sasha HF Staff commited on
Commit
fb1b078
·
1 Parent(s): c7632f4

Fixing labels and explainers

Browse files
Files changed (1) hide show
  1. app.py +5 -5
app.py CHANGED
@@ -73,17 +73,17 @@ with gr.Blocks(title=TITLE) as demo:
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  a = gr.Text(label="Number of images")
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  with gr.Row():
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  with gr.Column(scale=1):
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- c = gr.Plot(label="Model makeup of clssuster")
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  c_desc = gr.Text(label="")
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  with gr.Column(scale=1):
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- b = gr.Plot(label="Gender label makeup of cluster")
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  b_desc = gr.Text(label="")
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  with gr.Column(scale=2):
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- d = gr.Plot(label="Ethnicity label makeup of cluster")
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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(f"The 'Gender label makeup' plot corresponds to the number of images from each of the genders used in the prompts: male, female, non-binary and unmarked ('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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  cluster_id.change(fn=show_cluster, inputs=[cluster_id, num_clusters], outputs=[a, b, b_desc, c, c_desc, d, gallery])
 
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  a = gr.Text(label="Number of images")
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  with gr.Row():
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  with gr.Column(scale=1):
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+ c = gr.Plot(label="How many images in the cluster are from which models?")
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  c_desc = gr.Text(label="")
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  with gr.Column(scale=1):
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+ b = gr.Plot(label="How many genders are represented, based on the input prompts?")
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  b_desc = gr.Text(label="")
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  with gr.Column(scale=2):
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+ d = gr.Plot(label="Which ethnicities are present, based on the input prompts?")
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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 male, female, 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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  cluster_id.change(fn=show_cluster, inputs=[cluster_id, num_clusters], outputs=[a, b, b_desc, c, c_desc, d, gallery])