Create app.py

app.py

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+import gradio as gr
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+from PIL import Image
+import torch
+
+model_name = "orhanemree/ai-image-detector"
+
+processor = AutoImageProcessor.from_pretrained(model_name)
+model = AutoModelForImageClassification.from_pretrained(model_name)
+
+def predict(image):
+    if image is None:
+        return "No image uploaded", 0, 0
+    
+    inputs = processor(images=image, return_tensors="pt")
+    with torch.no_grad():
+        logits = model(**inputs).logits
+        probs = torch.softmax(logits, dim=1)[0]
+    
+    real_prob = float(probs[0])
+    fake_prob = float(probs[1])
+
+    label = "AI-Generated" if fake_prob > real_prob else "Real Photo"
+
+    return label, round(real_prob, 3), round(fake_prob, 3)
+
+interface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs=[
+        gr.Text(label="Prediction"),
+        gr.Number(label="Real Probability"),
+        gr.Number(label="AI Probability")
+    ],
+    title="AI vs Real Image Detector",
+    description="Upload an image to check if it's AI-generated or real."
+)
+
+interface.launch()