Updated line 7 with: # Disable the PyplotGlobalUseWarning st.set_option('deprecation.showPyplotGlobalUse', False) | Updated lines 34-45 with: display_images_and_predictions modifications

app.py

@@ -4,6 +4,9 @@ from tensorflow.keras.models import load_model
 from tensorflow.keras.preprocessing import image
 import matplotlib.pyplot as plt
 
+# Disable the PyplotGlobalUseWarning
+st.set_option('deprecation.showPyplotGlobalUse', False)
+
 # Load the model
 model = load_model('brain_tumor_model.keras')
 
@@ -30,16 +33,16 @@ def load_and_preprocess_image(image_path, image_shape=(168, 168)):
 
 # Function to display a row of images with predictions
 def display_images_and_predictions(image_paths, predictions, true_labels, figsize=(20, 5)):
-    plt.figure(figsize=figsize)
+    fig, axes = plt.subplots(1, len(image_paths), figsize=figsize)
     for i, (image_path, prediction, true_label) in enumerate(zip(image_paths, predictions, true_labels)):
-        ax = plt.subplot(1, len(image_paths), i + 1)
+        ax = axes[i]
         img_array = load_and_preprocess_image(image_path)
         img_array = np.squeeze(img_array)
-        plt.imshow(img_array, cmap='gray')
+        ax.imshow(img_array, cmap='gray')
         title_color = 'green' if prediction == true_label else 'red'
-        plt.title(f'True Label: {true_label}\nPred: {prediction}', color=title_color)
-        plt.axis('off')
-    st.pyplot()
+        ax.set_title(f'True Label: {true_label}\nPred: {prediction}', color=title_color)
+        ax.axis('off')
+    st.pyplot(fig)