将mask的标注信息转化为二值图，mask iou计算

1. 用seg2mask函数将segmentation转化为二值图（mask） 

2. mask_iou用来计算图片中两个mask的iou

import json
import cv2
import numpy as np
from pycocotools import mask


def json_load(json_file):
    with open(json_file, "r") as f:
        data = json.load(f)
    return data

def seg2mask():
    json_file = "517/imageset/Max15B2018081900282_A02.json"
    img = cv2.imread(json_file.replace(".json", ".jpg"))
    h, w, _ = img.shape
    data = json_load(json_file)
    segment = data['anns'][0] ['segmentation']
    # polygon -- a single object might consist of multiple parts
    # we merge all parts into one mask rle code
    rles = mask.frPyObjects(segment, h, w)
    rle = mask.merge(rles)
    area = mask.area(rles)
    bbox = mask.toBbox(rles)
    # convert rle to binart mask (numpy 2D array)
    m = mask.decode(rle)
    #m *= 255
    #print(m)
    #cv2.imwrite("test.jpg", m)
    return m


def mask_iou(mask1, mask2):
    area1 = mask1.sum()
    area2 = mask2.sum()
    inter = ((mask1+mask2)==2).sum()
    mask_iou = inter / (area1+area2-inter)
    return mask_iou

if __name__ == "__main__":
    m = seg2mask()
    mask_iou = mask_iou(m, m)