Update dashboard.py

dashboard.py

@@ -45,7 +45,7 @@ def predict_image(image):
     with torch.no_grad():
         outputs = hf_model(**inputs)
         probs = torch.nn.functional.softmax(outputs.logits, dim=1).squeeze().tolist()
-    label = "✅ Real Image" if probs[1] >= probs[0] else "⚠️ Fake Image"
+    label = "✅ Real Image" if probs[0] >= probs[1] else "⚠️ Fake Image"
     confidence = max(probs)
     return f"{label} (Confidence: {confidence:.2%})"