Merge branch 'main' of https://huggingface.co/spaces/sasha/StableDiffusionBiasExplorer into main

app.py

@@ -1,39 +1,51 @@
 import gradio as gr
 import random, os
 from PIL import Image
+import pandas as pd
 
-def open_ims(choice):
-    dirname='images/'+choice.replace(' ','_')+'/Seed_'+ str(seed_choice)+'/'
+def open_ims(adj, group):
+    if adj != '':
+        if adj[0] in vowels:
+            dirname='images/'+'Photo_portrait_of_an_'+ adj+'_'+ group.replace(' ','_')+'/Seed_'+ str(seed_choice)+'/'
+        else:
+            dirname='images/'+'Photo_portrait_of_a_'+ adj+ '_'+ group.replace(' ','_')+'/Seed_'+ str(seed_choice)+'/'
+    else:
+        if group[0] in vowels:
+            dirname='images/'+'Photo_portrait_of_an_'+ group.replace(' ','_')+'/Seed_'+ str(seed_choice)+'/'
+        else:
+            dirname='images/'+'Photo_portrait_of_a_'+ group.replace(' ','_')+'/Seed_'+ str(seed_choice)+'/'
     imnames= os.listdir(dirname)
     images = [(Image.open(dirname+name)) for name in imnames]
     return images[:9]
 
-def random_image():
-    cat = random.choice(categories)
-    dirname = 'images/'+cat.replace(' ','_')+'/Seed_'+str(seed_choice)+'/'
-    imnames = os.listdir(dirname)
-    images = [(Image.open(dirname+name)) for name in imnames]
-    return images[:9]
 
-categories=os.listdir('images/')
-categories = [c.replace('_',' ') for c in categories]
+vowels = ["a","e","i","o","u"]
+prompts = pd.read_csv('shortprompts.csv')
+
 seeds = [46267, 48040, 51237, 54325, 60884, 64830, 67031, 72935, 92118, 93109]
 
+#adjectives = prompts['Descriptive-Adj'].tolist()[:10]
+adjectives = ['attractive','strong']
+adjectives.append('')
+professions = [p.lower() for p in prompts['Occupation-Noun'].tolist()]
+
 with gr.Blocks() as demo:
     gr.Markdown("# Stable Diffusion Explorer")
-    gr.Markdown("## Choose from the prompts below to explore the way in which the Stable Diffusion model encodes societal biases")
+    gr.Markdown("## Choose from the prompts below to explore how the Stable Diffusion model represents different professions")
     seed_choice = gr.State(0)
     seed_choice = random.choice(seeds)
     print("Seed choice is: " + str(seed_choice))
     with gr.Row():
         with gr.Column():
-            choice1 = gr.Dropdown(categories, label = "Choose a first category", 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)
             images1 = gr.Gallery(label="Images").style(grid=[3], height="auto")
         with gr.Column():
-            choice2 = gr.Dropdown(categories, label = "Choose a second category", 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)
             images2 = gr.Gallery(label="Images").style(grid=[3], height="auto")
 
     #demo.load(random_image, None, [images])
-    choice1.change(open_ims, [choice1], [images1])
-    choice2.change(open_ims, [choice2], [images2])
+    choice1.change(open_ims, [adj1,choice1], [images1])
+    choice2.change(open_ims, [adj2,choice2], [images2])
 demo.launch()