app.py

import gradio as gr
import cv2
from moviepy.editor import VideoFileClip, ImageSequenceClip
import numpy as np
from diffusers import AutoPipelineForImage2Image
from diffusers.utils import load_image

# Load the anime-style model
pipe = AutoPipelineForImage2Image.from_pretrained(
    "nitrosocke/Arcane-Diffusion",
    safety_checker=None,
)
pipe.to("cuda")

# Function to process a single frame
def process_frame(frame, prompt):
    # Convert frame from BGR (OpenCV) to RGB
    frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    # Load the frame as an image for the model
    image = load_image(frame)
    # Apply the anime-style transformation
    result = pipe(prompt=prompt, image=image, strength=0.75).images[0]
    return np.array(result)

# Function to convert the entire video
def video_to_anime(video_path, prompt="Arcane style"):
    # Load the video and extract frames
    clip = VideoFileClip(video_path)
    frames = [frame for frame in clip.iter_frames()]

    # Process each frame with the anime-style model
    processed_frames = [process_frame(frame, prompt) for frame in frames]

    # Reassemble the processed frames into a video
    new_clip = ImageSequenceClip(processed_frames, fps=clip.fps)
    output_path = "output.mp4"
    new_clip.write_videofile(output_path, codec="libx264")

    return output_path

# Create the Gradio interface
iface = gr.Interface(
    fn=video_to_anime,
    inputs=[
        gr.Video(label="Input Video"),
        gr.Textbox(label="Style Prompt", default="Arcane style")
    ],
    outputs=gr.Video(label="Output Video"),
    title="Video to Anime Converter",
    description="Upload a video and convert it to anime style!"
)

# Launch the interface
iface.launch()