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| import gradio as gr | |
| import random, os, shutil | |
| from PIL import Image | |
| import pandas as pd | |
| import tempfile | |
| def open_sd_ims(adj, group, seed): | |
| if group != '': | |
| if adj != '': | |
| prompt=adj+'_'+group.replace(' ','_') | |
| if os.path.isdir(prompt) == False: | |
| shutil.unpack_archive('zipped_images/stablediffusion/'+ prompt.replace(' ', '_') +'.zip', prompt, 'zip') | |
| else: | |
| prompt=group | |
| if os.path.isdir(prompt) == False: | |
| shutil.unpack_archive('zipped_images/stablediffusion/'+ prompt.replace(' ', '_') +'.zip', prompt, 'zip') | |
| imnames= os.listdir(prompt+'/Seed_'+ str(seed)+'/') | |
| images = [(Image.open(prompt+'/Seed_'+ str(seed)+'/'+name)) for name in imnames] | |
| return images[:9] | |
| def open_ims(model, adj, group): | |
| seed = 48040 | |
| with tempfile.TemporaryDirectory() as tmpdirname: | |
| print('created temporary directory', tmpdirname) | |
| if model == "Dall-E 2": | |
| if group != '': | |
| if adj != '': | |
| prompt=adj+'_'+group.replace(' ','_') | |
| if os.path.isdir(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt) == False: | |
| shutil.unpack_archive('zipped_images/'+ model.replace(' ','').lower()+ '/'+ prompt.replace(' ', '_') +'.zip', tmpdirname+ '/'+ model.replace(' ','').lower()+ '/'+ prompt, 'zip') | |
| else: | |
| prompt=group | |
| if os.path.isdir(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt) == False: | |
| shutil.unpack_archive('zipped_images/' + model.replace(' ','').lower() + '/'+ prompt.replace(' ', '_') +'.zip', tmpdirname + '/' + model.replace(' ','').lower()+ '/' + prompt, 'zip') | |
| imnames= os.listdir(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt+'/') | |
| images = [(Image.open(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt+'/'+name)).convert("RGB") for name in imnames] | |
| return images[:9] | |
| else: | |
| if group != '': | |
| if adj != '': | |
| prompt=adj+'_'+group.replace(' ','_') | |
| if os.path.isdir(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt) == False: | |
| shutil.unpack_archive('zipped_images/'+ model.replace(' ','').lower()+ '/'+ prompt.replace(' ', '_') +'.zip', tmpdirname + '/' +model.replace(' ','').lower()+ '/'+ prompt, 'zip') | |
| else: | |
| prompt=group | |
| if os.path.isdir(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt) == False: | |
| shutil.unpack_archive('zipped_images/' + model.replace(' ','').lower() + '/'+ prompt.replace(' ', '_') +'.zip', tmpdirname + '/' + model.replace(' ','').lower()+'/'+ prompt, 'zip') | |
| imnames= os.listdir(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt+'/'+'Seed_'+ str(seed)+'/') | |
| images = [(Image.open(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt +'/'+'Seed_'+ str(seed)+'/'+name)) for name in imnames] | |
| return images[:9] | |
| vowels = ["a","e","i","o","u"] | |
| prompts = pd.read_csv('promptsadjectives.csv') | |
| seeds = [46267, 48040, 51237, 54325, 60884, 64830, 67031, 72935, 92118, 93109] | |
| m_adjectives = prompts['Masc-adj'].tolist()[:10] | |
| f_adjectives = prompts['Fem-adj'].tolist()[:10] | |
| adjectives = sorted(m_adjectives+f_adjectives) | |
| #adjectives = ['attractive','strong'] | |
| adjectives.insert(0, '') | |
| professions = sorted([p.lower() for p in prompts['Occupation-Noun'].tolist()]) | |
| models = ["Stable Diffusion 1.4", "Dall-E 2","Stable Diffusion 2"] | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# Diffusion Bias Explorer") | |
| gr.Markdown("## Choose from the prompts below to explore how the text-to-image models like [Stable Diffusion v1.4](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original), [Stable Diffion v.2](https://huggingface.co/stabilityai/stable-diffusion-2) and [DALLE-2](https://openai.com/dall-e-2/) represent different professions and adjectives") | |
| # gr.Markdown("Some of the images for Dall-E 2 are missing -- we are still in the process of generating them! If you get an 'error', please pick another prompt.") | |
| # seed_choice = gr.State(0) | |
| # seed_choice = 93109 | |
| # print("Seed choice is: " + str(seed_choice)) | |
| with gr.Row(): | |
| with gr.Column(): | |
| model1 = gr.Dropdown(models, label = "Choose a model to compare results", value = models[0], interactive=True) | |
| adj1 = gr.Dropdown(adjectives, label = "Choose a first adjective (or leave this blank!)", interactive=True) | |
| choice1 = gr.Dropdown(professions, label = "Choose a first group", interactive=True) | |
| # seed1= gr.Dropdown(seeds, label = "Choose a random seed to compare results", value = seeds[1], interactive=True) | |
| images1 = gr.Gallery(label="Images").style(grid=[3], height="auto") | |
| with gr.Column(): | |
| model2 = gr.Dropdown(models, label = "Choose a model to compare results", value = models[0], interactive=True) | |
| adj2 = gr.Dropdown(adjectives, label = "Choose a second adjective (or leave this blank!)", interactive=True) | |
| choice2 = gr.Dropdown(professions, label = "Choose a second group", interactive=True) | |
| # seed2= gr.Dropdown(seeds, label = "Choose a random seed to compare results", value= seeds[1], interactive=True) | |
| images2 = gr.Gallery(label="Images").style(grid=[3], height="auto") | |
| gr.Markdown("### [Research](http://gender-decoder.katmatfield.com/static/documents/Gaucher-Friesen-Kay-JPSP-Gendered-Wording-in-Job-ads.pdf) has shown that \ | |
| certain words are considered more masculine- or feminine-coded based on how appealing job descriptions containing these words \ | |
| seemed to male and female research participants and to what extent the participants felt that they 'belonged' in that occupation.") | |
| #demo.load(random_image, None, [images]) | |
| choice1.change(open_ims, [model1, adj1,choice1], [images1]) | |
| choice2.change(open_ims, [model2, adj2,choice2], [images2]) | |
| adj1.change(open_ims, [model1, adj1, choice1], [images1]) | |
| adj2.change(open_ims, [model2, adj2, choice2], [images2]) | |
| # seed1.change(open_ims, [adj1,choice1,seed1], [images1]) | |
| # seed2.change(open_ims, [adj2,choice2,seed2], [images2]) | |
| demo.launch() | |