Create app.py

app.py

@@ -0,0 +1,33 @@
+import gradio as gr
+from transformers import AutoModelForImageClassification, AutoImageProcessor
+from PIL import Image
+import torch
+
+# Load model and processor
+model_name = "dima806/deepfake_vs_real_image_detection"
+model = AutoModelForImageClassification.from_pretrained(model_name)
+processor = AutoImageProcessor.from_pretrained(model_name)
+
+def detect_deepfake(image):
+    # Preprocess image
+    inputs = processor(images=image, return_tensors="pt")
+    with torch.no_grad():
+        outputs = model(**inputs)
+        probs = torch.nn.functional.softmax(outputs.logits, dim=-1)[0]
+
+    # Convert to dict
+    labels = model.config.id2label
+    results = {labels[i]: float(probs[i]) for i in range(len(labels))}
+    return results
+
+# Gradio UI
+demo = gr.Interface(
+    fn=detect_deepfake,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Label(num_top_classes=2),
+    title="Deepfake Detector",
+    description="Upload an image to check if it's Real or Fake using an AI model."
+)
+
+if __name__ == "__main__":
+    demo.launch()