import gradio as gr
import os
import cv2
from encoded_video import EncodedVideo, write_video
import torch
import numpy as np

def video_identity(filepath):
    vid = EncodedVideo.from_path(filepath)
    clip = vid.get_clip(start_sec, start_sec + duration)
    video_arr = torch.from_numpy(clip['video']).permute(3, 0, 1, 2)
    write_video('out.mp4', video_arr, fps=60)
    capture = cv2.VideoCapture('out.mp4')
    while (True):
    
        success, frame = capture.read()

        if success:
            cv2.imwrite(f'train/frame_{frameNr}.jpg', frame)

        else:
            break

        frameNr = frameNr+10
    img=cv2.imread('train/frame_0')
    return img
demo = gr.Interface(video_identity, 
                    gr.inputs.Video(source='upload'), 
                    gr.inputs.Image(), 
                    cache_examples=True)
demo.launch(debug=True)