adding stuff

app.py

@@ -2,9 +2,11 @@ import gradio as gr
 from PIL import Image
 import os
 
-def get_identity_images(path="images/identities"):
-    ims = Image.open([os.path.join(path,im) for im in os.listdir(path)])
-    return ims
+def get_images(path):
+    images = [Image.open(os.path.join(path,im)) for im in os.listdir(path)]
+    paths = os.listdir(path)
+    return([(im, path) for im, path in zip(images,paths)])
+
 
 with gr.Blocks() as demo:
     gr.Markdown("""
@@ -13,6 +15,9 @@ with gr.Blocks() as demo:
     gr.HTML('''
      <p style="margin-bottom: 10px; font-size: 94%">This is the demo page for the "Stable Bias" paper, which aims to explore and quantify social biases in text-to-image systems. <br> This work was done by <a href='https://huggingface.co/sasha' style='text-decoration: underline;' target='_blank'> Alexandra Sasha Luccioni (Hugging Face) </a>, <a href='https://huggingface.co/cakiki' style='text-decoration: underline;' target='_blank'> Christopher Akiki (ScaDS.AI, Leipzig University)</a>, <a href='https://huggingface.co/meg' style='text-decoration: underline;' target='_blank'> Margaret Mitchell (Hugging Face) </a> and  <a href='https://huggingface.co/yjernite' style='text-decoration: underline;' target='_blank'> Yacine Jernite (Hugging Face) </a> .</p>
           ''')
+    examples_path= "images/examples"
+    examples_gallery = gr.Gallery(get_images(examples_path),
+            label="Example images", show_label=False, elem_id="gallery").style(grid=[1,6], height="auto")
     
     gr.HTML('''
      <p style="margin-bottom: 14px; font-size: 100%">  As AI-enabled Text-to-Image systems are becoming increasingly used, characterizing the social biases they exhibit is a necessary first step to lowering their risk of discriminatory outcomes. <br> We propose a new method for exploring and quantifying social biases in these kinds of systems by directly comparing collections of generated images designed to showcase a system’s variation across social attributes — gender and ethnicity — and target attributes for bias evaluation — professions and gender-coded adjectives. <br> We compare three models: Stable Diffusion v.1.4, Stable Diffusion v.2., and Dall-E 2, and present some of our key findings below:</p>
@@ -57,5 +62,46 @@ humans have no inherent gender or ethnicity nor do they belong to socially-const
          with gr.Row():
              gr.HTML('''
              <p style="margin-bottom: 14px; font-size: 100%"> TO DO: talk about what we see above. <br> Continue exploring the demo on your own to uncover other patterns!  </p>''')
-                     
+
+    with gr.Accordion("Comparing model generations", open=False):
+         gr.HTML('''
+         <p style="margin-bottom: 14px; font-size: 100%">  One of the goals of our study was allowing users to compare model generations across professions in an open-ended way, uncovering patterns and trends on their own. This is why we created the <a href='https://huggingface.co/spaces/society-ethics/DiffusionBiasExplorer' style='text-decoration: underline;' target='_blank'> Diffusion Bias Explorer </a> and the <a href='https://huggingface.co/spaces/society-ethics/Average_diffusion_faces' style='text-decoration: underline;' target='_blank'> Average Diffusion Faces </a> tools. <br> We show some of their functionalities below:    </p> ''')    
+         with gr.Row():
+            with gr.Column():
+                impath = "images/biasexplorer"
+                biasexplorer_gallery = gr.Gallery([os.path.join(impath,im) for im in os.listdir(impath)],
+                label="Bias explorer images", show_label=False, elem_id="gallery").style(grid=2, height="auto")
+            with gr.Column():
+                gr.HTML('''
+                 <p style="margin-bottom: 14px; font-size: 100%"> Comparing generations both between two models and within a single model can help uncover trends and patterns that are hard to measure using quantitative approaches. </p>''')
+         with gr.Row():
+            impath = "images/averagefaces"
+            average_gallery = gr.Gallery([os.path.join(impath,im) for im in os.listdir(impath)],
+            label="Average Face images", show_label=False, elem_id="gallery").style(grid=3, height="auto")
+            gr.HTML('''
+                 <p style="margin-bottom: 14px; font-size: 100%"> Looking at the average faces for a given profession across multiple models can help see the dominant characteristics of that profession, as well as how much variation there is (based on how fuzzy the image is). </p>''')                                              
+
+    with gr.Accordion("Exploring the color space of generated images", open=False):
+         gr.HTML('''
+         <p style="margin-bottom: 14px; font-size: 100%">  TODO Chris   </p> ''')               
+            
+    with gr.Accordion("Exploring the nearest neighbors of generated images", open=False):
+         gr.HTML('''
+         <p style="margin-bottom: 14px; font-size: 100%">  TODO Chris   </p> ''')              
+                
+    gr.Markdown("""
+                ### All of the tools created as part of this project:
+            """)
+    gr.HTML('''
+     <p style="margin-bottom: 10px; font-size: 94%">
+     <a href='https://huggingface.co/spaces/society-ethics/Average_diffusion_faces' style='text-decoration: underline;' target='_blank'> Average Diffusion Faces </a>  <br>
+     <a href='https://huggingface.co/spaces/society-ethics/DiffusionBiasExplorer' style='text-decoration: underline;' target='_blank'> Diffusion Bias Explorer </a> <br>
+     <a href='https://huggingface.co/spaces/society-ethics/DiffusionClustering' style='text-decoration: underline;' target='_blank'> Diffusion Cluster Explorer </a>
+     <a href='https://huggingface.co/spaces/society-ethics/DiffusionFaceClustering' style='text-decoration: underline;' target='_blank'> Identity Representation Demo </a>
+     <a href='https://huggingface.co/spaces/tti-bias/identities-bovw-knn' style='text-decoration: underline;' target='_blank'> BoVW Nearest Neighbors Explorer </a> <br> 
+     <a href='https://huggingface.co/spaces/tti-bias/professions-bovw-knn' style='text-decoration: underline;' target='_blank'> BoVW Professions Explorer </a> <br>    
+     <a href='https://huggingface.co/spaces/tti-bias/identities-colorfulness-knn' style='text-decoration: underline;' target='_blank'> Colorfulness Profession Explorer </a> <br>      
+     <a href='https://huggingface.co/spaces/tti-bias/professions-colorfulness-knn' style='text-decoration: underline;' target='_blank'> Colorfulness Identities Explorer </a> <br> </p>
+          ''')
+                                              
 demo.launch(debug=True)