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README.md

@@ -1,12 +1,13 @@
 ---
 title: Identities Knn
-emoji: 🔥
+emoji: 📉
 colorFrom: green
-colorTo: gray
+colorTo: red
 sdk: gradio
-sdk_version: 3.17.0
+sdk_version: 3.16.2
 app_file: app.py
 pinned: false
+license: apache-2.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+from datasets import load_dataset
+import numpy as np
+
+
+gender_labels = ['man', 'non-binary', 'woman', 'no_gender_specified', ]
+
+ethnicity_labels = ['African-American', 'American_Indian', 'Black', 'Caucasian', 'East_Asian',
+                    'First_Nations', 'Hispanic', 'Indigenous_American', 'Latino', 'Latinx',
+                    'Multiracial', 'Native_American', 'Pacific_Islander', 'South_Asian',
+                    'Southeast_Asian', 'White', 'no_ethnicity_specified']
+models = ['DallE', 'SD_14', 'SD_2']
+nos = [1,2,3,4,5,6,7,8,9,10]
+index = np.load("indexes/knn_10752_65.npy")
+ds = load_dataset("tti-bias/identities", split="train")
+
+def get_nearest_64(gender, ethnicity, model, no):
+    df = ds.remove_columns(["image","image_path"]).to_pandas()
+    ix = df.loc[(df['ethnicity'] == ethnicity)  & (df['gender'] == gender) & (df['no'] == no) & (df['model'] == model)].index[0]
+    image = ds.select([index[ix][0]])["image"][0]
+    neighbors =  ds.select(index[ix][1:])
+    neighbor_images = neighbors["image"]
+    neighbor_captions = [caption.split("/")[-1] for caption in neighbors["image_path"]]
+    return image, list(zip(neighbor_images, neighbor_captions))
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            gender = gr.Radio(gender_labels, label="Gender label")
+            model = gr.Radio(models, label="Model")
+            no = gr.Radio(nos, label="Image number")
+        with gr.Column():
+            ethnicity = gr.Radio(ethnicity_labels, label="Ethnicity label")
+    button = gr.Button(value="Get nearest neighbors")
+    with gr.Row():
+        image = gr.Image()
+        gallery = gr.Gallery().style(grid=8)
+    button.click(get_nearest_64, inputs=[gender, ethnicity, model, no], outputs=[image, gallery])
+demo.launch()

indexes/knn_10752_65.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:47eb9dbb1b403c0533e09336bd592125a0db83f2c122ca267bbc05fc877d05c1
+size 530528

requirements.txt

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+datasets[vision]
+numpy
+imutils