Update app.py

app.py

@@ -8,12 +8,10 @@ import os
 # Function to load the model
 @st.cache_resource
 def load_model():
-    model_path = 'path_to_your_saved_model.h5'  # Ensure this path is correct relative to your deployment setup
-    
+    model_path = 'models/my_model.h5'  # Path relative to the script
     if not os.path.isfile(model_path):
         st.error(f"Model file not found: {model_path}")
         return None
-    
     try:
         model = tf.keras.models.load_model(model_path)
         st.success("Model loaded successfully!")
@@ -25,8 +23,8 @@ def load_model():
 # Function to preprocess the image
 def preprocess_image(image):
     image = np.array(image.convert('RGB'))
-    image = cv2.resize(image, (224, 224))  # Resize the image to the input shape required by your model
-    image = image / 255.0  # Normalize the image
+    image = cv2.resize(image, (224, 224))
+    image = image / 255.0
     image = np.expand_dims(image, axis=0)
     return image
 
@@ -56,7 +54,7 @@ def main():
         st.write("Classifying...")
         try:
             prediction = predict(image, model)
-            predicted_class = np.argmax(prediction, axis=1)[0]  # Adjust based on your model's output
+            predicted_class = np.argmax(prediction, axis=1)[0]
             st.write(f"Predicted class: {predicted_class}")
         except Exception as e:
             st.error(f"Error in prediction: {e}")