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import gradio as gr | |
from diffusers import DiffusionPipeline | |
import torch | |
from PIL import Image | |
import spaces | |
# Load the pre-trained pipeline | |
pipeline = DiffusionPipeline.from_pretrained("stabilityai/stable-video-diffusion-img2vid-xt") | |
# Define the Gradio interface | |
interface = gr.Interface( | |
fn=lambda img: generate_video(img), | |
inputs=gr.Image(type="pil"), | |
outputs=gr.Video(), | |
title="Stable Video Diffusion", | |
description="Upload an image to generate a video", | |
theme="soft" | |
) | |
def generate_video(image): | |
""" | |
Generates a video from an input image using the pipeline. | |
Args: | |
image: A PIL Image object representing the input image. | |
Returns: | |
A list of PIL Images representing the video frames. | |
""" | |
video_frames = pipeline(image=image).images | |
return video_frames | |
# Launch the Gradio app | |
interface.launch() |