import spaces import gradio as gr import cv2 import numpy as np import os from PIL import Image from transparent_background import Remover remover = Remover() @spaces.GPU def doo(video): cap = cv2.VideoCapture(video) fps = cap.get(cv2.CAP_PROP_FPS) writer = None frame_count = 0 max_frames = 50 # Maximum number of frames to process at a time segment_count = 0 # Count of video segments processed total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT)) # Total number of frames in the video processed_frames = 0 # Number of frames processed so far while cap.isOpened(): ret, frame = cap.read() if ret is False: break frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) img = Image.fromarray(frame).convert('RGB') if writer is None: writer = cv2.VideoWriter(f'output_{segment_count}.mp4', cv2.VideoWriter_fourcc(*'mp4v'), fps, img.size) out = remover.process(img, type='green') writer.write(cv2.cvtColor(np.array(out), cv2.COLOR_BGR2RGB)) frame_count += 1 processed_frames += 1 # Print progress information print(f"Processing: {processed_frames}/{total_frames} frames") if frame_count >= max_frames: cap.release() writer.release() # Process the next segment cap = cv2.VideoCapture(video) for _ in range(frame_count): cap.read() # Skip frames that have already been processed writer = None frame_count = 0 segment_count += 1 cap.release() if writer is not None: writer.release() # Concatenate all the video segments final_output = cv2.VideoWriter('final_output.mp4', cv2.VideoWriter_fourcc(*'mp4v'), fps, img.size) for i in range(segment_count): cap = cv2.VideoCapture(f'output_{i}.mp4') while cap.isOpened(): ret, frame = cap.read() if ret is False: break final_output.write(frame) cap.release() os.remove(f'output_{i}.mp4') # Delete the segment file final_output.release() return 'final_output.mp4' iface = gr.Interface(fn=doo, inputs="video", outputs="video") iface.launch()