Update app.py

app.py

@@ -0,0 +1,41 @@
+# app.py
+import gradio as gr
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+from PIL import Image
+import torch
+
+# Load processor and model
+processor = AutoImageProcessor.from_pretrained("nguyenkhoa/dinov2_Liveness_detection_v2.2.3")
+model = AutoModelForImageClassification.from_pretrained("nguyenkhoa/dinov2_Liveness_detection_v2.2.3")
+
+# Define labels
+id2label = model.config.id2label
+
+# Inference function
+def detect_liveness(image: Image.Image):
+    # Preprocess image
+    inputs = processor(images=image, return_tensors="pt")
+    with torch.no_grad():
+        outputs = model(**inputs)
+
+    logits = outputs.logits
+    probs = torch.nn.functional.softmax(logits, dim=-1)[0]
+    
+    # Get prediction
+    predicted_class_idx = torch.argmax(probs).item()
+    predicted_label = id2label[predicted_class_idx]
+    confidence = round(probs[predicted_class_idx].item(), 4)
+
+    return f"Liveness: {predicted_label} (Confidence: {confidence})"
+
+# Launch Gradio app
+app = gr.Interface(
+    fn=detect_liveness,
+    inputs=gr.Image(type="pil", label="Upload Face Image"),
+    outputs=gr.Text(label="Liveness Detection Result"),
+    title="Liveness Detection App",
+    description="Upload a face image to check if it's live or spoofed using DinoV2 model."
+)
+
+if __name__ == "__main__":
+    app.launch()