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.ipynb_checkpoints/app-checkpoint.py

@@ -15,7 +15,8 @@ resnet_model = tf.keras.models.load_model('./flower_image_classification_ResNet5
 def preprocess_image(image):
     # Convert the PIL image to an array
     image = np.array(image)
-    
+    img_height = 180
+    img_width = 180
     # Read and resize the image
     image_resized = cv2.resize(image, (img_height, img_width))
     

app.py

@@ -15,7 +15,8 @@ resnet_model = tf.keras.models.load_model('./flower_image_classification_ResNet5
 def preprocess_image(image):
     # Convert the PIL image to an array
     image = np.array(image)
-    
+    img_height = 180
+    img_width = 180
     # Read and resize the image
     image_resized = cv2.resize(image, (img_height, img_width))