import json
import os
from os import listdir, getcwd
from os.path import join
import os.pathrootdir = 'F:/dataset/'# 写自己存放图片的数据地址
input_dir = 'F:/dataset/labels_json/'
output_dir = 'F:/dataset/labels_box/'
def position(pos):# 该函数用来找出xmin,ymin,xmax,ymax即bbox包围框x = []y = []nums = len(pos)for i in range(nums):x.append(pos[i][0])y.append(pos[i][1])x_max = max(x)x_min = min(x)y_max = max(y)y_min = min(y)b = (float(x_min), float(x_max), float(y_min), float(y_max))return bdef convert_annotation(image_ids, input_dir, output_dir):for image_id in image_ids:print(image_id)input_file_path = os.path.join(input_dir, f"{image_id}.json")output_file_path = os.path.join(output_dir, f"{image_id}.json")try:with open(input_file_path, 'r') as load_f:load_dict = json.load(load_f)w = load_dict['imageWidth']h = load_dict['imageHeight']objects = load_dict['shapes']annotations = []  # 创建一个空列表来存储注解for obj in objects:# 去除可能的额外空格，并设置默认标签（如果需要）labels = obj['label'].strip()# 根据标签处理形状if labels in ["class1", "class2","class3", "class4"]:pos = obj['points']b = position(pos)cls_id_mapping = {"class1": 1,"class2": 2,"class3": 3,"class4": 4,}cls_id = cls_id_mapping[labels]annotation = {'label': labels,'class_id': cls_id,'bbox': b}annotations.append(annotation)output_dict = {"version": "5.0.2","flags": {},"shapes": [],  # shapes数组为空，因为注解信息已经放在annotations中"imagePath": load_dict['imagePath'],"imageData": None,"imageHeight": h,"imageWidth": w,"annotations": annotations  # 添加注解列表}for shape in load_dict['shapes']:# 假设每个多边形都有四个点，我们可以直接取对角线上的两个点来定义矩形# 这里我们取第一个点和第三个点（或者您可以根据具体情况选择其他点对）objects = load_dict['shapes']for obj in objects:# 去除可能的额外空格，并设置默认标签（如果需要）labels = obj['label'].strip()if labels in ["class1", "class2","class3", "class4"]:pos = obj['points']b = position(pos)rect_points = [[b[0], b[3]],[b[1], b[2]]]new_shape = {"label": labels,  # 保留原多边形的标签（或者您可以根据需要生成新的标签）"points": rect_points,  # 使用调整后的点来表示矩形（但这里我们实际上只使用了两个点）# 注意：由于我们简化了问题，并没有真正地使用四个点来定义一个完整的矩形# 在实际应用中，您可能需要更精确地处理这个问题。"group_id": None,  # 您可以根据需要设置这个字段的值"shape_type": "rectangle",  # 指定形状类型为矩形"flags": {}  # 保留空的flags字段（或者您可以根据需要填充它）}output_dict['shapes'].append(new_shape)# 写入新的JSON文件with open(output_file_path, 'w') as output_f:json.dump(output_dict, output_f, indent=4)except Exception as e:print(f"Error processing {input_file_path}: {e}")def image_id(rootdir):a = []for parent, dirnames, filenames in os.walk(rootdir):for filename in filenames:# print(filename)if filename.endswith('.jpg'):filename = os.path.splitext(filename)[0]if filename.endswith('.jpeg'):filename = os.path.splitext(filename)[0]if filename.endswith('.JPG'):filename = os.path.splitext(filename)[0]if filename.endswith('.JPEG'):filename = os.path.splitext(filename)[0]a.append(filename)return anames = image_id("F:/dataset/images/"),for image_id in names:convert_annotation(image_id, input_dir, output_dir)