json_to_mask

'''
修改后的json_to_dataset文件，直接复制替换你自己原始的json_to_dataset，建议保存一下原版
'''
import argparse
import base64
import json
import os
import os.path as ospimport imgviz
import PIL.Imagefrom labelme.logger import logger
from labelme import utilsdef main():"""logger.warning("This script is aimed to demonstrate how to convert the ""JSON file to a single image dataset.")logger.warning("It won't handle multiple JSON files to generate a ""real-use dataset.")"""parser = argparse.ArgumentParser()parser.add_argument("json_file")parser.add_argument("-o", "--out", default=None)args = parser.parse_args()json_file = args.json_fileprint(osp.dirname(json_file))if osp.isdir(osp.join(osp.dirname(json_file), 'json_data')) is False:os.mkdir(osp.join(osp.dirname(json_file), 'json_data'))else:print("文件已存在")if args.out is None:out_dir = osp.basename(json_file).replace(".", "_")out_dir1 = osp.join(osp.dirname(json_file), 'json_data')out_dir = osp.join(out_dir1, out_dir)print(out_dir)print("#" * 10)else:out_dir = args.outif not osp.exists(out_dir):os.mkdir(out_dir)data = json.load(open(json_file))imageData = data.get("imageData")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_valuelbl = 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] = namelbl_viz = imgviz.label2rgb(lbl, imgviz.asgray(img), label_names=label_names, loc="rb")PIL.Image.fromarray(img).save(osp.join(out_dir, "img.png"))utils.lblsave(osp.join(out_dir, "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")logger.info("Saved to: {}".format(out_dir))if __name__ == "__main__":main()

修改地方：删除lbl后的“,-” ，只让lbl接受函数结果，要不然会报返回值与接受值不匹配的错误，ValueError: too many values to unpack (expected 2)。这类错误出现原因是比如返回三个值，但你用2个变量接受。