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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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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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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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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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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()
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