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Update app.py
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app.py
CHANGED
@@ -17,11 +17,11 @@ def generate(slider_x, slider_y, prompt, iterations, steps,
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# check if avg diff for directions need to be re-calculated
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if not sorted(slider_x) == sorted([x_concept_1, x_concept_2]):
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avg_diff = clip_slider.find_latent_direction(slider_x[0], slider_x[1],
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x_concept_1, x_concept_2 = slider_x[0], slider_x[1]
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if not sorted(slider_y) == sorted([y_concept_1, y_concept_2]):
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avg_diff_2nd = clip_slider.find_latent_direction(slider_y[0], slider_y[1],
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y_concept_1, y_concept_2 = slider_y[0], slider_y[1]
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image = clip_slider.generate(prompt, scale=0, scale_2nd=0, num_inference_steps=steps, avg_diff=avg_diff, avg_diff_2nd=avg_diff_2nd)
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@@ -95,7 +95,8 @@ with gr.Blocks(css=css) as demo:
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x = gr.Slider(minimum=-10, value=0, maximum=10, elem_id="x", interactive=False)
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y = gr.Slider(minimum=-10, value=0, maximum=10, elem_id="y", interactive=False)
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output_image = gr.Image(elem_id="image_out")
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iterations = gr.Slider(label = "num iterations", minimum=0, value=100, maximum=300)
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steps = gr.Slider(label = "num inference steps", minimum=1, value=8, maximum=30)
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# check if avg diff for directions need to be re-calculated
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if not sorted(slider_x) == sorted([x_concept_1, x_concept_2]):
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avg_diff = clip_slider.find_latent_direction(slider_x[0], slider_x[1], num_iterations=iterations)
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x_concept_1, x_concept_2 = slider_x[0], slider_x[1]
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if not sorted(slider_y) == sorted([y_concept_1, y_concept_2]):
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avg_diff_2nd = clip_slider.find_latent_direction(slider_y[0], slider_y[1], num_iterations=iterations)
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y_concept_1, y_concept_2 = slider_y[0], slider_y[1]
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image = clip_slider.generate(prompt, scale=0, scale_2nd=0, num_inference_steps=steps, avg_diff=avg_diff, avg_diff_2nd=avg_diff_2nd)
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x = gr.Slider(minimum=-10, value=0, maximum=10, elem_id="x", interactive=False)
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y = gr.Slider(minimum=-10, value=0, maximum=10, elem_id="y", interactive=False)
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output_image = gr.Image(elem_id="image_out")
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with gr.Accordion(label="advanced options", open=False):
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iterations = gr.Slider(label = "num iterations", minimum=0, value=100, maximum=300)
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steps = gr.Slider(label = "num inference steps", minimum=1, value=8, maximum=30)
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