Update app.py

app.py

@@ -7,13 +7,16 @@ from tensorflow.keras.preprocessing import image
 model = tf.keras.models.load_model('Tumor_Model.h5')
 
 def predict_input_image(img):
-    # Ensure the image is in the right shape and format
-    img = img.reshape((1, 224, 224, 3))
-    img = tf.keras.applications.vgg16.preprocess_input(img)
+    # Convert NumPy array to PIL.Image
+    img = Image.fromarray(np.uint8(img))
+    img = img.convert('RGB')
+    img = img.resize((224, 224))
+    img = np.array(img).reshape(1, 224, 224, 3)  # Reshape the image to match the model input
+​
     # Make predictions
-    prediction = model.predict(img).flatten()
+    prediction = model.predict(img)
     result = 'No Tumor Detected' if prediction[0][0] > 0.5 else 'Tumor detected'
-
+​
     return f"Prediction: {result}"
 
 # Define Gradio interface
@@ -24,4 +27,4 @@ iface = gr.Interface(
 )
 
 # Launch the interface
-iface.launch()
+iface.launch(debug = True)