Update app.py

app.py

@@ -3,14 +3,14 @@ import pandas as pd
 from datasets import load_dataset
 import numpy as np
 
-gender_labels = ['man', 'no_gender_specified', 'non-binary', 'woman']
+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("SDBiaseval/identities", split="train")
 
@@ -21,5 +21,14 @@ def get_nearest_64(gender, ethnicity, model, no):
     ix = get_index(gender, ethnicity, model, no)
     return ds.select(index[ix][0])["image"], ds.select(index[ix][1:])["image"]
 
+with gr.Blocks() as demo:
+    gender = gr.Radio(gender_labels, label="Gender label")
+    ethnicity = gr.Radio(ethnicity_labels, label="Ethnicity label")
+    model = gr.Radio(models, label="Model")
+    no = gr.Radio(nos, label="Image number")
+
+    button = gr.Button(value="Get nearest neighbors")
+    button.click(get_nearest_64, inputs=[gender, ethnicity, model, no], outputs=[gr.Image(), gr.Gallery().style(grid=[8])])
+demo.launch()
 # demo = gr.Interface(fn=query_db, inputs="text", outputs=[gr.Image(), gr.Gallery().style(grid=[8])])
 # demo.launch(debug=True)