import os
os.system('pip install gradio --upgrade')
os.system('pip freeze')
import torch
import gradio as gr
from moviepy.editor import *

model = torch.hub.load("PeterL1n/RobustVideoMatting", "mobilenetv3") # or "resnet50"

convert_video = torch.hub.load("PeterL1n/RobustVideoMatting", "converter")

def inference(video):
  os.system('rm output.mp4')
  #clip = VideoFileClip(video).subclip(0, 5)
  #clip.write_videofile("output.mp4")
  os.system('ffmpeg -ss 00:00:00 -i '+ video +' -to 00:00:05 -c copy -y output.mp4')
  convert_video(
      model,                           # The loaded model, can be on any device (cpu or cuda).
      input_source='output.mp4',        # A video file or an image sequence directory.
      input_resize=(500, 500),       # [Optional] Resize the input (also the output).
      downsample_ratio=0.25,           # [Optional] If None, make downsampled max size be 512px.
      output_type='video',             # Choose "video" or "png_sequence"
      output_composition='com.mp4',    # File path if video; directory path if png sequence.
      output_alpha="pha.mp4",          # [Optional] Output the raw alpha prediction.
      output_foreground="fgr.mp4",     # [Optional] Output the raw foreground prediction.
      output_video_mbps=4,             # Output video mbps. Not needed for png sequence.
      seq_chunk=7,                    # Process n frames at once for better parallelism.
      num_workers=1,                   # Only for image sequence input. Reader threads.
      progress=True                    # Print conversion progress.
  )
  return 'com.mp4',"pha.mp4","fgr.mp4"
  
title = "Robust Video Matting"
description = "Gradio demo for Robust Video Matting. To use it, simply upload your video, currently only mp4 and ogg formats are supported. Please trim video to 5 seconds or less. Read more at the links below."

article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2108.11515'>Robust High-Resolution Video Matting with Temporal Guidance</a> | <a href='https://github.com/PeterL1n/RobustVideoMatting'>Github Repo</a></p>"


gr.Interface(
    inference, 
    gr.inputs.Video(label="Input"), 
    [gr.outputs.Video(label="Output Composition"),gr.outputs.Video(label="Output Alpha"),gr.outputs.Video(label="Output Foreground")],
    title=title,
    description=description,
    article=article,
    enable_queue=True).launch(debug=True)