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Create app.py
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app.py
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import gradio as gr
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from gradio_client import Client
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fuse_client = Client("https://noamrot-fusecap-image-captioning.hf.space/")
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clipi_client = Client("https://fffiloni-clip-interrogator-2.hf.space/")
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def compare(image):
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ci_cap = clipi_client.predict(
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image, # str (filepath or URL to image) in 'parameter_3' Image component
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"best", # str in 'Select mode' Radio component
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2, # int | float (numeric value between 2 and 24) in 'best mode max flavors' Slider component
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api_name="/clipi2"
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)
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fuse_cap = fuse_client.predict(
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image, # str representing input in 'raw_image' Image component
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api_name="/predict"
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)
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coca_cap = "comming soon..."
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return ci_cap, coca_cap, fuse_cap
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with gr.Blocks() as demo:
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with gr.Column():
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gr.Markdown("""
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# Caption compare
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""")
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with gr.Row():
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with gr.Column():
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image_in = gr.Image(label="Image to caption", type="filepath")
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submit_btn = gr.Button("Compare !")
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with gr.Column():
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clip_int_out = gr.Textbox(label="Clip Interrogator")
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coca_out = gr.Textbox(label="CoCa")
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fuse_out = gr.Textbox(label="Fuse Cap")
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submit_btn.click(
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fn = compare,
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inputs = [
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image_in
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],
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outputs = [
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clip_int_out,
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coca_out,
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fuse_out
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]
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)
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demo.queue().launch()
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