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from PIL import Image |
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import os,csv |
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import pandas as pd |
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import numpy as np |
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import gradio as gr |
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prompts=pd.read_csv('promptsadjectives.csv') |
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masc = prompts['Masc-adj'][:10].tolist() |
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fem = prompts['Fem-adj'][:10].tolist() |
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adjectives = sorted(masc+fem) |
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adjectives.insert(0, '') |
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occupations = prompts['Occupation-Noun'][:150].tolist() |
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def get_averages(adj, profession): |
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if adj != "": |
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prompt = (adj + ' ' + profession).replace(' ','_') |
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else: |
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prompt = profession.replace(' ','_') |
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sd14_average = 'facer_faces/SDv14/'+prompt+'.png' |
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if os.path.isfile(sd14_average) == False: |
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sd14_average = 'facer_faces/blank.png' |
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sdv2_average = 'facer_faces/SDv2/'+prompt+'.png' |
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if os.path.isfile(sdv2_average) == False: |
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sdv2_average = 'facer_faces/blank.png' |
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dalle_average = 'facer_faces/dalle2/'+prompt.lower()+'.png' |
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if os.path.isfile(dalle_average) == False: |
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dalle_average = 'facer_faces/blank.png' |
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return((Image.open(sd14_average), "Stable Diffusion v 1.4"), (Image.open(sdv2_average), "Stable Diffusion v 2"), (Image.open(dalle_average), "Dall-E 2")) |
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with gr.Blocks() as demo: |
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gr.Markdown("# Text-to-Image Diffusion Model Average Faces") |
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gr.Markdown("### We ran 150 professions and 20 adjectives through 3 text-to-image diffusion models to examine what they generate.") |
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gr.Markdown("#### Choose one of the professions and adjectives from the dropdown menus and see the average face generated by each model.") |
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with gr.Row(): |
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with gr.Column(): |
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adj = gr.Dropdown(sorted(adjectives, key=str.casefold), value = '',label = "Choose an adjective", interactive= True) |
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prof = gr.Dropdown(sorted(occupations, key=str.casefold), value = '', label = "Choose a profession", interactive= True) |
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btn = gr.Button("Get average faces!") |
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with gr.Column(): |
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gallery = gr.Gallery( |
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label="Average images", show_label=False, elem_id="gallery" |
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).style(grid=[0,3], height="auto") |
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gr.Markdown("The three models are: Stable Diffusion v.1.4, Stable Diffusion v.2, and Dall-E 2.") |
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gr.Markdown("If you see a black square above, we weren't able to compute an average face for this profession!") |
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btn.click(fn=get_averages, inputs=[adj,prof], outputs=gallery) |
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demo.launch() |
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