Googles' deep learning framework Tensorflow is Open Source for quite some time now. It might be interesting to use TensorFlow for face and object detection/recognition in Digikam. This could improve the hit rate and also add some performance on CUDA based hardware. Sample implementation in the Tensorflow Tutorials on GitHub: https://github.com/tensorflow/models/tree/master/tutorials/image Another implementation: https://github.com/priya-dwivedi/Deep-Learning/blob/master/Object_Detection_Tensorflow_API.ipynb Helpful blog entry by Google: https://research.googleblog.com/2017/06/supercharge-your-computer-vision-models.html
TensorFlow is python based API. We use C++ here. So no way to use TensorFlow. Also, we have other algorithm to finalize and one explicitly based on Neural Network : https://cgit.kde.org/digikam.git/tree/core/libs/facesengine/dnnface This is based on DLib : https://github.com/davisking/dlib Gilles Caulier
(In reply to caulier.gilles from comment #1) > TensorFlow is python based API. We use C++ here. So no way to use TensorFlow. > > Also, we have other algorithm to finalize and one explicitly based on Neural > Network : > > https://cgit.kde.org/digikam.git/tree/core/libs/facesengine/dnnface > > This is based on DLib : > > https://github.com/davisking/dlib > > Gilles Caulier There is a C++ API for Tensorflow as well: https://www.tensorflow.org/tutorials/image_recognition (section: Usage with the C++ API) Thanks for the additional info on the ongoing work.
7.0.0 release will use Neural Network deep learning from OpenCV.