Simple implementation of kpzhang93's paper from Matlab to c++, and don't change models.
This original project is MTCNN. I transform this project from Matlab API to Caffe(C++) API。
Install caffe
compile example/MTSrc/MTMain.cpp
MTMain.bin [model dir] [image Path]
[e.g.: ./build/examples/MTSrc/MTMain.bin '/home/dafu/workspace/MTCNN_Caffe/examples/MTmodel' '/home/dafu/workspace/MTCNN_Caffe/examples/MTSrc/test2.jpg']
I add a MemoryData input layer in prototxt file(R-net and O-net) so that to set dynamically batch size. This modify can add speed and take full advantage of GPU resources.
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Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Center (BVLC) and community contributors.
Check out the project site for all the details like
and step-by-step examples.
Please join the caffe-users group or gitter chat to ask questions and talk about methods and models. Framework development discussions and thorough bug reports are collected on Issues.
Happy brewing!
Caffe is released under the BSD 2-Clause license. The BVLC reference models are released for unrestricted use.
Please cite Caffe in your publications if it helps your research:
@article{jia2014caffe,
Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
Journal = {arXiv preprint arXiv:1408.5093},
Title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
Year = {2014}
}