Spaces:
Runtime error
Runtime error
Add an additional tab for inference with url.
Browse files
app.py
CHANGED
|
@@ -107,17 +107,35 @@ for idx_example, example in enumerate(examples):
|
|
| 107 |
examples.append(examples[-1].copy())
|
| 108 |
examples[-1][1] = '512x512'
|
| 109 |
|
| 110 |
-
|
| 111 |
fn=predict,
|
| 112 |
inputs=[
|
| 113 |
-
'image',
|
| 114 |
gr.Textbox(lines=1, placeholder="Type the resolution (`WxH`) you want, e.g., `1024x1024`. Higher resolutions can be much slower for inference.", label="Resolution"),
|
| 115 |
gr.Radio(list(usage_to_weights_file.keys()), value='General', label="Weights", info="Choose the weights you want.")
|
| 116 |
],
|
| 117 |
-
outputs=ImageSlider(),
|
| 118 |
examples=examples,
|
| 119 |
-
|
| 120 |
-
description=('Upload a picture, our model will extract a highly accurate segmentation of the subject in it. :)'
|
| 121 |
-
'\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.')
|
| 122 |
)
|
| 123 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 107 |
examples.append(examples[-1].copy())
|
| 108 |
examples[-1][1] = '512x512'
|
| 109 |
|
| 110 |
+
tab_image = gr.Interface(
|
| 111 |
fn=predict,
|
| 112 |
inputs=[
|
| 113 |
+
gr.Image(label='Upload an image'),
|
| 114 |
gr.Textbox(lines=1, placeholder="Type the resolution (`WxH`) you want, e.g., `1024x1024`. Higher resolutions can be much slower for inference.", label="Resolution"),
|
| 115 |
gr.Radio(list(usage_to_weights_file.keys()), value='General', label="Weights", info="Choose the weights you want.")
|
| 116 |
],
|
| 117 |
+
outputs=ImageSlider(label="BiRefNet's prediction", type="pil"),
|
| 118 |
examples=examples,
|
| 119 |
+
api_name="image"
|
|
|
|
|
|
|
| 120 |
)
|
| 121 |
+
|
| 122 |
+
tab_text = gr.Interface(
|
| 123 |
+
fn=predict,
|
| 124 |
+
inputs=gr.Textbox(label="Paste an image URL"),
|
| 125 |
+
outputs=ImageSlider(label="BiRefNet's prediction", type="pil"),
|
| 126 |
+
examples=["https://hips.hearstapps.com/hmg-prod/images/gettyimages-1229892983-square.jpg"],
|
| 127 |
+
api_name="text"
|
| 128 |
+
)
|
| 129 |
+
|
| 130 |
+
demo = gr.TabbedInterface(
|
| 131 |
+
[tab_image, tab_text],
|
| 132 |
+
["image", "text"],
|
| 133 |
+
title="BiRefNet demo for subject extraction (general / salient / camouflaged / portrait)."
|
| 134 |
+
description=('Upload a picture, our model will extract a highly accurate segmentation of the subject in it.\n)'
|
| 135 |
+
' The resolution used in our training was `1024x1024`, thus the suggested resolution to obtain good results!\n'
|
| 136 |
+
' Our codes can be found at https://github.com/ZhengPeng7/BiRefNet.\n'
|
| 137 |
+
' We also maintain the HF model of BiRefNet at https://huggingface.co/ZhengPeng7/BiRefNet for easier access.')
|
| 138 |
+
)
|
| 139 |
+
|
| 140 |
+
if __name__ == "__main__":
|
| 141 |
+
demo.launch(debug=True)
|