labelme的 json格式转化成自己的json格式

矫情吗；* 2023-10-04 17:16 38阅读 0赞

**labelme的json格式：**

{
      "version": "4.5.6",
      "flags": {},
      "shapes": [
        {
          "label": "1",
          "points": [
            [
              1609.6923076923076,
              884.6153846153846
            ],
            [
              1988.1538461538462,
              1172.3076923076924
            ]
          ],
          "group_id": null,
          "shape_type": "rectangle",
          "flags": {}
        },
        {
          "label": "0",
          "points": [
            [
              1352.7692307692307,
              3.0769230769230766
            ],
            [
              1925.076923076923,
              578.4615384615385
            ]
          ],
          "group_id": null,
          "shape_type": "rectangle",
          "flags": {}
        }
      ],
      "imagePath": "..\\imgs\\0001.jpg",
      "imageData": null,
      "imageHeight": 1492,
      "imageWidth": 2040
    }

**自己的json格式：**

{
        "name": "0001.jpg",
        "frames": [
            {
                "timestamp": "10000",
                "objects": [
                    {
                        "category": "1",
                        "id": 0,
                        "attributes": {
                            "occluded": false,
                            "truncated": false,
                            "trafficLightCorlor": "none"
                        },
                        "box2d": {
                            "x1": 1609.6923076923076,
                            "y1": 884.6153846153846,
                            "x2": 1988.1538461538462,
                            "y2": 1172.3076923076924
                        }
                    },
                    {
                        "category": "0",
                        "id": 1,
                        "attributes": {
                            "occluded": false,
                            "truncated": false,
                            "trafficLightCorlor": "none"
                        },
                        "box2d": {
                            "x1": 1352.7692307692307,
                            "y1": 3.0769230769230766,
                            "x2": 1925.076923076923,
                            "y2": 578.4615384615385
                        }
                    }
                ]
            }
        ],
        "imagePath": "..\\imgs\\0001.jpg",
        "imageData": null,
        "imageHeight": 1492,
        "imageWidth": 2040
    }

## 转换代码： ##

import argparse
    import json
    import cv2
    import numpy as np
    import os
    
    '''
    parser = argparse.ArgumentParser()
    parser.add_argument("square", help="display a square of a given number", type=int)
    args = parser.parse_args()
    print(args.square** 2)
    '''
    def json_for_train(from_json, to_json):
            final_json = dict()
            final_json['name'] = None
            final_json['frames'] = None
    
           #解析from_json
            load_f = open(from_json)
            anno = json.load(load_f)
            version = anno["version"]
            flags = anno["flags"]
            imagePath = anno["imagePath"]
            imageData = anno["imageData"]
            imageHeight = anno["imageHeight"]
            imageWidth = anno["imageWidth"]
            shapes = []
            object1=[]
            fname=imagePath.split("\\")[-1]  #获得图片的名字
            #print(fname)
    
            classes_locations = anno["shapes"]
            i=-1
            for cls in classes_locations:
                 i=i+1
                 print(cls)
                 attr = {
                     "occluded":False,
                     "truncated": False,
                     "trafficLightCorlor": "none"
                 }
                 print(cls.get("points"))
                 box = {
                     "x1": cls.get("points")[0][0],
                     "y1": cls.get("points")[0][1],
                     "x2": cls.get("points")[1][0],
                     "y2": cls.get("points")[1][1]
                 }
                 #print(box)
                 print("label:"+cls.get("label"))
                 mid = {
                     "category": cls.get("label"),
                     "id": i,
                     "attributes": attr,
                     "box2d": box
                 }
                 object1.append(mid)
                 print("******")
                 print(object1)
                 print("====")
    
    
    
            shape = {
                "timestamp": "10000",
                "objects": object1,
            }
            shapes.append(shape)
            print("----")
            #print(shapes)
            result_json = {
                "name": fname,
                "frames": shapes,
                "imagePath": imagePath,
                "imageData": imageData,
                "imageHeight": imageHeight,
                "imageWidth": imageWidth
            }
            print(result_json)
            labelme_json = json.dumps(result_json, indent=4, ensure_ascii=False)
            with open(to_json, "w+") as fp:
                fp.write(labelme_json)
    
    if __name__ == '__main__':
        from_jsons = './annotation/'
        to_jsons = './annotation_new/'
        dir_jsons = os.listdir(from_jsons)
        print(dir_jsons)
        i = 1
        for dir_json in dir_jsons:
            print("第" + str(i) + "/" + str(len(dir_jsons)) + "张     ===>" + dir_json)
            i += 1
            from_name = os.path.join(from_jsons, dir_json)
            to_name = os.path.join(to_jsons, dir_json)
            try:
                json_for_train(from_name, to_name)
            except Exception as e:
                print(e)