python编写labelme的json文件并且能够在labelme下打开使用_labelme的json标注文件显示标注内容python

作者：Cpp五条 | 2024-03-17 17:29:00

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labelme的json标注文件显示标注内容python

今天教大家使用Python来生成一个json文件，这个json文件可以使用labelme打开，如果有自动框猫的模型，可借鉴我的上篇文章链接如下：

python使用opencv对猫脸进行检测，并且框出猫脸_小琼带你轻松学编程的博客-CSDN博客

，实现自动给猫咪打标注。

导入所需要的库：


import json
import base64
from PIL import Image

json库用来使字典转为json文件。

base64库是能够生成labelme打完标签生成的json文件中的imagDate中的数据即下图所示：

from PIL import Image是为了读取图片和获取图片的宽高。

框和点的数据集：


bbox = [[206.90909090909088, 210.5454545454545], [490.18181818181813, 520.3766233766233],
        [428.7272727272727, 85.09090909090907], [721.3506493506493, 395.7012987012987]]
point = [[397.8181818181818, 390.5454545454545], [374.18181818181813, 305.090909090909],
         [423.27272727272725, 326.9090909090909], [359.6363636363636, 481.4545454545454],
         [277.8181818181818, 510.5454545454545], [308.7272727272727, 408.72727272727263],
         [281.45454545454544, 325.090909090909], [208.72727272727272, 255.99999999999994],
         [297.8181818181818, 245.09090909090907],
         [541.4545454545454, 290.5454545454545], [639.6363636363636, 254.18181818181813],
         [605.090909090909, 312.3636363636364], [466.9090909090909, 259.63636363636357],
         [437.81818181818176, 161.45454545454544], [517.8181818181818, 203.27272727272725],
         [594.1818181818181, 179.63636363636363], [641.4545454545454, 90.5454545454545],
         [666.9090909090909, 179.63636363636363], ]

原图如下：

数据集最终在labelme的呈现效果，即一个猫脸一个框，九个点（可根据需要自行修改）：

读取图片，初始化字典cur_json_dict，将无关紧要的固定住：


img_path = './1.jpg'
img = Image.open(img_path)
cur_json_dict = {
    "version": "4.5.6",
    "flags": {},
    "shapes": [
    ],
}

将bbox（框）和points（点）按照labelme所需的要求写入字典中，bbox和points的样式可根据自己的需要修改：


# bbox
for i in range(int(len(bbox) / 2)):
    if len(bbox) / 2 >= 1:
        cur_json_dict['shapes'].append(
            {"label": "bbox", "points": bbox[i * 2:i * 2+ 2], 'group_id': f'{i}', "shape_type": "rectangle", "flags": {}})
    else:
        cur_json_dict['shapes'].append(
            {"label": "bbox", "points": bbox[i * 2:i * 2+ 2], 'group_id': 'NULL', "shape_type": "rectangle", "flags": {}})
# point
for i in range(int(len(point) / 9)):
    for j in range(9):
        if len(bbox) / 2 >= 1:
            cur_json_dict['shapes'].append(
                {"label": f"{j}", "points": point[i * 9 + j:i * 9 + j + 1], 'group_id': f'{i}',
                 "shape_type": "point", "flags": {}})
        else:
            cur_json_dict['shapes'].append(
                {"label": f"{j}", "points": point[i * 9 + j:i * 9 + j + 1], 'group_id': 'NULL',
                 "shape_type": "point", "flags": {}})

按照labelme生成的json文件的顺序imagePath，imageData，imageHeight，imageWidth写入字典中：


cur_json_dict["imagePath"] = img_path
cur_json_dict["imageData"] = str(base64.b64encode(open(img_path, "rb").read()))
# delete 'b and '
cur_json_dict["imageData"] = cur_json_dict["imageData"][2:-1]
cur_json_dict["imageHeight"] = img.size[0]
cur_json_dict["imageWidth"] = img.size[1]
new_dict = cur_json_dict

最后生成和图片除后缀不一样的json文件，并且使用json.dumps（）将字典cur_json_dict转为json：


with open(img_path.split(img_path.split('.')[-1])[0]+'json', 'a+') as f:
    f.write(json.dumps(cur_json_dict))

运行前：

运行结果如下：

使用labelme打开查看是否成功，查看结果如下：

全部代码如下所示：


import json
import base64
from PIL import Image
# date
bbox = [[206.90909090909088, 210.5454545454545], [490.18181818181813, 520.3766233766233],
        [428.7272727272727, 85.09090909090907], [721.3506493506493, 395.7012987012987]]
point = [[397.8181818181818, 390.5454545454545], [374.18181818181813, 305.090909090909],
         [423.27272727272725, 326.9090909090909], [359.6363636363636, 481.4545454545454],
         [277.8181818181818, 510.5454545454545], [308.7272727272727, 408.72727272727263],
         [281.45454545454544, 325.090909090909], [208.72727272727272, 255.99999999999994],
         [297.8181818181818, 245.09090909090907],
         [541.4545454545454, 290.5454545454545], [639.6363636363636, 254.18181818181813],
         [605.090909090909, 312.3636363636364], [466.9090909090909, 259.63636363636357],
         [437.81818181818176, 161.45454545454544], [517.8181818181818, 203.27272727272725],
         [594.1818181818181, 179.63636363636363], [641.4545454545454, 90.5454545454545],
         [666.9090909090909, 179.63636363636363], ]
img_path = './1.jpg'
img = Image.open(img_path)
cur_json_dict = {
    "version": "4.5.6",
    "flags": {},
    "shapes": [
    ],
}
# bbox
for i in range(int(len(bbox) / 2)):
    if len(bbox) / 2 >= 1:
        cur_json_dict['shapes'].append(
            {"label": "bbox", "points": bbox[i * 2:i * 2+ 2], 'group_id': f'{i}', "shape_type": "rectangle", "flags": {}})
    else:
        cur_json_dict['shapes'].append(
            {"label": "bbox", "points": bbox[i * 2:i * 2+ 2], 'group_id': 'NULL', "shape_type": "rectangle", "flags": {}})
# point
for i in range(int(len(point) / 9)):
    for j in range(9):
        if len(bbox) / 2 >= 1:
            cur_json_dict['shapes'].append(
                {"label": f"{j}", "points": point[i * 9 + j:i * 9 + j + 1], 'group_id': f'{i}',
                 "shape_type": "point", "flags": {}})
        else:
            cur_json_dict['shapes'].append(
                {"label": f"{j}", "points": point[i * 9 + j:i * 9 + j + 1], 'group_id': 'NULL',
                 "shape_type": "point", "flags": {}})
cur_json_dict["imagePath"] = img_path
cur_json_dict["imageData"] = str(base64.b64encode(open(img_path, "rb").read()))
# delete 'b and '
cur_json_dict["imageData"] = cur_json_dict["imageData"][2:-1]
cur_json_dict["imageHeight"] = img.size[0]
cur_json_dict["imageWidth"] = img.size[1]
new_dict = cur_json_dict
with open(img_path.split(img_path.split('.')[-1])[0]+'json', 'a+') as f:
    f.write(json.dumps(cur_json_dict))

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python编写labelme的json文件并且能够在labelme下打开使用_labelme的json标注文件 显示标注内容python

python编写labelme的json文件并且能够在labelme下打开使用_labelme的json标注文件显示标注内容python