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		Runtime error
		
	Update app.py
Browse files
    	
        app.py
    CHANGED
    
    | @@ -1,4 +1,5 @@ | |
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            import os, subprocess
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            def setup():
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| @@ -44,20 +45,21 @@ ci = Interrogator(config) | |
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            def inference(image, mode, best_max_flavors):
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                image = image.convert('RGB')
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                if mode == 'best':
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                    return ci.interrogate(image, max_flavors=int(best_max_flavors))
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                elif mode == 'classic':
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                    return ci.interrogate_classic(image)
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                else:
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                    return ci.interrogate_fast(image)
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            title = """
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                <div style="text-align: center; max-width:  | 
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                    <div
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                    style="
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                        display: inline-flex;
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                        align-items: center;
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                        gap: 0.8rem;
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                        font-size: 1.75rem;
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                    "
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                    >
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                    <h1 style="font-weight: 600; margin-bottom: 7px;">
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| @@ -65,14 +67,15 @@ title = """ | |
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                    </h1>
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                    </div>
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                    <p style="margin-bottom: 10px;font-size: 16px;font-weight: 100;line-height: 1.5em;">
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                    Want to figure out what a good prompt might be to create new images like an existing one?  | 
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                    <br />This version is specialized for producing nice prompts for use with Stable Diffusion 2.0 using the ViT-H-14 OpenCLIP model!
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                    </p>
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                </div>
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            """
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            article = """
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            <div style="text-align: center; max-width:  | 
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                <p>
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                Server busy? You can also run on <a href="https://colab.research.google.com/github/pharmapsychotic/clip-interrogator/blob/open-clip/clip_interrogator.ipynb">Google Colab</a>
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| @@ -125,11 +128,19 @@ with gr.Blocks(css=css) as block: | |
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                    input_image = gr.Image(type='pil', elem_id="input-img")
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                    mode_input = gr.Radio(['best', 'classic', 'fast'], label='', value='best')
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                    flavor_input = gr.Number(value=4, label='best mode max flavors')
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                    submit_btn = gr.Button("Submit")
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                    output_text = gr.Textbox(label="Output", elem_id="output-txt")
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                    gr.HTML(article)
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                submit_btn.click(fn=inference, inputs=[input_image,mode_input,flavor_input], outputs=[output_text])
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            block.queue(max_size=32).launch(show_api=False)
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            +
            from share_btn import community_icon_html, loading_icon_html, share_js
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            import os, subprocess
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            def setup():
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            def inference(image, mode, best_max_flavors):
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                image = image.convert('RGB')
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                if mode == 'best':
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                    return ci.interrogate(image, max_flavors=int(best_max_flavors)), gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
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                elif mode == 'classic':
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                    return ci.interrogate_classic(image), gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
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                else:
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                    return ci.interrogate_fast(image), gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
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            title = """
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            +
                <div style="text-align: center; max-width: 500px; margin: 0 auto;">
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                    <div
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                    style="
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                        display: inline-flex;
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                        align-items: center;
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                        gap: 0.8rem;
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                        font-size: 1.75rem;
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            +
                        margin-bottom: 10px;
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                    "
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                    >
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                    <h1 style="font-weight: 600; margin-bottom: 7px;">
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                    </h1>
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                    </div>
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                    <p style="margin-bottom: 10px;font-size: 16px;font-weight: 100;line-height: 1.5em;">
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| 70 | 
            +
                    Want to figure out what a good prompt might be to create new images like an existing one? 
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| 71 | 
            +
                    <br />The CLIP Interrogator is here to get you answers!
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                    <br />This version is specialized for producing nice prompts for use with Stable Diffusion 2.0 using the ViT-H-14 OpenCLIP model!
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                    </p>
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                </div>
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            """
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            article = """
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            +
            <div style="text-align: center; max-width: 500px; margin: 0 auto;font-size: 94%;">
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                <p>
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                Server busy? You can also run on <a href="https://colab.research.google.com/github/pharmapsychotic/clip-interrogator/blob/open-clip/clip_interrogator.ipynb">Google Colab</a>
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                    input_image = gr.Image(type='pil', elem_id="input-img")
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                    mode_input = gr.Radio(['best', 'classic', 'fast'], label='', value='best')
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                    flavor_input = gr.Number(value=4, label='best mode max flavors')
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            +
                    
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                    submit_btn = gr.Button("Submit")
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                    output_text = gr.Textbox(label="Output", elem_id="output-txt")
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                    with gr.Group(elem_id="share-btn-container"):
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                        community_icon = gr.HTML(community_icon_html, visible=False)
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                        loading_icon = gr.HTML(loading_icon_html, visible=False)
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                        share_button = gr.Button("Share to community", elem_id="share-btn", visible=False)
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                    gr.HTML(article)
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                submit_btn.click(fn=inference, inputs=[input_image,mode_input,flavor_input], outputs=[output_text, share_button, community_icon, loading_icon])
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            +
                share_button.click(None, [], [], _js=share_js)
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            +
                
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            block.queue(max_size=32).launch(show_api=False)
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