Spaces:
Running
on
Zero
Running
on
Zero
import spaces | |
import gradio as gr | |
import cv2 | |
import numpy as np | |
import time | |
import random | |
from PIL import Image | |
import torch | |
torch.jit.script = lambda f: f | |
from transparent_background import Remover | |
def doo(video, mode, progress=gr.Progress()): | |
if mode == 'Fast': | |
remover = Remover(mode='fast') | |
else: | |
remover = Remover() | |
cap = cv2.VideoCapture(video) | |
total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT)) # Get total frames | |
writer = None | |
tmpname = random.randint(111111111, 999999999) | |
processed_frames = 0 | |
start_time = time.time() | |
while cap.isOpened(): | |
ret, frame = cap.read() | |
if ret is False: | |
break | |
if time.time() - start_time >= 20 * 60 - 5: | |
print("GPU Timeout is coming") | |
cap.release() | |
writer.release() | |
return str(tmpname) + '.mp4' | |
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) | |
img = Image.fromarray(frame).convert('RGB') | |
if writer is None: | |
writer = cv2.VideoWriter(str(tmpname) + '.mp4', cv2.VideoWriter_fourcc(*'mp4v'), cap.get(cv2.CAP_PROP_FPS), img.size) | |
processed_frames += 1 | |
print(f"Processing frame {processed_frames}") | |
progress(processed_frames / total_frames, desc=f"Processing frame {processed_frames}/{total_frames}") | |
out = remover.process(img, type='green') | |
writer.write(cv2.cvtColor(np.array(out), cv2.COLOR_BGR2RGB)) | |
cap.release() | |
writer.release() | |
return str(tmpname) + '.mp4' | |
examples = [['./mp4.mp4']] | |
css = """ | |
footer { | |
visibility: hidden; | |
} | |
""" | |
iface = gr.Interface(theme="Nymbo/Nymbo_Theme", css=css, | |
fn=doo, | |
inputs=["video", gr.components.Radio(['Normal', 'Fast'], label='Select mode', value='Normal', info='Normal is more accurate, but takes longer. | Fast has lower accuracy so the process will be faster.')], | |
outputs="video", | |
examples=examples | |
) | |
iface.launch() | |