Upload any image and our deep learning model will analyze it in seconds. Built with transfer learning on EfficientNet-B0 for high-accuracy detection.
Upload & DetectThree simple steps to verify any image
Drag & drop or click to upload a JPG, PNG, or WebP image from your device.
Our EfficientNet-B0 model processes the image through deep neural network layers to detect AI artifacts.
Get an instant verdict with a confidence score — see exactly how sure the model is about its prediction.
Your image never leaves your computer — all processing happens locally
Built with industry-standard deep learning tools
Pre-trained on ImageNet with fine-tuned layers for AI image detection
Training pipeline with transfer learning, cosine LR scheduling & early stopping
High-performance async Python backend serving predictions in milliseconds
No cloud uploads — your images are processed entirely on your machine
The model is trained to detect images created by diffusion models (Stable Diffusion, DALL-E, Midjourney) and GANs (StyleGAN, etc.). Detection accuracy depends on the diversity and quality of the training dataset.
The current model achieves ~94.7% validation accuracy. Accuracy improves with more training data. For best results, use diverse images of similar resolution to the training set.
No. Everything runs locally on your machine. The image is sent to a local server (localhost) and is never transmitted over the internet.
JPG/JPEG, PNG, and WebP. The image is automatically resized and normalized before inference — any resolution works.
Yes! Add more images to the data/train/ and data/val/ folders, then retrain with python -m training.train. More diverse data leads to better generalization.