Update app.py

app.py

@@ -56,7 +56,7 @@ def load_model_detection():
 
 def preprocess_image(image):
     """ Preprocess the image to the required size and normalization. """
-    image = cv2.resize(image, (W_detection, H_detection))
+    # image = cv2.resize(image, (W_detection, H_detection))
     image = (image - 127.5) / 127.5  # Normalize to [-1, +1]
     image = np.expand_dims(image, axis=0).astype(np.float32)
     return image
@@ -102,7 +102,7 @@ def load_gradcam_model():
     x = GlobalAveragePooling2D()(x)
 
     # and a logistic layer
-    predictions = Dense(len(labels), activation="sigmoid")(x)
+    predictions = Dense(14, activation="sigmoid")(x)
 
     model = Model(inputs=base_model.input, outputs=predictions)
     model.compile(optimizer='adam', loss="categorical_crossentropy")