Update app.py

app.py

@@ -3,17 +3,17 @@ from tensorflow.keras.models import load_model
 import numpy as np
 from PIL import Image
 
+
 model = load_model('xray_image_classifier_model.keras')
 
 def predict(image):
+
     img = image.resize((150, 150))
     img_array = np.array(img) / 255.0
     img_array = np.expand_dims(img_array, axis=0)
 
-    # Make a prediction
     prediction = model.predict(img_array)
     predicted_class = 'Pneumonia' if prediction > 0.5 else 'Normal'
-
     return predicted_class
 
 
@@ -55,7 +55,13 @@ css = """
     }
 """
 
-# Gradio interface set up
+
+examples = [
+    ["samples/normal_xray1.jpg"],
+    ["samples/pneumonia_xray1.jpg"],
+]
+
+# Gradio interface set up instructions
 with gr.Blocks(css=css) as interface:
     gr.Markdown("<h1>Chest X-ray Pneumonia Classifier</h1>")
     gr.Markdown("<p>Upload an X-ray image to classify it as 'Pneumonia' or 'Normal'.</p>")
@@ -67,4 +73,7 @@ with gr.Blocks(css=css) as interface:
     submit_btn = gr.Button("Classify X-ray", elem_classes=["gr-button"])
     submit_btn.click(fn=predict, inputs=image_input, outputs=output)
 
+    
+    gr.Examples(examples=examples, inputs=image_input)
+
 interface.launch()