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Update app.py
Browse files
app.py
CHANGED
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@@ -11,10 +11,10 @@ def clear_all(image1, image2, output_image, output_json):
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with gr.Blocks(css="app.css") as demo:
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gr.Markdown("Choose or upload a dog image and press cpmpare!! the system will retutn the 2 detected faces with the recognition result")
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with gr.Row(equal_height=True, scale=2):
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with gr.Column(scale=1, min_width=
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image1_input = gr.Image(type="pil", label="Image 1",width=200,height=200)
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examples_image1 = gr.Examples(examples=["./dob1.jpg", "./p1.jpg", "./dob3.jpg", "./d1.jpg"], inputs=image1_input)
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with gr.Column(scale=1, min_width=
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image2_input = gr.Image(type="pil", label="Image 2",width=200,height=200)
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examples_image2 = gr.Examples(examples=["./dob2.jpg", "./p2.jpg", "./dob4.jpg", "./d2.jpg"], inputs=image2_input)
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threshold_input = gr.Slider(minimum=0.0, maximum=1.0, value=0.55, step=0.05, label="Threshold")
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with gr.Blocks(css="app.css") as demo:
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gr.Markdown("Choose or upload a dog image and press cpmpare!! the system will retutn the 2 detected faces with the recognition result")
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with gr.Row(equal_height=True, scale=2):
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with gr.Column(scale=1, min_width=200):
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image1_input = gr.Image(type="pil", label="Image 1",width=200,height=200)
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examples_image1 = gr.Examples(examples=["./dob1.jpg", "./p1.jpg", "./dob3.jpg", "./d1.jpg"], inputs=image1_input)
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with gr.Column(scale=1, min_width=200):
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image2_input = gr.Image(type="pil", label="Image 2",width=200,height=200)
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examples_image2 = gr.Examples(examples=["./dob2.jpg", "./p2.jpg", "./dob4.jpg", "./d2.jpg"], inputs=image2_input)
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threshold_input = gr.Slider(minimum=0.0, maximum=1.0, value=0.55, step=0.05, label="Threshold")
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