Why am I getting AttributeError in yolo.py on my linux terminal when i run darknet Yolov3?

Question

Error (from linux terminal):

File "yolo.py", line 98, in writer.release() AttributeError: 'NoneType' object has no attribute 'release'

I've added the image focusing on the portion of the code that contains the error. I've also included the entire code of the file just incase. I have no clue as to why I'm even getting that error.

import numpy as np
import argparse
import cv2 as cv
import subprocess
import time
import os
from yolo_utils import infer_image

FLAGS = []

if __name__ == '__main__':
    parser = argparse.ArgumentParser()

    parser.add_argument('-w', '--weights',
        type=str,
        default='./yolov3.weights',
        help='Path to the file which contains the weights \
                for YOLOv3.')

    parser.add_argument('-cfg', '--config',
        type=str,
        default='./cfg/yolov3.cfg',
        help='Path to the configuration file for the YOLOv3 model.')

    parser.add_argument('-v', '--video-path',
        type=str,
        help='The path to the video file')


    parser.add_argument('-vo', '--video-output-path',
        type=str,
        default='./output.mp4',
        help='The path of the output video file')

    parser.add_argument('-l', '--labels',
        type=str,
        default='./coco-labels',
        help='Path to the file having the \
                    labels in a new-line seperated way.')

    parser.add_argument('-c', '--confidence',
        type=float,
        default=0.5,
        help='The model will reject boundaries which has a \
                probabiity less than the confidence value. \
                default: 0.5')

    parser.add_argument('-th', '--threshold',
        type=float,
        default=0.3,
        help='The threshold to use when applying the \
                Non-Max Suppresion')

    FLAGS, unparsed = parser.parse_known_args()

    # Get the labels
    labels = open(FLAGS.labels).read().strip().split('\n')

    # Intializing colors to represent each label uniquely
    colors = np.random.randint(0, 255, size=(len(labels), 3), dtype='uint8')

    # Load the weights and configutation to form the pretrained YOLOv3 model
    net = cv.dnn.readNetFromDarknet(FLAGS.config, FLAGS.weights)

    # Get the output layer names of the model
    layer_names = net.getLayerNames()
    layer_names = [layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()]

    # If both image and video files are given then raise error
    if FLAGS.video_path is None:
        print ('Path to video not provided')

    elif FLAGS.video_path:
        # Read the video
        vid = cv.VideoCapture(str(FLAGS.video_path))
        height, width, writer= None, None, None
        while True:

            grabbed, frame = vid.read()

            if not grabbed:
                break

            if width is None or height is None:
                height, width = frame.shape[:2]

            frame, _, _, _, _ = infer_image(net, layer_names, height, width, frame, colors, labels, FLAGS)

            if writer is None:
                fourcc = cv.VideoWriter_fourcc(*'mp4v')
                writer = cv.VideoWriter(FLAGS.video_output_path, fourcc, 30,(frame.shape[1], frame.shape[0]), True)


            writer.write(frame)


        print ("[INFO] Cleaning up...")
        writer.release()
        vid.release()


    else:
        print("[ERROR] Something's not right...")

the image showing last portion of the code where the error is located:

Answer 1

You are breaking the while loop when grabbed is False, meaning you never assigned a writer and it is kept as a None type object. Since that is false, it means your Video capture is failing, suggesting that the file path is incorrect and/or forgotten to add the video extension.