Update app.py

app.py

@@ -1,4 +1,8 @@
 import gradio as gr
+import numpy as np
+
+
+encoded_images = np.load("X_encoded_compressed.npy")
 
 def find_nearest_neighbors(encoded_images, input_image, top_n=5):
     """
@@ -26,6 +30,45 @@ def get_image(index):
   else:
     return dataset["test"][index-split]
 
+def process_image(image):
+    pass
+
+def inference(image):
+
+    input_image = process_image(image)
+    
+    nearest_neighbors = find_nearest_neighbors(encoded_images, input_image, top_n=5)
+    
+    # Print the results
+    print("Nearest neighbors (index, distance):")
+    for neighbor in nearest_neighbors:
+        print(neighbor)
+    
+    top4 = [int(i[0]) for i in nearest_neighbors[:4]]
+    print(f"top 4: {top4}")
+    
+    for i in top4:
+      im = get_image(i)
+      print(im["label"], im["timestamp"])
+    
+    n=2
+    plt.figure(figsize=(8, 8))
+    for i, (image1, image2) in enumerate(zip(top4[:2], top4[2:])):
+        ax = plt.subplot(2, n, i + 1)
+        image1 = get_image(image1)["image"]
+        image2 = get_image(image2)["image"]
+    
+        plt.imshow(image1)
+        plt.gray()
+        ax.get_xaxis().set_visible(False)
+        ax.get_yaxis().set_visible(False)
+    
+        ax = plt.subplot(2, n, i + 1 + n)
+        plt.imshow(image2)
+        plt.gray()
+        ax.get_xaxis().set_visible(False)
+        ax.get_yaxis().set_visible(False)
+    
 
 
 demo = gr.Interface(fn=greet,