Create app.py

app.py

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+import gradio as gr
+from transformers import ViTForImageClassification, ViTImageProcessor
+from PIL import Image
+import torch
+
+# মডেল ও প্রসেসর লোড করো
+model = ViTForImageClassification.from_pretrained("rakib730/vit-base-oxford-iiit-pets")
+processor = ViTImageProcessor.from_pretrained("rakib730/vit-base-oxford-iiit-pets")
+
+# প্রেডিকশন ফাংশন
+def classify_image(image):
+    inputs = processor(images=image, return_tensors="pt")
+    with torch.no_grad():
+        outputs = model(**inputs)
+    logits = outputs.logits
+    predicted_class_idx = logits.argmax(-1).item()
+    label = model.config.id2label[predicted_class_idx]
+    return label
+
+# Gradio UI
+iface = gr.Interface(
+    fn=classify_image,
+    inputs=gr.Image(type="pil"),
+    outputs="label",
+    title="Oxford-IIIT Pets Classifier",
+    description="Upload a pet image to classify its breed using ViT."
+)
+
+iface.launch()