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app.py
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import gradio as gr
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import utils
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# Araclip demo
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with gr.Blocks() as demo_araclip:
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gr.Markdown("## Input parameters")
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txt = gr.Textbox(label="Text Query (Caption)")
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num = gr.Slider(label="Number of retrieved image", value=1, minimum=1, maximum=1000)
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with gr.Row():
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btn = gr.Button("Retrieve images", scale=1)
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gr.Markdown("## Retrieved Images")
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gallery = gr.Gallery(
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label="Generated images", show_label=True, elem_id="gallery"
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, columns=[5], rows=[1], object_fit="contain", height="auto")
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with gr.Row():
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lables = gr.Label(label="Text image similarity")
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with gr.Row():
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with gr.Column(scale=1):
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gr.Markdown("<div style='text-align: center; font-size: 24px; font-weight: bold;'>Data Retrieved based on Images Similarity</div>")
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json_output = gr.JSON()
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with gr.Column(scale=1):
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# gr.Markdown("### Data Retrieved based on Text similarity")
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# gr.Markdown("<div style='text-align: center;'> Data Retrieved based on Text similarity </div>")
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gr.Markdown("<div style='text-align: center; font-size: 24px; font-weight: bold;'>Data Retrieved based on Text similarity</div>")
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json_text = gr.JSON()
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btn.click(utils.predict, inputs=[txt, num], outputs=[gallery,lables, json_output, json_text])
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gr.Examples(
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examples=[["تخطي لاعب فريق بيتسبرج بايرتس منطقة اللوحة الرئيسية في مباراة بدوري البيسبول", 5],
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["وقوف قطة بمخالبها على فأرة حاسوب على المكتب", 10],
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["صحن به شوربة صينية بالخضار، وإلى جانبه بطاطس مقلية وزجاجة ماء", 7]],
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inputs=[txt, num],
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outputs=[gallery,lables, json_output, json_text],
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fn=utils.predict,
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cache_examples=False,
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)
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# mclip demo
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with gr.Blocks() as demo_mclip:
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gr.Markdown("## Input parameters")
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txt = gr.Textbox(label="Text Query (Caption)")
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num = gr.Slider(label="Number of retrieved image", value=1, minimum=1, maximum=1000)
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with gr.Row():
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btn = gr.Button("Retrieve images", scale=1)
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gr.Markdown("## Retrieved Images")
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gallery = gr.Gallery(
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label="Generated images", show_label=True, elem_id="gallery_mclip"
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, columns=[5], rows=[1], object_fit="contain", height="auto")
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lables = gr.Label()
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with gr.Row():
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with gr.Column(scale=1):
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gr.Markdown("## Images Retrieved")
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json_output = gr.JSON()
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with gr.Column(scale=1):
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gr.Markdown("## Text Retrieved")
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json_text = gr.JSON()
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btn.click(utils.predict_mclip, inputs=[txt, num], outputs=[gallery,lables, json_output, json_text])
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gr.Examples(
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examples=[["تخطي لاعب فريق بيتسبرج بايرتس منطقة اللوحة الرئيسية في مباراة بدوري البيسبول", 5],
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["وقوف قطة بمخالبها على فأرة حاسوب على المكتب", 10],
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["صحن به شوربة صينية بالخضار، وإلى جانبه بطاطس مقلية وزجاجة ماء", 7]],
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inputs=[txt, num],
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outputs=[gallery,lables, json_output, json_text],
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fn=utils.predict_mclip,
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cache_examples=False,
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)
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# Group the demos in a TabbedInterface
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with gr.Blocks() as demo:
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gr.Markdown("<font color=red size=10><center>AraClip: Arabic Image Retrieval Application</center></font>")
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gr.TabbedInterface([demo_araclip, demo_mclip], ["Our Model", "Mclip model"])
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if __name__ == "__main__":
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demo.launch()
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