multimodalart HF staff commited on
Commit
ded3b8b
1 Parent(s): dd195c1

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +4 -2
app.py CHANGED
@@ -5,6 +5,7 @@ import argparse
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  import shutil
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  from train_dreambooth import run_training
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  from PIL import Image
 
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  css = '''
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  .instruction{position: absolute; top: 0;right: 0;margin-top: 0px !important}
@@ -64,7 +65,7 @@ def train(*inputs):
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  image = file.crop((left, top, right, bottom))
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  image = image.resize((512, 512))
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  extension = file_temp.name.split(".")[1]
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- image.convert('RGB')
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  image.save(f'instance_images/{prompt}_({j+1}).jpg', format="JPEG", quality = 100)
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  file_counter += 1
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@@ -159,6 +160,7 @@ def train(*inputs):
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  shutil.rmtree('instance_images')
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  shutil.make_archive("output_model", 'zip', "output_model")
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  shutil.rmtree("output_model")
 
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  return [gr.update(visible=True, value="output_model.zip"), gr.update(visible=True), gr.update(visible=True)]
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  with gr.Blocks(css=css) as demo:
@@ -251,6 +253,6 @@ with gr.Blocks(css=css) as demo:
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  gr.Markdown("Push to Hugging Face Hub")
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  model_repo_tag = gr.Textbox(label="Model name or URL", placeholder="username/model_name")
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  push_button = gr.Button("Push to the Hub")
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- result = gr.File(label="Download the uploaded models (zip file are diffusers weights, *.ckpt are CompVis/AUTOMATIC1111 weights)", visible=False)
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  train_btn.click(fn=train, inputs=is_visible+concept_collection+file_collection+[type_of_thing]+[steps]+[perc_txt_encoder]+[swap_auto_calculated], outputs=[result, try_your_model, push_to_hub])
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  demo.launch()
 
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  import shutil
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  from train_dreambooth import run_training
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  from PIL import Image
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+ import torch
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  css = '''
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  .instruction{position: absolute; top: 0;right: 0;margin-top: 0px !important}
 
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  image = file.crop((left, top, right, bottom))
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  image = image.resize((512, 512))
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  extension = file_temp.name.split(".")[1]
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+ image = image.convert('RGB')
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  image.save(f'instance_images/{prompt}_({j+1}).jpg', format="JPEG", quality = 100)
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  file_counter += 1
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  shutil.rmtree('instance_images')
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  shutil.make_archive("output_model", 'zip', "output_model")
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  shutil.rmtree("output_model")
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+ torch.cuda.empty_cache()
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  return [gr.update(visible=True, value="output_model.zip"), gr.update(visible=True), gr.update(visible=True)]
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  with gr.Blocks(css=css) as demo:
 
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  gr.Markdown("Push to Hugging Face Hub")
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  model_repo_tag = gr.Textbox(label="Model name or URL", placeholder="username/model_name")
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  push_button = gr.Button("Push to the Hub")
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+ result = gr.File(label="Download the uploaded models (zip file are diffusers weights, *.ckpt are CompVis/AUTOMATIC1111 weights)", visible=True)
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  train_btn.click(fn=train, inputs=is_visible+concept_collection+file_collection+[type_of_thing]+[steps]+[perc_txt_encoder]+[swap_auto_calculated], outputs=[result, try_your_model, push_to_hub])
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  demo.launch()