Update app.py

app.py

@@ -2,9 +2,9 @@ import gradio as gr
 import numpy as np
 from sklearn.metrics.pairwise import euclidean_distances
 import cv2
+from keras.models import load_model
 
-
-
+autoencoder = tf.keras.models.load_model("autoencoder_model.keras")
 encoded_images = np.load("X_encoded_compressed.npy")
 
 def find_nearest_neighbors(encoded_images, input_image, top_n=5):
@@ -34,14 +34,15 @@ def get_image(index):
     return dataset["test"][index-split]
 
 def process_image(image):
-    print(type(image))
     img = np.array(image)
     img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)  
     img = cv2.resize(img, (64, 64))  
     img = img.astype('float32')  
-    img /= 255.0  
+    img /= 255.0
+    img = np.expand_dims(img, axis=0)
+    encoded_features = autoencoder.predict(img)
 
-    return img
+    return encoded_features
     
 def inference(image):