摘要：

labelme是常用的标注工具，由于最近要用到示例分割的模型，需要把labelme的polygon格式转为mask，这里用与复旦行人检测数据集类似的方式生成mask，即：背景像素值0，目标物体像素值根据目标个数依次确定，如：有两个物体则像素值依次为1,2，有5个物体则依次为1,2,3,4,5.
重写也不是很困难但是某些小细节上可能会坑你好久，造个轮子后面直接用。

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源码

import cv2 as cv
import numpy as np
import json
import os


def convertPolygonToMask(jsonfilePath):
    with open(jsonfilePath, "r", encoding='utf-8') as jsonf:
        jsonData = json.load(jsonf)
        img_h = jsonData["imageHeight"]
        img_w = jsonData["imageWidth"]
        mask = np.zeros((img_h, img_w), np.uint8)
        #图片中目标的数量 num=len(jsonData["shapes"])
        num = 0
        for obj in jsonData["shapes"]:
            label = obj["label"]
            polygonPoints = obj["points"]
            polygonPoints = np.array(polygonPoints,np.int32)
            # print("+" * 50, "\n", polygonPoints)
            # print(label)
            num+=1
            cv.drawContours(mask,[polygonPoints],-1,(255),-1)

    return mask

def main():
    jsonfileFolder = r"K:\imageData\colorR\dataset\label"
    maskSaveFolder = r"K:\imageData\colorR\dataset\mask"

    for jsonfile in os.listdir(jsonfileFolder):
        jsonfilePath = os.path.join(jsonfileFolder,jsonfile)
        mask = convertPolygonToMask(jsonfilePath)
        maskName = jsonfile.split(".")[0] + ".png"
        maskPath = os.path.join(maskSaveFolder,maskName)
        cv.imwrite(maskPath,mask)


if __name__ == "__main__":
    #main()
    jsonfilePath = r"K:\deepImage\del\1.json"
    maskSaveFolder = r"K:\deepImage\del"
    mask = convertPolygonToMask(jsonfilePath)
    # 为了可视化把mask做一下阈值分割
    _, th = cv.threshold(mask, 0, 255, cv.THRESH_BINARY)
    cv.imshow("mask", th)
    src = cv.imread(r"K:\deepImage\del\1.jpg")
    cv.imwrite(maskSaveFolder + "\mask.png", mask)
    cv.imshow("src", src)
    cv.waitKey(0)
    cv.destroyAllWindows()

示例

• 对比 在这里插入图片描述

• mask保存后用3D surface显示如下

  
  2.png