# Most code is from https://huggingface.co/spaces/Tune-A-Video-library/Tune-A-Video-Training-UI
#!/usr/bin/env python
from __future__ import annotations
import os
from subprocess import getoutput
import gradio as gr
import torch
from gradio_demo.app_running import create_demo
from gradio_demo.runner import Runner
TITLE = '# [vid2vid-zero](https://github.com/baaivision/vid2vid-zero)'
ORIGINAL_SPACE_ID = 'BAAI/vid2vid-zero'
SPACE_ID = os.getenv('SPACE_ID', ORIGINAL_SPACE_ID)
GPU_DATA = getoutput('nvidia-smi')
if os.getenv('SYSTEM') == 'spaces' and SPACE_ID != ORIGINAL_SPACE_ID:
SETTINGS = f'Settings'
else:
SETTINGS = 'Settings'
CUDA_NOT_AVAILABLE_WARNING = f'''## Attention - Running on CPU.
You can assign a GPU in the {SETTINGS} tab if you are running this on HF Spaces.
You can use "T4 small/medium" to run this demo.
'''
HF_TOKEN_NOT_SPECIFIED_WARNING = f'''The environment variable `HF_TOKEN` is not specified. Feel free to specify your Hugging Face token with write permission if you don't want to manually provide it for every run.
You can check and create your Hugging Face tokens here.
You can specify environment variables in the "Repository secrets" section of the {SETTINGS} tab.
'''
HF_TOKEN = os.getenv('HF_TOKEN')
def show_warning(warning_text: str) -> gr.Blocks:
with gr.Blocks() as demo:
with gr.Box():
gr.Markdown(warning_text)
return demo
pipe = None
runner = Runner(HF_TOKEN)
with gr.Blocks(css='gradio_demo/style.css') as demo:
if not torch.cuda.is_available():
show_warning(CUDA_NOT_AVAILABLE_WARNING)
gr.Markdown(TITLE)
with gr.Tabs():
with gr.TabItem('Zero-shot Testing'):
create_demo(runner, pipe)
if not HF_TOKEN:
show_warning(HF_TOKEN_NOT_SPECIFIED_WARNING)
demo.queue(max_size=1).launch(share=True)