安装labelme

目录

这个是语义标注的工具

安装labelme

安装labellme可以直接pip安装

pip install labelme -i https://pypi.douban.com/simple

我在安装的报了如下的错误，setuptools没有属性，

AttributeError: module 'setuptools.build_meta' has no attribute '__legacy__'

于是升级了一下setuptools，然后再安装，成功了

pip install --upgrade setuptools

使用labelme

1. 在命令行输入

lableme

制作完会在图片的目录生成对应的json格式的文件。

2. 把json文件转为对应的标注的图片，修改了原来的labelme里面的json_to_dataset.py文件，运行下面这个会生成如下结构的文件，1、2等等是保存每张图像的原图、标签图、标签的名字，因为每个文件都是独立的，标签也是独立，因此生成的还不能直接使用。需要经过不揍3转换。
   

import base64
import json
import os
import os.path as osp
import imgviz
import PIL.Image
from labelme.logger import logger
from labelme import utils

def main(input_file,save_path):
    count = 1
    for json_path in os.listdir(input_file):
        if json_path.endswith('.json'): # 找以.json结尾的文件
            json_file = os.path.join(input_file,json_path)
            data = json.load(open(json_file))
            imageData = data.get('imageData')
            out_dir = os.path.join(save_path,str(count))
            if not os.path.exists(out_dir):
                os.makedirs(out_dir)

            if not imageData:
                imagePath = os.path.join(os.path.dirname(json_file), data['imagePath'])
                with open(imagePath, 'rb') as f:
                    imageData = f.read()
                    imageData = base64.b64encode(imageData).decode('utf-8')
            img = utils.img_b64_to_arr(imageData)

            label_name_to_value = {'_background_': 0}
            for shape in sorted(data['shapes'], key=lambda x: x['label']):
                label_name = shape['label']
                if label_name in label_name_to_value:
                    label_value = label_name_to_value[label_name]
                else:
                    label_value = len(label_name_to_value)
                    label_name_to_value[label_name] = label_value
            lbl, _ = utils.shapes_to_label(
                img.shape, data['shapes'], label_name_to_value
            )

            label_names = [None] * (max(label_name_to_value.values()) + 1)
            for name, value in label_name_to_value.items():
                label_names[value] = name
            lbl_viz = imgviz.label2rgb(
                label=lbl, img=imgviz.asgray(img), label_names=label_names, loc='rb'
            )
            orgin_image_path = json_path.split('.')[0] +'.jpg'
            PIL.Image.fromarray(img).save(osp.join(out_dir,orgin_image_path ))
            utils.lblsave(osp.join(out_dir, json_path.split('.')[0]+'_label.png'), lbl)
            PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir, 'label_viz.png'))
            with open(osp.join(out_dir, 'label_names.txt'), 'w') as f:
                for lbl_name in label_names:
                    f.write(lbl_name + '\n')

            count +=1
            print('结束')

if __name__ == '__main__':
    input_file = './1'  # 图片的路径,和json，就是制作标签的路径
    save_path = './outputs' # 输出的文件夹
    main(input_file,save_path)

3. 上面生成的每个图像都是从0开始，不能直接使用需要使用下面的这个转换，生成可以使用的

from PIL import Image
import os
import numpy as np
save_path = './outputs' # 上面输出的文件

# 数据集文件夹
if not os.path.exists('./dataset'):
    os.mkdir('./dataset')
original_image_dir= './dataset/images'
if not os.path.exists(original_image_dir):
    os.makedirs(original_image_dir)
label_image_dir = './dataset/labels'
if not os.path.exists(label_image_dir):
    os.makedirs(label_image_dir)

# 保存所有的标签
def make_all_label_name_txt():
    with open('./dataset/all_label_names.txt','w',encoding='utf-8') as fw:
        label_set =set()
        label_names_list = ['_background_']
        label_set.add('_background_')
        for per_img_dir in os.listdir(save_path):
            with open(os.path.join(save_path,per_img_dir,'label_names.txt'),'r',encoding='utf-8') as fr:
                label = fr.readlines()
                for i in label:
                    i = i.strip('\n')
                    if i in label_set:
                        pass
                    else:
                        label_set.add(i)
                        label_names_list.append(i)
        for label in label_names_list:
            fw.write(label+'\n')
        print('所有的标签',label_names_list)


def make_label():
    """因为每个图像的标签都是从0开始，需要自己修改"""
    with open('./dataset/all_label_names.txt','r',encoding='utf-8') as f:
        label_list = [i.strip() for i in f.readlines()]
    for per_img_dir in os.listdir(save_path):
        for img_path in os.listdir(os.path.join(save_path,per_img_dir)):
            if img_path.endswith('.jpg'):
                origin_image_path = os.path.join(save_path,per_img_dir,img_path)

                img = Image.open(origin_image_path)
                img.save(os.path.join(original_image_dir,img_path))
            elif img_path.endswith('_label.png'):

                label_image_path = os.path.join(save_path,per_img_dir,img_path)
                # 打开每个图像的label_names.txt
                with open(os.path.join(save_path,per_img_dir,'label_names.txt'), 'r', encoding='utf-8') as perf:
                    per_label_list = [i.strip() for i in perf.readlines()]   
                # 打开图像
                img = Image.open(label_image_path)
                img_arr = np.array(img)
                for i, label_val in enumerate(per_label_list):
                   
                    img_arr[img_arr==i] = label_list.index(label_val)
           
     
                img_arr =  np.asarray(img_arr, np.uint8)
                img =Image.fromarray(img_arr)
                img.save(os.path.join(label_image_dir,img_path))
make_all_label_name_txt()
make_label()

制作完了标签是黑色的不要怀疑，自己可以根据指定的色彩替换像素，看着直观