Update app.py

app.py

@@ -49,9 +49,9 @@ def query_model(input_text):
     return response.stdout if response.returncode == 0 else response.stderr                           
 # Load the breast cancer detection model
 
-incept_model = tf.keras.models.load_model('/content/sample_data/breast cancer/best_model_2.h5')
+incept_model = tf.keras.models.load_model('best_model_2.h5')
 
-fixed_image_url = "/content/sample_data/breast cancer/static/breast-cancer-awareness-month-1200x834.jpg"
+fixed_image_url = "breast-cancer-awareness-month-1200x834.jpg"
 
 
 
@@ -59,17 +59,18 @@ fixed_image_url = "/content/sample_data/breast cancer/static/breast-cancer-aware
 
 examples = [
 
-    ["/content/sample_data/breast cancer/malignant.png", "Malignant X-ray image."],
+    ["malignant.png", "Malignant X-ray image."],
 
-    ["/content/sample_data/breast cancer/normal.png", "X-ray image indicating normal."],
+    ["normal.png", "X-ray image indicating normal."],
 
-    ["/content/sample_data/breast cancer/benign.png", "X-ray image showing no signs of benign."]
+    ["benign.png", "X-ray image showing no signs of benign."]
 
 ]
 
 IMAGE_SHAPE = (224, 224)
 
-classes = ['benign', 'malignant', 'normal']                                                                           # Function to prepare the image for prediction
+classes = ['benign', 'malignant', 'normal']      
+# Function to prepare the image for prediction
 
 def prepare_image(file):
 
@@ -119,7 +120,8 @@ def predict(file):
 
 
 
-    return advice, fixed_image_url                                                                                              # Function to provide project information
+    return advice, fixed_image_url                                                                                              
+# Function to provide project information
 
 def show_info():