app.py

from transformers import AutoImageProcessor, AutoModelForImageClassification
from PIL import Image
import torch
import gradio as gr

image_processor = AutoImageProcessor.from_pretrained("wesleyacheng/dog-breeds-multiclass-image-classification-with-vit")
model = AutoModelForImageClassification.from_pretrained("wesleyacheng/dog-breeds-multiclass-image-classification-with-vit")

def classify_dog(image):
    inputs = image_processor(images=image, return_tensors="pt")
    with torch.no_grad():
        outputs = model(**inputs)
    logits = outputs.logits
    predicted_class_idx = logits.argmax(-1).item()
    predicted_breed = model.config.id2label[predicted_class_idx]
    return f"Predicted Dog Breed: {predicted_breed}"

demo = gr.Interface(
    fn=classify_dog,
    inputs=gr.Image(type="pil"),
    outputs="text",
    title="Dog Breed Classifier",
    description="Upload an image of a dog and the model will classify its breed (120 breeds supported)."
)

demo.launch()