Update app.py

app.py

@@ -1,25 +1,25 @@
 # -*- coding: utf-8 -*-
 """demo.ipynb
-
 Automatically generated by Colab.
-
 Original file is located at
     https://colab.research.google.com/drive/10nAdNOzeCbnza9ZenZqOLtvBYn8BKlk5
 """
 
-
 import streamlit as st
 from PIL import Image
 import numpy as np
 from joblib import load
 from skimage.transform import resize
-from google.colab import drive
 import os
 
-drive.mount('/content/drive')
-
 def load_model():
-    model = load('/content/drive/MyDrive/Senior Project/Coding/svm_model3.joblib') # SkinTone Dataset  svm_model1.joblib')
+    # Ensure the model path is correct and accessible from your current directory
+    model_path = 'svm_model3.joblib'  # Update this path to where you've saved your model
+    if os.path.exists(model_path):
+        model = load(model_path)
+        st.write("Model loaded successfully!")
+    else:
+        st.error("Model file not found.")
     return model
 
 # Function to make predictions
@@ -30,7 +30,7 @@ def classify_image(image, model):
     prediction = model.predict(image_reshaped)
     return prediction[0]
 
-model = load_model()
+model = load_model()  # Load the model on startup
 
 # Mapping of Monk classes to colors
 monk_colors = {
@@ -56,4 +56,3 @@ if uploaded_file is not None:
     if st.button('Classify'):
         prediction = classify_image(image, model)
         display_monk_class_color(prediction)
-