How to save output of darknet YOLOv4 video in a txt file for each frame?

I am using darknet to detect objects with YOLOv4 on my custom made dataset. For this detection on videos I use:

./darknet detector demo data/obj.data yolo-obj.cfg yolo-obj_best.weights -ext_output video.mp4 -out-filename video_results.mp4

This gives my the video with the bounding boxes printed for every detection. However, I want to create a .txt (or .csv) file with for each frame number the prediction(s).

I did find this answer, but this gives the output in a json file and I need a .txt or .csv file. I am not so familiar with C so I find it hard to modify this answer into the format I need.

I followed the suggestion by Rafael and wrote a some code to move from JSON to cvs. I'll put it here in case anyone wants to use it. This is for the case in which a video was analyzed, so each "image" is a frame in a video.

import json
import csv

# with and height of the video
WIDTH = 1920
HEIGHT = 1080


with open('~/detection_results.json', encoding='latin-1') as json_file:
    data = json.load(json_file)
    
# open csv file
csv_file_to_make = open('~/detection_results.csv', 'w', newline='\n')

csv_file = csv.writer(csv_file_to_make)

# write the header 
# NB x and y values are relative
csv_file.writerow(['Frame ID',
                   'class',
                   'x_center',
                   'y_center',
                   'bb_width',
                   'bb_heigth',
                   'confidence'])


for frame in data:
    frame_id = frame['frame_id']
    instrument = ""
    center_x = ""
    center_y = ""
    bb_width = ""
    bb_height = ""
    confidence = ""

    if frame['objects'] == []:
        csv_file.writerow([frame_id,
                              class,
                              center_x,
                              center_y,
                              bb_width,
                              bb_height,
                              confidence
                               ])
    else:
        for single_detection in frame['objects']:
            instrument = single_detection['name']
            center_x = WIDTH*single_detection['relative_coordinates']['center_x']
            center_y = HEIGHT*single_detection['relative_coordinates']['center_y']
            bb_width = WIDTH*single_detection['relative_coordinates']['width']
            bb_height = HEIGHT*single_detection['relative_coordinates']['height']
            confidence = single_detection['confidence']
        
            csv_file.writerow([frame_id,
                              class,
                              center_x,
                              center_y,
                              bb_width,
                              bb_height,
                              confidence
                               ])
    
csv_file_to_make.close()

Hope this helps! If you see a solution to optimize this code that's also welcome of course :)