Update app.py

app.py

@@ -4,7 +4,7 @@ from PIL import Image
 import numpy as np
 
 # Load your custom regression model
-model_path = "kia_mnist_keras_model.weights.h5"
+# model_path = "kia_mnist_keras_model.weights.h5"
 model_path = "pokemon_transferlearning.keras"
 
 model = tf.keras.models.load_model(model_path)
@@ -15,9 +15,8 @@ labels = ['Porygon', 'Seel', 'Vaporeon']
 def predict_regression(image):
     # Preprocess image
     image = Image.fromarray(image.astype('uint8'))  # Convert numpy array to PIL image
-    image = image.resize((150, 150)).convert('RGB') # Resize the image to 150x150 and convert it to RGB
+    image = image.resize((150, 150)).convert('L') # Resize the image to 150x150 and convert it to RGB
     image = np.array(image)
-    image = image / 255.0  # Normalize the image to [0, 1]
     print(image.shape)
     # Predict
     prediction = model.predict(image[None, ...])  # Assuming single regression value