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Update app.py
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app.py
CHANGED
@@ -95,7 +95,7 @@ with gr.Blocks(title=TITLE) as demo:
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d = gr.Plot(label="Which ethnicities are present?")
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gr.Markdown(f"The 'Model makeup' plot corresponds to the number of images from the cluster that come from each of the TTI systems that we are comparing: Dall-E 2, Stable Diffusion v.1.4. and Stable Diffusion v.2.")
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gr.Markdown('The Gender plot shows the number of images based on the input prompts that used the words
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gr.Markdown(f"The 'Ethnicity label makeup' plot corresponds to the number of images from each of the 18 ethnicities used in the prompts. A blank value means unmarked ethnicity.")
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demo.load(fn=show_cluster, inputs=[cluster_id, num_clusters], outputs=[a, b, b_desc, c, c_desc, d, gallery])
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num_clusters.change(fn=show_cluster, inputs=[cluster_id, num_clusters], outputs=[a, b, b_desc, c, c_desc, d, gallery])
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d = gr.Plot(label="Which ethnicities are present?")
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gr.Markdown(f"The 'Model makeup' plot corresponds to the number of images from the cluster that come from each of the TTI systems that we are comparing: Dall-E 2, Stable Diffusion v.1.4. and Stable Diffusion v.2.")
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gr.Markdown('The Gender plot shows the number of images based on the input prompts that used the words man, woman, non-binary, and unmarked, which we label "person".')
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gr.Markdown(f"The 'Ethnicity label makeup' plot corresponds to the number of images from each of the 18 ethnicities used in the prompts. A blank value means unmarked ethnicity.")
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demo.load(fn=show_cluster, inputs=[cluster_id, num_clusters], outputs=[a, b, b_desc, c, c_desc, d, gallery])
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num_clusters.change(fn=show_cluster, inputs=[cluster_id, num_clusters], outputs=[a, b, b_desc, c, c_desc, d, gallery])
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