代码如下
import argparse
import json
import matplotlib.pyplot as plt
import skimage.io as io
import cv2
from labelme import utils
import numpy as np
import glob
import PIL.Image

class MyEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj, np.integer):
return int(obj)
elif isinstance(obj, np.floating):
return float(obj)
elif isinstance(obj, np.ndarray):
return obj.tolist()
else:
return super(MyEncoder, self).default(obj)

class labelme2coco(object):
def init(self, labelme_json=[], save_json_path='./val.json'):
'''
:param labelme_json: 所有labelme的json文件路径组成的列表
:param save_json_path: json保存位置
'''
self.labelme_json = labelme_json
self.save_json_path = save_json_path
self.images = []
self.categories = []
self.annotations = []
# self.data_coco = {}
self.label = []
self.annID = 1
self.height = 0
self.width = 0

    self.save_json()

def data_transfer(self):

    for num, json_file in enumerate(self.labelme_json):
        with open(json_file, 'r') as fp:
            data = json.load(fp)  # 加载json文件
            self.images.append(self.image(data, num))
            for shapes in data['shapes']:
                label = shapes['label']
                if label not in self.label:
                    self.categories.append(self.categorie(label))
                    self.label.append(label)
                points = shapes['points']  # 这里的point是用rectangle标注得到的，只有两个点，需要转成四个点
                # points.append([points[0][0],points[1][1]])
                # points.append([points[1][0],points[0][1]])

                self.annotations.append(self.annotation(points, label, num))
                self.annID += 1

def image(self, data, num):
    image = {}
    img = utils.img_b64_to_arr(data['imageData'])  # 解析原图片数据
    # img=io.imread(data['imagePath']) # 通过图片路径打开图片
    # img = cv2.imread(data['imagePath'], 0)
    height, width = img.shape[:2]
    img = None
    image['height'] = height
    image['width'] = width
    image['id'] = num + 1
    image['file_name'] = data['imagePath'].split('/')[-1]

    self.height = height
    self.width = width

    return image

def categorie(self, label):
    categorie = {}
    categorie['supercategory'] = 'person'
    categorie['id'] = len(self.label) + 1  # 0 默认为背景
    categorie['name'] = label

    categorie['keypoints'] = ["head", "left_eye0", "left_eye1", "right_eye0", "right_eye1", "nose", "left_mouse",
                              "right_mouse",
                              "left_shoulder0", "left_shoulder1", "left_shoulder2",
                              "left_elbow0", "left_elbow1", "left_elbow2", "left_elbow3",
                              "left_wrist0", "left_wrist1",
                              "left_hand",
                              "left_wrist2", "left_wrist3",
                              "left_elbow4", "left_elbow5", "left_elbow6",
                              "left_chest0", "left_chest1", "left_chest2", "left_chest3", "left_chest4",
                              "left_hip0", "left_hip1", "left_hip2",
                              "left_knee0", "left_knee1",
                              "left_ankle0", "left_ankle1",
                              "left_knee2", "left_knee3",
                              "left_hip3", "left_hip4", "left_hip5",
                              "right_hip0", "right_hip1",
                              "right_knee0", "right_knee1",
                              "right_ankle0", "right_ankle1",
                              "right_knee2", "right_knee3",
                              "right_hip2", "right_hip3", "right_hip4",
                              "right_chest0", "right_chest1", "right_chest2", "right_chest3", "right_chest4",
                              "right_elbow4", "right_elbow5", "right_elbow6",
                              "right_wrist2", "right_wrist3",
                              "right_hand",
                              "right_wrist0", "right_wrist1",
                              "right_elbow0", "right_elbow1", "right_elbow2", "right_elbow3",
                              "right_shoulder0", "right_shoulder1", "right_shoulder2"]

