preview_test.py

import gradio as gr
import cv2

def extract_frames(video_path):
    # Open the video file
    cap = cv2.VideoCapture(video_path)
    if not cap.isOpened():
        # If video cannot be opened, return four None values
        return [None] * 4
    
    # Get the total number of frames
    total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
    if total_frames == 0:
        # If video has no frames, release and return None values
        cap.release()
        return [None] * 4
    
    # Calculate frame indices at 0%, 25%, 50%, and 75%
    indices = [int(total_frames * i / 4) for i in range(4)]
    frames = []
    
    # Extract frames at the calculated indices
    for idx in indices:
        cap.set(cv2.CAP_PROP_POS_FRAMES, idx)
        ret, frame = cap.read()
        if ret:
            # Convert from BGR (OpenCV format) to RGB (Gradio format)
            frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
            frames.append(frame)
        else:
            # If frame extraction fails, append None
            frames.append(None)
    
    # Release the video capture object
    cap.release()
    
    # Return the four frames as a tuple for Gradio outputs
    return tuple(frames)

# Create the Gradio interface
iface = gr.Interface(
    fn=extract_frames,
    inputs=gr.Video(label="Upload a video"),
    outputs=[gr.Image(label=f"Frame at {i*25}%") for i in range(4)],
    title="Video Frame Extractor",
    description="Upload a video to extract four frames from different parts of the video."
)

# Launch the web app
iface.launch()