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| import torch | |
| from diffusers import StableDiffusionPipeline, DDIMScheduler | |
| # load sd model | |
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| model_id = "stabilityai/stable-diffusion-2-1-base" | |
| inv_pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to(device) | |
| inv_pipe.scheduler = DDIMScheduler.from_pretrained(model_id, subfolder="scheduler") | |
| def preprocess(data_path:str = 'examples/woman-running.mp4', | |
| height:int = 512, | |
| weidth: int = 512, | |
| # save_dir: str = "latents", | |
| steps: int = 500, | |
| batch_size: int = 8, | |
| save_steps: int = 50, | |
| n_frames: int = 40, | |
| inversion_prompt:str = '' | |
| ): | |
| # save_video_frames(data_path, img_size=(height, weidth)) | |
| frames = video_to_frames(data_path, img_size=(height, weidth)) | |
| # data_path = os.path.join('data', Path(video_path).stem) | |
| toy_scheduler = DDIMScheduler.from_pretrained(model_id, subfolder="scheduler") | |
| toy_scheduler.set_timesteps(save_steps) | |
| timesteps_to_save, num_inference_steps = get_timesteps(toy_scheduler, num_inference_steps=save_steps, | |
| strength=1.0, | |
| device=device) | |
| seed_everything(1) | |
| frames, latents = get_data(inv_pipe, frames, n_frames) | |
| # inverted_latents = noisy_latents | |
| inverted_latents = extract_latents(inv_pipe, num_steps = steps, | |
| latent_frames = latents, | |
| batch_size = batch_size, | |
| timesteps_to_save = timesteps_to_save, | |
| inversion_prompt = inversion_prompt,) | |
| return frames, latents, inverted_latents | |
| import gradio as gr | |
| ######## | |
| # demo # | |
| ######## | |
| intro = """ | |
| <h1 style="font-weight: 1400; text-align: center; margin-bottom: 7px;"> | |
| TokenFlow | |
| </h1> | |
| """ | |
| with gr.Blocks(css="style.css") as demo: | |
| gr.HTML(intro) | |
| with gr.Row(): | |
| input_vid = gr.Video(label="Input Video", interactive=True, elem_id="input_video") | |
| output_vid = gr.Video(label="Edited Video", interactive=False, elem_id="output_video") | |
| input_vid.style(height=365, width=365) | |
| output_vid.style(height=365, width=365) | |
| # with gr.Group(visible=False) as share_btn_container: | |
| # with gr.Group(elem_id="share-btn-container"): | |
| # community_icon = gr.HTML(community_icon_html, visible=True) | |
| # loading_icon = gr.HTML(loading_icon_html, visible=False) | |
| # share_button = gr.Button("Share to community", elem_id="share-btn", visible=True) | |
| with gr.Row(): | |
| inversion_progress = gr.Textbox(visible=False, label="Inversion progress") | |
| with gr.Row(): | |
| run_button = gr.Button("Edit your video!", visible=True) | |
| # with gr.Accordion("Advanced Options", open=False): | |
| demo.queue() | |
| demo.launch() |