/caffebeniz

Caffe: a Fast framework for deep learning. For the most recent version checkout the dev branch. For the latest stable release checkout the master branch.

Primary LanguageC++OtherNOASSERTION

Caffe for DeepDetect

This is a slightly modified version of Caffe as used by the Deep Learning API & server Deepdetect. The repository is kept up to date with the original Caffe master branch.

Improvements and new features include:

  • Switch from LOG(FATAL) error to CaffeErrorException thrown on every recoverable errors. This allows the safe use of Caffe as a C++ library from external applications, and in production
  • Various fixes, including ability to run the exact same job in parallel
  • Makefile fixes with default build supporting all NVIDIA architectures
  • Sparse inputs and CPU/GPU computations
  • Support for class weights applied to Softmax loss, useful for training over imbalanced datasets
  • SSD: Single Shot MultiBox Detector for object detection in images
  • Support for lightweight nets via accelerated depthwise convolutions (BVLC#5665) and shufflenet layer (https://github.com/farmingyard/ShuffleNet).
  • Support for image segmentation, via PSPNet, U-Net, SegNet, etc...
  • Support for Squeeze & Excitation Nets (https://github.com/hujie-frank/SENet).
  • Support for SoftNMS with SSD (https://arxiv.org/abs/1704.04503)
  • Support for Focal-Loss with SSD (https://arxiv.org/abs/1708.02002)

While this is intended to be used with DeepDetect, this is a great alternative to the original Caffe if you'd like to avoid uncaptured errors, train from text or sparse data, need built-in image detection.