Caffe-Pose
Modified Caffe that supports hand pose estimation.
Features
- Data layers for ICVL, NYU, MSRA, Hands17 hand pose dataset
- PoseDistance layer to display mean joint error in training
- tools/output_pose to save predicted labels
- Baseline for hand pose estimation in ICVL, NYU, MSRA dataset
Files have been changed (compared with caffe@e963ef4)
- data_transformer.hpp/cpp (functions added and modified)
- io.hpp/cpp (functions added and modified)
- smooth_l1_loss_layer.hpp/cpp (added, from rbgirshick's caffe-fast-rcnn)
- roi_pooling_layer.hpp/cpp (added, from rbgirshick's caffe-fast-rcnn)
- pose_data_layer.hpp/cpp (added)
- pose_distance_layer.hpp/cpp (add)
- tools/output_pose (added)
- caffe.proto (parameters added and modified)
Changelog
- Added tools/output_pose
- Added PoseDistanceLayer
- Added PoseDataLayer
- Merged ROIPoolingLayer from rbgirshick's caffe-fast-rcnn
- Merged SmoothL1LossLayer from rbgirshick's caffe-fast-rcnn
- Forked caffe from caffe@e963ef4
Caffe
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and community contributors.
Check out the project site for all the details like
- DIY Deep Learning for Vision with Caffe
- Tutorial Documentation
- BAIR reference models and the community model zoo
- Installation instructions
and step-by-step examples.
Custom distributions
- Intel Caffe (Optimized for CPU and support for multi-node), in particular Xeon processors (HSW, BDW, SKX, Xeon Phi).
- OpenCL Caffe e.g. for AMD or Intel devices.
- Windows Caffe
Community
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!
License and Citation
Caffe is released under the BSD 2-Clause license. The BAIR/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}
}