app.py

import gradio as gr
from src.inference import SwinTExCo
import cv2
import os
from PIL import Image
import time
import app_config as cfg


model = SwinTExCo(weights_path=cfg.ckpt_path)

def video_colorization(video_path, ref_image, progress=gr.Progress()):
    # Initialize video reader
    video_reader = cv2.VideoCapture(video_path)
    fps = video_reader.get(cv2.CAP_PROP_FPS)
    height = int(video_reader.get(cv2.CAP_PROP_FRAME_HEIGHT))
    width = int(video_reader.get(cv2.CAP_PROP_FRAME_WIDTH))
    num_frames = int(video_reader.get(cv2.CAP_PROP_FRAME_COUNT))
    
    # Initialize reference image
    ref_image = Image.fromarray(ref_image)
    
    # Initialize video writer
    output_path = os.path.join(os.path.dirname(video_path), os.path.basename(video_path).split('.')[0] + '_colorized.mp4')
    video_writer = cv2.VideoWriter(output_path, cv2.VideoWriter_fourcc(*'mp4v'), fps, (width, height))
    
    # Init progress bar
    
    for colorized_frame, _ in zip(model.predict_video(video_reader, ref_image), progress.tqdm(range(num_frames), desc="Colorizing video", unit="frames")):
        video_writer.write(colorized_frame)
    
    # for i in progress.tqdm(range(1000)):
    #     time.sleep(0.5)
        
    video_writer.release()
    
    return output_path

app = gr.Interface(
    fn=video_colorization,
    inputs=[gr.Video(format="mp4", sources="upload", label="Input video (grayscale)", interactive=True), 
            gr.Image(sources="upload", label="Reference image (color)")],
    outputs=gr.Video(label="Output video (colorized)"),
    title=cfg.TITLE,
    description=cfg.DESCRIPTION
).queue()


app.launch()