update app.py

app.py

@@ -9,6 +9,9 @@ from PIL import Image
 feature_extractor = ViTFeatureExtractor.from_pretrained('google/vit-base-patch16-224')
 model = ViTForImageClassification.from_pretrained('google/vit-base-patch16-224')
 
+examples_dir = './samples'
+example_files = glob.glob(os.path.join(examples_dir, '*.jpg'))
+
 def classify_image(image):
 
     with torch.no_grad():
@@ -34,7 +37,10 @@ with gr.Blocks(title="ViT ImageNet Classification - ClassCat",
     gr.HTML("""<div style="font-family:'Times New Roman', 'Serif'; font-size:16pt; font-weight:bold; text-align:center; color:royalblue;">ViT - ImageNet Classification</div>""")
 
     with gr.Row(): 
-        input_image = gr.Image(type="pil", image_mode="RGB", shape=(224, 224))
+        with gr.Column():
+            input_image = gr.Image(type="pil", image_mode="RGB", shape=(224, 224))
+            gr.Examples(example_files, inputs=input_image)
+        
         output_label=gr.Label(label="Probabilities", num_top_classes=3)
 
     send_btn = gr.Button("Infer")