[Python知识库]从mask读取轮廓点坐标到json文件

import os
from collections import defaultdict, OrderedDict
import json
import numpy as np
import cv2
import glob

class NpEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, np.integer):
            return int(obj)
        elif isinstance(obj, np.floating):
            return float(obj)
        elif isinstance(obj, np.ndarray):
            return obj.tolist()
        else:
            return super(NpEncoder, self).default(obj)


results = defaultdict(list)
mask = defaultdict(list)
volume= defaultdict(list)
stress= defaultdict(list)
parm= defaultdict(list)

line=defaultdict(list)
param=defaultdict(list)


results["mask"] =[]
results["volume"] =volume
results["stress"] =stress
results["parm"] =param
# mask["series_number"]=1
# mask["slice_index"]=1
# mask["rois"]=rois
# rois["RV"]= contours1
# rois["LV-Inner"]=contours2[0]
# rois["LV-Ext"]=contours2[1]
# rois["PPM"]=contours4
volume["line"]=[[10, 100], [20, 3000]]
volume["ED"]=10
volume["ES"]=100
stress["GLS"]=-19.5
stress["GCS"]=-17.7
stress["GRS"]=39.7
param["EDV"]=201
param["ESV"]=105
param["LVM"]=189

test_dict = {
    "patientID": "0000086930",
    "studyUID": "1.2.842065.95027634.776400958",
    "seriesUID": "1.3.12.2.1107.5.2.43.166151.2022011508231736189313766.0.0.0",
    "task": "CardiacMRI",
    'results': results,

}


# files = glob.glob('./data/test/outputs/1464455/*')
files = os.listdir('./data/test/pre/1464455/')
print('files1',files)
files.sort()
print('files2',files)

# for imgp in os.listdir('./data/test/pre/1464455'):
for imgp in files:
    # imbgr = cv2.imread('./data/test/pre/1464457/224.png')
    id=str(imgp).replace('.png','')
    print('id', id)
    imgp=os.path.join('./data/test/pre/1464455', imgp)
    print('imgp',imgp)
    imbgr = cv2.imread(imgp)
    imgray_path=imgp.replace('pre','outputs')
    imgray = cv2.imread(imgray_path, 0)
    # 以灰度图读取mask图片，那么不同物体对应的像素值是不同的，提取统一像素值的所有位置
    img = np.array(imgray)
    # mask中物体1 RV 的像素值为38，设定像素范围来获取所有坐标
    upper1 = img <= 40
    lower1 = img >= 30
    thresh1 = (np.multiply(upper1, lower1).astype(np.float32) * 255).astype(np.uint8)

    # mask中物体2 Myo 的像素值为75，设定像素范围来获取所有坐标
    upper2 = imgray <= 80
    lower2 = imgray >= 60
    thresh2 = (np.multiply(upper2, lower2).astype(np.float32) * 255).astype(np.uint8)

    # mask中物体3  LV的像素值为113，设定像素范围来获取所有坐标
    upper3 = imgray <= 120
    lower3 = imgray >= 110
    thresh3 = (np.multiply(upper3, lower3).astype(np.float32) * 255).astype(np.uint8)

    # mask中物体4  PPm的像素值为15，设定像素范围来获取所有坐标
    upper4 = imgray <= 20
    lower4 = imgray >= 5
    thresh4 = (np.multiply(upper4, lower4).astype(np.float32) * 255).astype(np.uint8)

    contours1, hierarchy1 = cv2.findContours(thresh1, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    contours2, hierarchy2 = cv2.findContours(thresh2, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    contours3, hierarchy3 = cv2.findContours(thresh3, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    contours4, hierarchy4 = cv2.findContours(thresh4, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    lst1 = []
    for i, cous in enumerate(contours1):
        a = cv2.contourArea(cous)
        print('contours1:', i, a)
        if a >= 100:
            lst1.append(cous)
    contours1 = lst1

    lst2 = []
    for i, cous in enumerate(contours2):
        a = cv2.contourArea(cous)
        print('contours2:', i, a)
        if a >= 30:
            lst2.append(cous)
    contours2 = lst2

    lst4 = []
    for i, cous in enumerate(contours4):
        a = cv2.contourArea(cous)
        print('contours4:', i, a)
        if a >= 5:
            lst4.append(cous)
    contours4 = lst4

    label = defaultdict(list)
    rois = defaultdict(list)
    RV = defaultdict(list)
    LVI = defaultdict(list)
    LVE = defaultdict(list)
    PPM = defaultdict(list)

    label["series_number"]=1
    label["slice_index"] = int(id)
    print('label-id',id)
    label["rois"]=rois

    if contours1:
            rois["RV"]=contours1
    else :  rois["RV"]=[]

    if len(contours2) == 1:
        rois["LV-Inner"] = contours2[0]
        rois["LV-Ext"] = []
    elif  len(contours2)>=2:
            rois["LV-Inner"]=contours2[0]
            rois["LV-Ext"] = contours2[1]
    else:
            rois["LV-Inner"]=[]
            rois["LV-Ext"]=[]

    rois["LV-Ext"]=[]

    if contours4:
        rois["PPM"]=contours4
    else:rois["PPM"]=[]

    results["mask"].append(label)



json_str = json.dumps(test_dict, cls=NpEncoder)
with open('patient-1464455.json', 'w') as json_file:
    json_file.write(json_str)