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| import spaces | |
| import torch | |
| from diffusers import CogVideoXImageToVideoPipeline | |
| from diffusers.utils import export_to_video, load_image | |
| import gradio as gr | |
| pipe = CogVideoXImageToVideoPipeline.from_pretrained( | |
| "THUDM/CogVideoX-5b-I2V", | |
| torch_dtype=torch.bfloat16 | |
| ) | |
| def generate_video(prompt, image): | |
| # Ensure the generator is on the same device as the model | |
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| pipe.to("cuda") | |
| generator = torch.Generator(device=device).manual_seed(42) | |
| video = pipe( | |
| prompt=prompt, | |
| image=image, | |
| num_videos_per_prompt=1, | |
| num_inference_steps=15, | |
| num_frames=49, | |
| guidance_scale=6, | |
| generator=generator, | |
| ).frames[0] | |
| video_path = "output.mp4" | |
| export_to_video(video, video_path, fps=8) | |
| return video_path | |
| # Interface Gradio | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# Image to Video Generation") | |
| with gr.Row(): | |
| # Entrada de texto para o prompt | |
| prompt_input = gr.Textbox(label="Prompt", value="A little girl is riding a bicycle at high speed. Focused, detailed, realistic.") | |
| # Upload de imagem | |
| image_input = gr.Image(label="Upload an Image", type="pil") | |
| # Botão para gerar o vídeo | |
| generate_button = gr.Button("Generate Video") | |
| # Saída do vídeo gerado | |
| video_output = gr.Video(label="Generated Video") | |
| # Ação ao clicar no botão | |
| generate_button.click(fn=generate_video, inputs=[prompt_input, image_input], outputs=video_output) | |
| # Rodar a interface | |
| demo.launch() | |