    categorie['skeleton'] = [[1, 2], [2, 3], [3, 4],
                             [4, 5], [5, 6], [6, 7], [7, 8],
                             [8, 9], [9, 10], [10, 11], [11, 12],
                             [12, 13], [13, 14], [14, 15], [15, 16],
                             [16, 17], [17, 18], [18, 19], [19, 20],
                             [20, 21], [21, 22], [22, 23], [23, 24],
                             [24, 25], [25, 26], [26, 27], [27, 28],
                             [28, 29], [29, 30], [30, 31], [31, 32],
                             [32, 33], [33, 34], [34, 35], [35, 36],
                             [36, 37], [37, 38], [38, 39], [39, 40],
                             [40, 41], [41, 42], [42, 43], [43, 44],
                             [44, 45], [45, 46], [46, 47], [47, 48],
                             [48, 49], [49, 50], [50, 51], [51, 52],
                             [52, 53], [53, 54], [54, 55], [55, 56],
                             [56, 57], [57, 58], [58, 59], [59, 60],
                             [60, 61], [61, 62], [62, 63], [63, 64],
                             [64, 65], [65, 66], [66, 67], [67, 68],
                             [68, 69], [69, 70], [70, 71]]
    return categorie

def annotation(self, points, label, num):
    annotation = {}
    annotation['segmentation'] = [list(np.asarray(points).flatten())]
    annotation['iscrowd'] = 0
    annotation['image_id'] = num + 1
    # annotation['bbox'] = str(self.getbbox(points)) # 使用list保存json文件时报错（不知道为什么）
    # list(map(int,a[1:-1].split(','))) a=annotation['bbox'] 使用该方式转成list
    annotation['bbox'] = list(map(float, self.getbbox(points)))
    annotation['area'] = annotation['bbox'][2] * annotation['bbox'][3]
    # annotation['category_id'] = self.getcatid(label)
    annotation['category_id'] = self.getcatid(label)  # 注意，源代码默认为1
    annotation['id'] = self.annID

    annotation['keypoints'] = []
    for p in points:
        annotation['keypoints'].extend([p[0], p[1], 2])
    annotation['num_keypoints'] = len(points)
    return annotation

def getcatid(self, label):
    for categorie in self.categories:
        if label == categorie['name']:
            return categorie['id']
    return 1

def getbbox(self, points):
    # img = np.zeros([self.height,self.width],np.uint8)
    # cv2.polylines(img, [np.asarray(points)], True, 1, lineType=cv2.LINE_AA)  # 画边界线
    # cv2.fillPoly(img, [np.asarray(points)], 1)  # 画多边形 内部像素值为1
    polygons = points

    mask = self.polygons_to_mask([self.height, self.width], polygons)
    return self.mask2box(mask)

def mask2box(self, mask):
    '''从mask反算出其边框
    mask：[h,w]  0、1组成的图片
    1对应对象，只需计算1对应的行列号（左上角行列号，右下角行列号，就可以算出其边框）
    '''
    # np.where(mask==1)
    index = np.argwhere(mask == 1)
    rows = index[:, 0]
    clos = index[:, 1]
    # 解析左上角行列号
    left_top_r = np.min(rows)  # y
    left_top_c = np.min(clos)  # x

    # 解析右下角行列号
    right_bottom_r = np.max(rows)
    right_bottom_c = np.max(clos)

    # return [(left_top_r,left_top_c),(right_bottom_r,right_bottom_c)]
    # return [(left_top_c, left_top_r), (right_bottom_c, right_bottom_r)]
    # return [left_top_c, left_top_r, right_bottom_c, right_bottom_r]  # [x1,y1,x2,y2]
    return [left_top_c, left_top_r, right_bottom_c - left_top_c,
            right_bottom_r - left_top_r]  # [x1,y1,w,h] 对应COCO的bbox格式

def polygons_to_mask(self, img_shape, polygons):
    mask = np.zeros(img_shape, dtype=np.uint8)
    mask = PIL.Image.fromarray(mask)
    xy = list(map(tuple, polygons))
    PIL.ImageDraw.Draw(mask).polygon(xy=xy, outline=1, fill=1)
    mask = np.array(mask, dtype=bool)
    return mask

def data2coco(self):
    data_coco = {}
    data_coco['images'] = self.images
    data_coco['categories'] = self.categories
    data_coco['annotations'] = self.annotations
    return data_coco

def save_json(self):
    self.data_transfer()
    self.data_coco = self.data2coco()
    # 保存json文件
    json.dump(self.data_coco, open(self.save_json_path, 'w'), indent=4, cls=MyEncoder)  # indent=4 更加美观显示

labelme_json = glob.glob('./val/*.json')

labelme_json=['./Annotations/*.json']

labelme2coco(labelme_json, './val.json')

我只修改了最后三句话。