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from __future__ import annotations |
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import os |
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import gradio as gr |
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from constants import MODEL_LIBRARY_ORG_NAME, UploadTarget |
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from uploader import upload |
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from utils import find_exp_dirs |
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def load_local_model_list() -> dict: |
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choices = find_exp_dirs() |
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return gr.update(choices=choices, value=choices[0] if choices else None) |
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def create_upload_demo() -> gr.Blocks: |
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model_dirs = find_exp_dirs() |
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with gr.Blocks() as demo: |
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with gr.Box(): |
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gr.Markdown('Local Models') |
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reload_button = gr.Button('Reload Model List') |
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model_dir = gr.Dropdown( |
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label='Model names', |
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choices=model_dirs, |
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value=model_dirs[0] if model_dirs else None) |
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with gr.Box(): |
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gr.Markdown('Upload Settings') |
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with gr.Row(): |
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use_private_repo = gr.Checkbox(label='Private', value=True) |
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delete_existing_repo = gr.Checkbox( |
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label='Delete existing repo of the same name', value=False) |
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upload_to = gr.Radio(label='Upload to', |
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choices=[_.value for _ in UploadTarget], |
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value=UploadTarget.MODEL_LIBRARY.value) |
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model_name = gr.Textbox(label='Model Name') |
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hf_token = gr.Text(label='Hugging Face Write Token', |
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visible=os.getenv('HF_TOKEN') is None) |
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upload_button = gr.Button('Upload') |
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gr.Markdown(f''' |
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- You can upload your trained model to your personal profile (i.e. https://huggingface.co/{{your_username}}/{{model_name}}) or to the public [Tune-A-Video Library](https://huggingface.co/{MODEL_LIBRARY_ORG_NAME}) (i.e. https://huggingface.co/{MODEL_LIBRARY_ORG_NAME}/{{model_name}}). |
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''') |
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with gr.Box(): |
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gr.Markdown('Output message') |
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output_message = gr.Markdown() |
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reload_button.click(fn=load_local_model_list, |
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inputs=None, |
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outputs=model_dir) |
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upload_button.click(fn=upload, |
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inputs=[ |
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model_dir, |
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model_name, |
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upload_to, |
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use_private_repo, |
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delete_existing_repo, |
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hf_token, |
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], |
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outputs=output_message) |
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return demo |
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if __name__ == '__main__': |
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demo = create_upload_demo() |
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demo.queue(api_open=False, max_size=1).launch() |
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