Diversify example images with different classes

app.py

@@ -27,8 +27,7 @@ def infer(model, image_tensor):
     labels = ["cardboard", "glass", "metal", "paper", "plastic", "trash"]
     predictions = list(map(float, predictions[0]))
     output = dict(zip(labels, predictions))
-    print(output)
-    
+
     return output
 
 
@@ -52,11 +51,12 @@ description = "Upload an image or select from examples to classify trash."
 article = "<div style='text-align: center;'>Space by Tan Le</div>"
 
 examples = [
-    "images/beverage_cans_17.jpeg",
-    "images/construction_scrap_69.jpeg",
-    "images/metal_containers_19.jpeg",
-    "images/metal_objects_12.jpeg",
-    "images/spray_cans_47.jpeg",
+    "images/cigarette_butt.jpeg",
+    "images/masks.jpeg",
+    "images/metal_objects.jpeg",
+    "images/paper.jpeg",
+    "images/spray_cans.jpeg",
+    "images/syringe.jpeg",
 ]
 
 demo = gr.Interface(