OpenCV error when running python script on Jetson Nano

Question

I'm running a pose estimation script on an NVIDIA Jetson Nano. It works fine on a short video I tried, but when I run it on a longer video I get the following error:

(python3.6:24822): GStreamer-CRITICAL **: 23:27:53.556: gst_element_make_from_uri: assertion 'gst_uri_is_valid (uri)' failed

(python3.6:24822): GStreamer-CRITICAL **: 23:27:53.570: gst_element_make_from_uri: assertion 'gst_uri_is_valid (uri)' failed


[ WARN:0] global /home/nvidia/host/build_opencv/nv_opencv/modules/videoio/src/cap_gstreamer.cpp (711) open OpenCV | GStreamer warning: Error opening bin: no source element for URI "/home/fvpt/Desktop/tech"

[ WARN:0] global /home/nvidia/host/build_opencv/nv_opencv/modules/videoio/src/cap_gstreamer.cpp (480) isPipelinePlaying OpenCV | GStreamer warning: GStreamer: pipeline have not been created

[ERROR:0] global /home/nvidia/host/build_opencv/nv_opencv/modules/videoio/src/cap.cpp (392) open VIDEOIO(GSTREAMER): raised OpenCV exception:

OpenCV(4.1.1) /home/nvidia/host/build_opencv/nv_opencv/modules/videoio/src/cap_gstreamer.cpp:1392: error: (-215:Assertion failed) fps > 0 in function 'open'
Process finished with exit code 0

The only place i can find "open" in my script is where i load in the json file for the pose estimation.

with open(*'path to json'*, 'r') as f:
human_pose = json.load(f)

I'm not sure what details are relevant to give - I'm running this on Ubuntu 18.04, using PyCharm but the same error happens even when I run the script from terminal. OpenCV version 4.1.1 Python version 3.6.9. It works when I run it on a video from an iphone. I created a video in davinci resolve with multiple videos from multiple sources, but it's a normal mp4, 720x576, 24 fps, nothing weird.

Example code:

import cv2
import PIL.Image, PIL.ImageFont
import numpy as np
import argparse
import os.path


parser = argparse.ArgumentParser(description='TensorRT pose estimation run')
parser.add_argument('--model', type=str, default='resnet', help='resnet or densenet')
parser.add_argument('--video', type=str, default='/home/fvpt/Desktop/tech project/videos/final.mp4', help='video file name')
args = parser.parse_args()


cap = cv2.VideoCapture(args.video)
ret_val, img = cap.read()
H = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))

W = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))

fpsvid = cap.get(cv2.CAP_PROP_FPS)

fourcc = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
dir, filename = os.path.split(args.video)
name, ext = os.path.splitext(filename)
out_video = cv2.VideoWriter('/home/fvpt/Desktop/tech project/outputs/mrf%s_%s.mp4' % (args.model, name), fourcc, fpsvid,
                            (W, H))
count = 0

count = 1
while cap.isOpened():
    ret_val, dst = cap.read()
    if ret_val == False:
        print("Frame Read End")
        break
    img = cv2.resize(dst, dsize=(640, 480), interpolation=cv2.INTER_AREA)
    pilimg = cv2.cvtColor(dst, cv2.COLOR_BGR2RGB)
    pilimg = PIL.Image.fromarray(pilimg)
    array = np.asarray(pilimg, dtype="uint8")
    out_video.write(array)
    count += 1

cv2.destroyAllWindows()
out_video.release()
cap.release()

This code works fine with this video, and this is the video it gives the error on.