labelme标注后的数据只剩下面积1600像素以内的小颗粒

点击查看代码

import cv2
import numpy as np
import json
import os
def list_jsons(folder_path):
    for filename in os.listdir(folder_path):
        if filename.endswith(('.json',)):
            yield os.path.join(folder_path, filename)

def remove_specific_labels(json_file):
    # 读取JSON文件
    with open(json_file, 'r') as f:
        data = json.load(f)
        data_small=data
    if"shapes" in data:
        new_shapes=[]
        new_shapes_small=[]
        # 提取闭合区域的轮廓
        contours = []
        for shape in data['shapes']:
            points = np.array(shape['points'], np.int32)
            area=cv2.contourArea(points)
            if(area<1600):
                new_shapes.append(shape)
            # else:
            #     shape["label"]="small_ban"
            #     new_shapes.append(shape)
            #     print("")
            # print("闭合区域的面积为", cv2.contourArea(points))
            # contours.append(points)
        data["shapes"]=new_shapes
        # data_small["shapes"]=new_shapes_small
    with open(json_file,'w',encoding='utf-8')as f:
        json.dump(data,f,ensure_ascii=False,indent=4)


    # with open(r"D:\gzj\pic\SEE\0827\backup\small.json",'w',encoding='utf-8')as f:
    #     json.dump(data_small,f,ensure_ascii=False,indent=4)
if __name__ == '__main__':
# 使用例子
    folder_path = '/home/administrator/gzj/pic/primary_tiao/src_copy/'  # 替换为你的文件夹路径
    for json_path in list_jsons(folder_path):
         remove_specific_labels(json_path)
    #remove_specific_labels('/home/administrator/gzj/pic/primary_ban/src_copy')
    #E:\SVN\08代码交接\granule_server_cngr_2\granule_server_cngr_2