文件列表:

CMakeLists.txt (1187, 2016-09-12)
Makefile (6241, 2016-09-12)
affTest.cpp (18739, 2016-09-12)
bitMatcher.cu (11577, 2016-09-12)
bitMatcher.h (134, 2016-09-12)
driveGnuPlotStreams.pl (5275, 2016-09-12)
gpuFacade.cpp (4640, 2016-09-12)
gpuFacade.hpp (1616, 2016-09-12)
latch.cu (31480, 2016-09-12)
latch.h (483, 2016-09-12)
latchAff.cu (32473, 2016-09-12)
latchAff.h (527, 2016-09-12)
min.cpp (6284, 2016-09-12)
vo.cpp (16936, 2016-09-12)
vo2.cpp (14700, 2016-09-12)

Major updates are coming in the immediate future. Please watch this space. # CUDA implementation of the LATCH descriptor & brute-force matcher This is a high performance GPU implementation of the [LATCH descriptor](http://www.openu.ac.il/home/hassner/projects/LATCH/) invented by [Gil Levi](https://gilscvblog.com/2015/11/07/performance-evaluation-of-binary-descriptor-introducing-the-latch-descriptor/) and [Tal Hassner](http://www.openu.ac.il/home/hassner/). Please reference: "LATCH: Learned Arrangements of Three Patch Codes", IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Placid, NY, USA, March, 2016. You should probably be looking at the [OpenMVG branch](https://github.com/mdaiter/openMVG) which includes this code. [](http://www.youtube.com/watch?v=zmfLZY7T6Qg "Video Title") On a GTX 970M I see 10^6 descriptor extractions per second (1 to 1.2 microseconds per descriptor), and 3*10^9 comparisons per second. A GTX 760 sees 70% of this speed. NVidia graphics card with CUDA compute capability >=3.0 required. Look at min.cpp for a minimal introduction. Compile it with "make min -j7". Run it as "./min 1.png 2.png" (Note, min.cpp is broken. Take a look at vo.cpp instead or the OpenMVG class.) vo.cpp has a better example of how you can hide 100% of the processing time of the GPU. The quickest way to see it in action is to install "youtube-dl" and then run "make demo -j7". Or you could just watch this video: https://www.youtube.com/watch?v=zmfLZY7T6Qg I see cumulative 43ms of CPU overhead for GPU processing of 4250 frames of 1080p video. Note that currently each descriptor is 2048 bits but the last 1536 bits are 0. I was originally planning on building larger variants: true 1024 bit and 2048 bit LATCH descriptors. You can relatively easily adjust this down to 1024 bits by changing defines, but refactoring is necessary for 512 bits. Current features: - hardware interpolation for affine invariant descriptors at virtually no performance overhead - customizable importance masking for patch triplet comparisons at no performance overhead - asynchronous GPU operation - fast cross-checking (symmetry test) with event-driven multi-stream matching kernel Approximate order of planned features: - multichannel support ( http://arxiv.org/abs/1603.04408 ) - extractor kernel granularity optimization (possibly increased extractor speed) - documentation - 512 bit matcher (increased matcher speed) - API improvements (currently a mess) - CUDA implementation of adaptive grid FAST detector - offline parameter optimization with PyGMO - integration into OpenCV Multi-GPU support is not currently planned. Please contact me if you have a use case that requires it. This work is released under a Creative Commons Attribution-ShareAlike license. If you use this code in an academic work, please cite me by name ([Christopher Parker](https://github.com/csp256/)) and link to [this repository](https://github.com/csp256/cudaLATCH/). Please email me if you have any questions: csparker.work@gmail.com

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