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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.Image(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() |