ZhengPeng7 commited on
Commit
1acca69
1 Parent(s): 4420101

Add an additional tab for inference with url.

Browse files
Files changed (1) hide show
  1. app.py +25 -7
app.py CHANGED
@@ -107,17 +107,35 @@ for idx_example, example in enumerate(examples):
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  examples.append(examples[-1].copy())
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  examples[-1][1] = '512x512'
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- 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., `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)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  examples.append(examples[-1].copy())
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  examples[-1][1] = '512x512'
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+ tab_image = gr.Interface(
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  fn=predict,
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  inputs=[
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+ gr.Image(label='Upload an 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(label="BiRefNet's prediction", type="pil"),
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  examples=examples,
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+ api_name="image"
 
 
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  )
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+
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+ tab_text = gr.Interface(
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+ fn=predict,
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+ inputs=gr.Textbox(label="Paste an image URL"),
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+ outputs=ImageSlider(label="BiRefNet's prediction", type="pil"),
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+ examples=["https://hips.hearstapps.com/hmg-prod/images/gettyimages-1229892983-square.jpg"],
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+ api_name="text"
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+ )
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+
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+ demo = gr.TabbedInterface(
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+ [tab_image, tab_text],
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+ ["image", "text"],
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+ title="BiRefNet demo for subject extraction (general / salient / camouflaged / portrait)."
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+ description=('Upload a picture, our model will extract a highly accurate segmentation of the subject in it.\n)'
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+ ' The resolution used in our training was `1024x1024`, thus the suggested resolution to obtain good results!\n'
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+ ' Our codes can be found at https://github.com/ZhengPeng7/BiRefNet.\n'
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+ ' 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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+
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+ if __name__ == "__main__":
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+ demo.launch(debug=True)