Update app.py

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 from transformers import pipeline
 
 # Load models
-vit_classifier = pipeline("image-classification", model="LukeXOTWOD/vit-base-oxford-iiit-pets")
+vit_classifier = pipeline("image-classification", model="Fadri/vit-base-oxford-iiit-pets")
 clip_detector = pipeline(model="openai/clip-vit-large-patch14", task="zero-shot-image-classification")
 
 labels_oxford_pets = [
@@ -20,17 +20,23 @@ def classify_pet(image):
     clip_results = clip_detector(image, candidate_labels=labels_oxford_pets)
     clip_output = {result['label']: result['score'] for result in clip_results}
     
-    return {
-        "ViT Transfer Learning Model": vit_output,
-        "CLIP Zero-Shot Model": clip_output
-    }
+    return {"ViT Classification": vit_output, "CLIP Zero-Shot Classification": clip_output}
+
+example_images = [
+    ["example_images/dog1.jpeg"],
+    ["example_images/dog2.jpeg"],
+    ["example_images/leonberger.jpg"],
+    ["example_images/snow_leopard.jpeg"],
+    ["example_images/cat.jpg"]
+]
 
 iface = gr.Interface(
     fn=classify_pet,
     inputs=gr.Image(type="filepath"),
     outputs=gr.JSON(),
     title="Pet Classification Comparison",
-    description="Upload an image of a pet, and compare predictions from a trained ViT model and a zero-shot CLIP model."
+    description="Upload an image of a pet, and compare results from a trained ViT model and a zero-shot CLIP model.",
+    examples=example_images
 )
 
 iface.launch()