labelme指定輸出檔案夾 批量json轉png --圖像分割資料集準備

用labelme标注之後，導出的是json檔案，我們可用labelme自帶的json_to_datase.py來把json轉為png圖檔

假如我的json檔案名為event_172.json

轉成的是一個檔案夾

檔案夾有如下檔案，其中label.png是我想要的mask圖檔

現在想批量把json檔案夾下所有的json檔案都統一轉為對應名稱的png（比如172.json轉為172.png），并儲存到我指定的輸出檔案夾下

步驟如下：

找到 labelme自帶的json_to_dataset.py

可用conda env list指令找到目前labelme環境所在的檔案夾

在環境檔案夾下到

把json_to_dataset.py的代碼拷到其他py檔案裡（最好不要修改原檔案），并修改如下

因為這裡我隻要mask的圖檔，是以隻輸出一個png

ps: 代碼基本沒修改，隻加了一個file的循環，注釋掉了不需要的輸出

運作結果：在mask檔案夾下輸出了對應名稱的png圖檔

#import argparse
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():
    # 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."
    # )
    json_folder = "./json"
    out_dir = "./mask"
    if not osp.exists(out_dir):
        os.mkdir(out_dir)

    json_list = os.listdir(json_folder)
    for i in range(0, len(json_list)):
        json_file = os.path.join(json_folder, json_list[i])
        out_name = json_list[i][:-5]
        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_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"
        # )

        #PIL.Image.fromarray(img).save(osp.join(out_dir, "img.png"))
        utils.lblsave(osp.join(out_dir, out_name+".png"), lbl)
        #PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir, "label_viz.png"))


        #logger.info("Saved to: {}".format(out_dir))


if __name__ == "__main__":
    main()