top of page


On this website you can try the model with your own images and buy it if you are satisfied with its accuracy. 


Model description:

Face Anti-Spoofing feature enables to prevent false facial verification by using a photo, video or a different substitute for an authorized person’s face. This model can defend against video attacks which is a sophisticated way to trick the face recognition systems, usually requiring a looped video of a victim’s face.

Business case:

This model can be used for client authentication.

It can be an ideal complement to facial recognition systems. 


Number of classes: 2 (spoof; real)


mAP (mean average precision):
class_id = 0, name = Spoof, ap = 99.33% 
class_id = 1, name = Real, ap = 99.41% 
for conf_thresh = 0.25, precision = 0.96, recall = 0.98, F1-score = 0.97
for conf_thresh = 0.25, average IoU = 85.73 %
IoU threshold = 50 %, used Area-Under-Curve for each unique Recall
mean average precision (mAP@0.50) = 0.993667, or 99.37 %

System requirements:

Inference time using CPU: 55 ms (on HP Laptop 15-DA0042NH (Processor: Intel(R) Core(TM) i7-8550U CPU))


bottom of page