ZhengPeng7 commited on
Commit
8000135
·
verified ·
1 Parent(s): 8ed67a5

Update descriptions in the app head.

Browse files
Files changed (1) hide show
  1. app.py +2 -2
app.py CHANGED
@@ -108,13 +108,13 @@ demo = gr.Interface(
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  fn=predict,
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  inputs=[
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  'image',
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- gr.Textbox(lines=1, placeholder="Type the resolution (`WxH`) you want, e.g., `512x512`. Higher resolutions can be much slower for inference.", label="Resolution"),
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  gr.Radio(list(usage_to_weights_file.keys()), value='General', label="Weights", info="Choose the weights you want.")
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  ],
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  outputs=ImageSlider(),
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  examples=examples,
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  title='Online demo for `Bilateral Reference for High-Resolution Dichotomous Image Segmentation`',
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  description=('Upload a picture, our model will extract a highly accurate segmentation of the subject in it. :)'
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- '\nThe resolution used in our training was `1024x1024`, which is thus the suggested resolution to obtain good results!\n Ours codes can be found at https://github.com/ZhengPeng7/BiRefNet.\n We also maintain the HF model of BiRefNet at https://huggingface.co/ZhengPeng7/birefnet for easier access.')
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  )
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  demo.launch(debug=True)
 
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  fn=predict,
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  inputs=[
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  'image',
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+ gr.Textbox(lines=1, placeholder="Type the resolution (`WxH`) you want, e.g., `1024x1024`. Higher resolutions can be much slower for inference.", label="Resolution"),
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  gr.Radio(list(usage_to_weights_file.keys()), value='General', label="Weights", info="Choose the weights you want.")
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  ],
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  outputs=ImageSlider(),
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  examples=examples,
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  title='Online demo for `Bilateral Reference for High-Resolution Dichotomous Image Segmentation`',
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  description=('Upload a picture, our model will extract a highly accurate segmentation of the subject in it. :)'
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+ '\nThe resolution used in our training was `1024x1024`, thus the suggested resolution to obtain good results!\n Ours codes can be found at https://github.com/ZhengPeng7/BiRefNet.\n We also maintain the HF model of BiRefNet at https://huggingface.co/ZhengPeng7/BiRefNet for easier access.')
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  )
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  demo.launch(debug=True)