How does this work?

Based on face detection

This app is based on face detection, recognition and analysis. Camgirl.ID is a Python and Torch implementation of face recognition with deep neural networks (DNN).

The following overview shows the workflow for an example image:


1. Detect faces with dlib/OpenCV
2. Transform the face for the neural network. Camgirl.ID uses dlib's real-time pose estimation with OpenCV's affine transformation to try to make the eyes and bottom lip appear in the same location on each image.
3. Use a deep neural network to represent (or embed) the face on a 128-dimensional unit hypersphere. The embedding is a generic representation for anybody's face. Unlike other face representations, this embedding has the nice property that a larger distance between two face embeddings means that the faces are likely not of the same person.

Those properties makes clustering, similarity detection, and classification tasks easier than other face recognition techniques where the Euclidean distance between features is not meaningful.

Over 600,000 camgirls

Our algorithm used is trained on 600,000 webcam models and the current neural network was trained on more than 10 million faces in total. Our bots are spidering over 100,000 additional images every day.

Below are a few aligned and cropped faces of a camgirl:


You can search the database of all the camgirls the DNN is currently trained on here.

Interesting articles about our sister website PornstarID:

After watching thousands of hours of porn, this neural network can identify nearly any adult film star
Neural face recognition network tuned with 650,000 pornstar images