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app.py
CHANGED
@@ -249,6 +249,8 @@ def generate_matching_superfeatures(
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# bbox = legend.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
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return fig1, fig2, fig_leg
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# ','.join(map(str, sf_idx_))
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@@ -261,10 +263,10 @@ article = "<p style='text-align: center'><a href='https://github.com/naver/fire'
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iface = gr.Interface(
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fn=generate_matching_superfeatures,
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inputs=[
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gr.inputs.Image(type="pil", label="First Image"),
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gr.inputs.Image(type="pil", label="Second Image"),
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gr.inputs.Checkbox(default=False, label="Model trained on ImageNet (Default: SfM-120k)"),
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gr.inputs.Slider(minimum=0, maximum=6, step=1, default=4, label="Scale"),
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gr.inputs.Slider(minimum=0, maximum=255, step=25, default=50, label="Binarization Threshold"),
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# bbox = legend.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
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im1 = None
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im2 = None
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return fig1, fig2, fig_leg
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# ','.join(map(str, sf_idx_))
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iface = gr.Interface(
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fn=generate_matching_superfeatures,
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inputs=[
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gr.inputs.Image(shape=(1024, 1024), type="pil", label="First Image"),
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gr.inputs.Image(shape=(1024, 1024), type="pil", label="Second Image"),
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# gr.inputs.Image(type="pil", label="First Image"),
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# gr.inputs.Image(type="pil", label="Second Image"),
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gr.inputs.Checkbox(default=False, label="Model trained on ImageNet (Default: SfM-120k)"),
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gr.inputs.Slider(minimum=0, maximum=6, step=1, default=4, label="Scale"),
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gr.inputs.Slider(minimum=0, maximum=255, step=25, default=50, label="Binarization Threshold"),
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