Update app.py

app.py

@@ -1,9 +1,34 @@
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+def find_nearest_neighbors(encoded_images, input_image, top_n=5):
+    """
+    Find the closest neighbors to the input image in the encoded image space.
+
+    Args:
+    encoded_images (np.ndarray): Array of encoded images (shape: (n_samples, n_features)).
+    input_image (np.ndarray): The encoded input image (shape: (1, n_features)).
+    top_n (int): The number of nearest neighbors to return.
+
+    Returns:
+    List of tuples: (index, distance) of the top_n nearest neighbors.
+    """
+    # Compute pairwise distances
+    distances = euclidean_distances(encoded_images, input_image.reshape(1, -1)).flatten()
+
+    # Sort by distance
+    nearest_neighbors = np.argsort(distances)[:top_n]
+    return [(index, distances[index]) for index in nearest_neighbors]
+
+def get_image(index):
+  split = len(dataset["train"])
+  if index < split:
+    return dataset["train"][index]
+  else:
+    return dataset["test"][index-split]
+
+
 
 demo = gr.Interface(fn=greet, 
-                        inputs=[gr.File('Upload image')]
+                        inputs=[gr.File(label='Upload image')]
                         outputs="text")
 demo.launch()