DeepLabCut — The Mathis Lab of Adaptive Intelligence
DeepLabCutâ„¢ is an efficient method for 2D and 3D markerless pose estimation based on transfer learning with deep neural networks that achieves excellent results (i.e. you can match human labeling accuracy) with minimal training data (typically 50-200 frames). We demonstrate the versatility of this framework by tracking various body parts in multiple species across a broad collection of behaviors.
Caffe Installation on OS X 10.12 (&Matcaffe) - complex small world
所用ã§caffeã‚’å‹•ã‹ã™å¿…è¦ãŒç™ºç”Ÿã—ãŸãŸã‚。 Mac OS Sierra 10.12.1 / OpenBLAS / Matlab 2015b (NO Cuda / NO Python) 実施日時2017/1/3 ã‚ãã¾ã§ä»¥ä¸‹ã®è‡ªåˆ†ã®è¸ã‚“ã é“ã§ã‚ã‚Šã€ä»–ã«ãƒ™ã‚¿ãƒ¼ãªã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«æ–¹æ³•ãŒã‚ã‚‹ã®ã‹ã‚‚ã§ã™ã€‚ 基本的ãªã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã¨Makefile.configã«ã¤ã„㦠ã¾ãšCaffeå…¬å¼ã‚’å‚考ã«ã€‚terminalã‹ã‚‰brewを使ã£ã¦ä»¥ä¸‹ã‚’インストール。 $ brew install -vd snappy leveldb gflags glog szip lmdb $ brew tap homebrew/science $ brew install hdf5 opencv ã¾ãŸã€ä»Šå›žã¯Python環境を使ã‚ãªã„ã®ã§ä»¥ä¸‹ã®ã¿ã€‚ $ brew install protobuf boost BLASã¯OpenB
Caffe | Deep Learning Framework
Caffe Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Check out our web image classification demo! Why Caffe? Expressive architecture encourages application and innovat
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GitHub - BVLC/caffe at windows
GitHub - floydhub/dl-docker: An all-in-one Docker image for deep learning. Contains all the popular DL frameworks (TensorFlow, Theano, Torch, Caffe, etc.)
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