Spaces:
Running
on
Zero
Running
on
Zero
Commit
•
fbb3ef2
1
Parent(s):
62af647
Update app.py
Browse files
app.py
CHANGED
@@ -65,7 +65,7 @@ def load_captioning(uploaded_images, option):
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def check_removed_and_restart(images):
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visible = bool(images)
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return [gr.update(visible=visible) for _ in range(
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def make_options_visible(option):
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if (option == "object") or (option == "face"):
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@@ -440,6 +440,19 @@ def run_captioning(*inputs):
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final_captions[index] = final_caption
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yield final_captions
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with gr.Blocks() as demo:
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dataset_folder = gr.State()
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gr.Markdown("# SDXL LoRA Dreambooth Training")
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@@ -708,20 +721,28 @@ To improve the quality of your outputs, you can add a custom caption for each im
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local_rank = gr.Number(label="local_rank", value=-1)
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with gr.Row():
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with gr.Group():
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gr.Markdown('''### This training is estimated to cost <b
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- (For the training to your you need to have a credit card set up in your account, set it up [here](https://huggingface.co/settings/billing/payment))
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''')
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token = gr.Textbox(label="Your Hugging Face write token", info="A Hugging Face write token you can obtain on the settings page")
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with gr.Group() as no_payment_method:
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with gr.Row():
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gr.Markdown("Your Hugging Face account doesn't have a payment method.
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gr.Button("I have set up my payment method")
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start = gr.Button("Start training", visible=False)
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progress_area = gr.HTML("...")
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output_components.insert(1, advanced)
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output_components.insert(1, start)
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use_snr_gamma.change(
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lambda x: gr.update(visible=x),
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inputs=use_snr_gamma,
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@@ -767,7 +788,7 @@ To improve the quality of your outputs, you can add a custom caption for each im
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images.change(
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check_removed_and_restart,
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inputs=[images],
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outputs=[captioning_area, advanced
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)
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training_option.change(
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make_options_visible,
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def check_removed_and_restart(images):
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visible = bool(images)
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return [gr.update(visible=visible) for _ in range(2)]
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def make_options_visible(option):
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if (option == "object") or (option == "face"):
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final_captions[index] = final_caption
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yield final_captions
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def check_token(token):
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api = HfApi(token=token)
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user_data = api.whoami()
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if (username['auth']['accessToken']['role'] != "write"):
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gr.Warning("Oops, you've uploaded a `Read` token. We need a Write token!")
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else:
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if user_data['canPay']:
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return gr.update(visible=False), gr.update(visible=True)
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else:
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return gr.update(visible=True), gr.update(visible=False)
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return gr.update(visible=False), gr.update(visible=False)
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with gr.Blocks() as demo:
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dataset_folder = gr.State()
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gr.Markdown("# SDXL LoRA Dreambooth Training")
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local_rank = gr.Number(label="local_rank", value=-1)
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with gr.Row():
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with gr.Group():
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gr.Markdown('''### This training is estimated to cost <b>< US$ 1,50</b> with your current train settings
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Grab a Hugging Face <b>write</b> token [here](https://huggingface.co/settings/tokens)
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''')
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token = gr.Textbox(label="Your Hugging Face write token", info="A Hugging Face write token you can obtain on the settings page")
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with gr.Group() as no_payment_method:
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with gr.Row():
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gr.Markdown("Your Hugging Face account doesn't have a payment method. Set it up [here](https://huggingface.co/settings/billing/payment) to train your LoRA")
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payment_setup = gr.Button("I have set up my payment method")
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start = gr.Button("Start training", visible=False)
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progress_area = gr.HTML("...")
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output_components.insert(1, advanced)
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output_components.insert(1, start)
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gr.on(
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triggers=[
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token.change,
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payment_setup.click
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],
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fn=check_token,
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inputs=token,
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outputs=no_payment_method, start
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)
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use_snr_gamma.change(
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lambda x: gr.update(visible=x),
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inputs=use_snr_gamma,
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images.change(
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check_removed_and_restart,
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inputs=[images],
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outputs=[captioning_area, advanced],
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)
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training_option.change(
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make_options_visible,
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