Update app.py

app.py

@@ -18,6 +18,7 @@ from tensorflow import image
 from tensorflow.python.keras.models import load_model
 from keras.applications.densenet import DenseNet121
 from keras.layers import Dense, GlobalAveragePooling2D
+from keras.models import Model
 from pydicom.pixel_data_handlers.util import apply_voi_lut
 
 # Environment Configuration
@@ -57,9 +58,9 @@ 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 = (image - 127.5) / 127.5  # Normalize to [-1, +1]
-    image = np.expand_dims(image, axis=0).astype(np.float32)
-    return image
+    # image = (image - 127.5) / 127.5  # Normalize to [-1, +1]
+    # image = np.expand_dims(image, axis=0).astype(np.float32)
+    # return image
 
 def predict(model_detection, image):
     """ Predict bounding box and label for the input image. """