.ET_CLOSEDPOLYGON)offset = min((int)(area * (1 - rate) / (peri + 0.001) + 0.5), max_shr)shrinked_bbox = pco.Execute(-offset)if len(shrinked_bbox) == 0:shrinked_bboxes.append(bbox)continueshrinked_bbox = np.array(shrinked_bbox)[0]if shrinked_bbox.shape[0] <= 2:shrinked_bboxes.append(bbox)continueshrinked_bboxes.append(shrinked_bbox)return shrinked_bboxes  # np.array(shrinked_bboxes)def main(shrink_threshold=0.9):img_path = './src_imgs/img_43.jpg'label_path = './labels_txt/img_43.txt'img = cv2.imread(img_path)H, W, _ = img.shapewith open(label_path, 'r') as f:label_lines = f.readlines()f.close()gt_boxes = []for line in label_lines:line = line.strip().strip('\ufeff').strip('\xef\xbb\xbf')# print('===line:', line)box_points = [int(float(item)) for item in line.split(',')[:-1]]box_info = np.array(box_points).reshape((-1, 2))# print('===box_info:', box_info)gt_boxes.append(box_info)ori_mask_img = np.zeros((H, W))for box in gt_boxes:cv2.fillPoly(ori_mask_img, [box], (255))cv2.imwrite('./ori_mask_img.jpg', ori_mask_img)shrink_mask_img = np.zeros((H, W))new_gt_boxes = shrink(gt_boxes, shrink_threshold)for box in new_gt_boxes:cv2.fillPoly(shrink_mask_img, [box], (100))cv2.imwrite('./shrink_mask_img.jpg', shrink_mask_img)if __name__ == "__main__":main(shrink_threshold=0.6)

                               1.原图

    

                               2.原先分割图                                                                         3.收缩后分割图