Запись данных в json файл

import numpy as np
import cv2 as cv
import argparse
import glob
import os
import time
import json
 
face_cascade = cv.CascadeClassifier('haarcascade_frontalface_default.xml')
 
ap = argparse.ArgumentParser()
 
ap.add_argument("-f", "--folder", required = True, 
    help = "path to folder with images")
args = ap.parse_args()
 
num = len([1 for x in list(os.scandir(args.folder)) if x.is_file()])
 
if not os.path.isdir('images/'):
    os.makedirs('images/')
 
d = {}
 
 
def load_images_from_folder(path):
    for (i,filename) in enumerate(os.listdir(path)):
        if filename.split('.')[-1].lower() in {'jpeg', 'jpg', 'png'}:
            face_detection(path + filename, i)
 
def face_detection(image, key):
    
    img = cv.imread(image)
    gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
 
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    if len(faces) == 0:
        print ("No faces found")
    else:
        # print (faces)
        print ("Number of faces detected: " + str(faces.shape[0]))
        for (x,y,w,h) in faces:
                #cv.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
                #print((x,y),(x+w,y+h))
                
                blurred = cv.GaussianBlur(img,(25,25),0)
                img[y:y+h,x:x+w] = blurred[y:y+h,x:x+w]
 
                #cv.rectangle(img, ((0,img.shape[0] -25)),(270, img.shape[0]), (255,255,255), -1)
                cv.resize(img,(0,0), fx = 0.5, fy = 0.5)
 
 
                #cv.putText(img, "Number of faces detected: " + str(faces.shape[0]), (0,img.shape[0] -10), cv.FONT_HERSHEY_TRIPLEX, 0.5,  (0,0,0), 1)
 
    cv.imwrite(os.path.join('images/', "image-" + str(key) + ".jpg"), img)
 
    d = { "image-" + str(key): {"Number of faces detected: " : faces.shape[0], "Coordinats:" : (x,y,x+w,y+h) }}
 
    with open('result.json', 'w') as f:
        for k,val in d.items():
            f.write(json.dumps(d))
 
if __name__ == "__main__":
 
    load_images_from_folder(args.folder)

from random import randint
 
def write(file, value):
    file.write(value + '\n')
 
def rand():
    return str(randint(-10, 10))
 
if __name__ == '__main__':
    f = open('text.txt', 'w')
    a = rand()
    write(f, a)
    b = rand()
    write(f, b)
    f.close()

   d = { "Image": 'image' + str(key) + '.jpg',
          "Number of faces detected: " : faces.shape[0],
          "Coordinats:" : (x,y,x+w,y+h)}

def face_detection(image, key):
    coor = []
    k = 1
    img = cv.imread(image)
    gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
 
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    if len(faces) == 0:
        faces = 0
        # print (faces)
        cv.imwrite(os.path.join('images/', "image-" + str(key) + ".jpg"), img)
        json_dict = create_dict(None, faces, key)
        with open('result.json', 'w') as f:
            f.write(json.dumps(json_dict))
    else:
        # print (faces)
        print ("Number of faces detected: " + str(faces.shape[0]))
        for (x,y,w,h) in faces:
                #cv.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
                #print((x,y),(x+w,y+h))
                
                blurred = cv.GaussianBlur(img,(25,25),0)
                img[y:y+h,x:x+w] = blurred[y:y+h,x:x+w]
 
                #cv.rectangle(img, ((0,img.shape[0] -25)),(270, img.shape[0]), (255,255,255), -1)
                cv.resize(img,(0,0), fx = 0.5, fy = 0.5)
                if  k == faces.shape[0]:
                    coor.append([x,y,x+w,y+h])
                    cv.imwrite(os.path.join('images/', "image-" + str(key) + ".jpg"), img)
 
                    json_dict = create_dict(str(coor), faces.shape[0], key)
                    # annotation.append(json_dict)
                    with open('result.json', 'w') as f:
                        f.write(json.dumps(json_dict))
 
                else:
                    k+=1