Update app.py

app.py

@@ -1,4 +1,4 @@
-**Data Preprocessing**
+#Data Preprocessing
 
 import os
 import numpy as np
@@ -32,7 +32,7 @@ val_data = datagen.flow_from_directory(
     subset='validation'  # Set as validation data
 )
 
-** CNN Model Setup (Transfer Learning)**
+#CNN Model Setup (Transfer Learning)
 
 import tensorflow as tf
 from tensorflow.keras.applications import ResNet50
@@ -64,7 +64,7 @@ model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy']
 # Model summary
 model.summary()
 
-**Training the Model**
+#Training the Model
 
 # Train the model
 history = model.fit(
@@ -103,7 +103,7 @@ plt.grid(True)
 plt.tight_layout()
 plt.show()
 
-**Explainable AI Integration (Grad-CAM)**
+#Explainable AI Integration (Grad-CAM)
 
 import numpy as np
 import tensorflow as tf
@@ -166,13 +166,13 @@ heatmap = make_gradcam_heatmap(img_array, model, 'conv5_block3_out')  # Replace
 # Display the original image with the Grad-CAM heatmap overlay
 display_gradcam(img_path, heatmap)
 
-**Evaluation**
+#Evaluation
 
 # Evaluate model on validation data
 test_loss, test_acc = model.evaluate(val_data, verbose=2)
 print(f'Test Accuracy: {test_acc:.2f}')
 
-**Gradio User Interface**
+#Gradio User Interface
 
 !pip install gradio