Update app.py

app.py

@@ -8,6 +8,10 @@ import numpy as np
 # Load pre-trained ResNet50 model + higher level layers
 model = ResNet50(weights='imagenet')
 
+
+chameleon = load_img("example_1.jpeg", output_type="pil")
+
+
 def classify_image(img):
     # Resize the image to 224x224 pixels (required input size for ResNet50)
     img = img.resize((224, 224))
@@ -32,7 +36,7 @@ iface = gr.Interface(
     outputs=gr.Label(num_top_classes=3),  # Output is a label with top 3 predictions
     title="Contextual Image Classification",
     description="Upload an image, and the model will classify it based on the context.",
-    examples = gr.Examples([["./example_1.jpeg"], ["./example_2.jpeg"]], Image)
+    examples=[chameleon],
 )
 
 # Launch the interface