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import gradio as gr
import torch
import torchvision
from diffusers import I2VGenXLPipeline
from diffusers.utils.loading_utils import load_image
from PIL import Image
def generate(image: Image.Image, prompt: str):
negative_prompt = "Distorted, discontinuous, Ugly, blurry, low resolution, motionless, static, disfigured, disconnected limbs, Ugly faces, incomplete arms"
generator = torch.manual_seed(8888)
image = image.convert("RGB")
pipeline = I2VGenXLPipeline.from_pretrained("ali-vilab/i2vgen-xl", torch_dtype=torch.float16, variant="fp16")
pipeline.enable_model_cpu_offload()
pipeline.unet.enable_forward_chunking()
frames = pipeline(
prompt=prompt,
image=image,
num_inference_steps=50,
negative_prompt=negative_prompt,
guidance_scale=9.0,
generator=generator,
decode_chunk_size=6,
).frames[0]
torchvision.io.write_video("video.mp4", frames, fps=16)
return "video.mp4"
app = gr.Interface(
fn=generate,
inputs=[gr.Image(type="pil"), "text"],
outputs=gr.Video()
)
if __name__ == "__main__":
app.launch()
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