What the model sees
A convolutional network trained on FER-2013, exported to ONNX and executed here. Nothing is uploaded, and there is no backend to upload it to.
Pick a face below, upload one, or use your camera.
Loading the model…
Faces it has never seen
Held-out FER-2013 test images with their true labels. Some of these it gets wrong — they are included on purpose.
How good is it, honestly
Human agreement on FER-2013 is roughly 65% and published state of the art is near 73%. A model small enough to download lands below both.
Per-class recall matters more than the headline: the training set has 7,215 happy faces and 436 disgusted ones, so a model can ignore disgust completely and barely be punished for it by accuracy alone.
Confusion matrix
Rows are the true expression, columns what the model said. Darker is more.