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Create app.py

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  1. app.py +40 -0
app.py ADDED
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+ import gradio as gr
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+ from gradio_client import Client
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+
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+ def get_caption(image_in):
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+ client = Client("https://vikhyatk-moondream1.hf.space/")
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+ result = client.predict(
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+ image_in, # filepath in 'image' Image component
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+ "Describe precisely the image in one sentence.", # str in 'Question' Textbox component
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+ api_name="/answer_question"
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+ )
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+ print(result)
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+ return result
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+
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+ def get_clm(prompt):
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+ client = Client("https://fffiloni-lcm-lora-for-sdxl.hf.space/")
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+ result = client.predict(
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+ prompt, # str in 'parameter_5' Textbox component
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+ 0.3, # float (numeric value between 0.0 and 5) in 'Guidance' Slider component
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+ 8, # float (numeric value between 2 and 10) in 'Steps' Slider component
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+ 0, # float (numeric value between 0 and 12013012031030) in 'Seed' Slider component
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+ True, # bool in 'Randomize' Checkbox component
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+ api_name="/predict"
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+ )
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+ print(result)
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+ return result
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+
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+ def infer(image_in):
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+ caption = get_caption(image_in)
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+ img_var = get_lcm(caption)
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+ return img_var
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+
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+ gr.Interface(
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+ fn = infer,
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+ intputs = [
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+ gr.Image(type="filepath")
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+ ],
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+ outputs = [
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+ gr.Image()
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+ ]
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+ ).launch()