# 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')
SHARED_UI_WARNING = f'''## Attention - Running doesn't work in this shared UI. You can duplicate and use it with a paid private T4 GPU.
'''
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:
gr.HTML('''
Duplicate the Space and run securely with your machine''')
if not torch.cuda.is_available():
show_warning(CUDA_NOT_AVAILABLE_WARNING)
# elif SPACE_ID == ORIGINAL_SPACE_ID:
# show_warning(SHARED_UI_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=False)