Create app.py

app.py

@@ -0,0 +1,25 @@
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+from PIL import Image
+import gradio as gr
+
+# Load the model and feature extractor
+feature_extractor = AutoFeatureExtractor.from_pretrained("google/vit-base-patch16-224")
+model = AutoModelForImageClassification.from_pretrained("google/vit-base-patch16-224")
+
+# Define prediction function
+def classify_image(image):
+    image = Image.fromarray(image).convert("RGB")
+    inputs = feature_extractor(images=image, return_tensors="pt")
+    outputs = model(**inputs)
+    predicted_class = outputs.logits.argmax(-1).item()
+    return model.config.id2label[predicted_class]
+
+# Create a Gradio app
+app = gr.Interface(
+    fn=classify_image,
+    inputs=gr.Image(type="numpy"),
+    outputs="text",
+    title="Image Classifier"
+)
+
+app.launch()