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import gradio as gr |
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import numpy as np |
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def inference(image): |
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img1 = np.array(np.random.rand(240,240)) |
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img2 = np.array(np.random.rand(240,240)) |
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img3 = np.array(np.random.rand(240,240)) |
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parts_list_damage = 'test' |
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return img1, img2, img3, parts_list_damage |
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with gr.Blocks() as demo: |
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with gr.Row(): |
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with gr.Column(): |
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gr.Markdown("## Inputs") |
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image = gr.Image(type="pil",label="Input") |
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submit_button = gr.Button(value="Submit", label="Submit") |
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with gr.Column(): |
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gr.Markdown("## Outputs") |
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with gr.Tab('Image of damages'): |
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im1 = gr.Image(type='numpy',label='Image of damages') |
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with gr.Tab('Image of scratches'): |
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im2 = gr.Image(type='numpy',label='Image of scratches') |
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with gr.Tab('Image of parts'): |
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im3 = gr.Image(type='numpy',label='Image of car parts') |
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with gr.Tab('Information about damaged parts'): |
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intersections = gr.Textbox(label='Information about type of damages on each part') |
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submit_button.click( |
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fn=inference, |
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inputs = [image], |
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outputs = [im1,im2,im3,intersections] |
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) |
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if __name__ == "__main__": |
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demo.launch() |
