caffe2_cpp_tutorial | C++ transcripts of the Caffe2 Python tutorials | Machine Learning library

by leovandriel C++ Version: 0.0.6 License: BSD-2-Clause

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kandi X-RAY | caffe2_cpp_tutorial Summary

caffe2_cpp_tutorial is a C++ library typically used in Artificial Intelligence, Machine Learning applications. caffe2_cpp_tutorial has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Caffe2 has a strong C++ core but most tutorials only cover the outer Python layer of the framework. This project aims to provide example code written in C++, complementary to the Python documentation and tutorials. It covers verbatim transcriptions of most of the Python tutorials and other example applications. Some higher level tools, like brewing models and adding gradient operations are currently not available in Caffe2's C++. This repo therefore provides some model helpers and other utilities as replacements, which are probably just as helpful as the actual tutorials. You can find them in include/caffe2/util and src/caffe2/util. Check out the original Caffe2 Python tutorials at

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caffe2_cpp_tutorial has a low active ecosystem.

It has 427 star(s) with 95 fork(s). There are 28 watchers for this library.

It had no major release in the last 6 months.

There are 37 open issues and 46 have been closed. On average issues are closed in 60 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of caffe2_cpp_tutorial is 0.0.6

Quality

caffe2_cpp_tutorial has 0 bugs and 0 code smells.

Security

caffe2_cpp_tutorial has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

caffe2_cpp_tutorial code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

caffe2_cpp_tutorial is licensed under the BSD-2-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

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caffe2_cpp_tutorial releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

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Community Discussions

Trending Discussions on caffe2_cpp_tutorial

caffe2 Tensor assignment, construction or copy

QUESTION

caffe2 Tensor assignment, construction or copy

Asked 2017-Nov-22 at 15:34

This is a long shot, if you think the question is too localized, please do vote to close. I have searched on the caffe2 github repository, opened an issue asking the same question, opened another issue at the caffe2_ccp_tutorials repository because its author seems to understand it best, read the doxygen documentation on caffe2::Tensor and caffe2::CUDAContext, and even gone through the caffe2 source code, and in specific the tensor.h, context_gpu.h and context_gpu.cc.

I understand that currently caffe2 does not allow copying device memory to a tensor. I am willing to expand the library and do a pull request in order to achieve this. My reason behind this is that I do all image pre-processing using cv::cuda::* methods which operate on device memory, and as such I think it is clearly a problem doing the pre-processing on the gpu, only to download the result back on the host, and then have it re-uploaded to the network from host to device.

Looking at the constructors of Tensor I can see that maybe only

...

ANSWER

Answered 2017-Nov-22 at 15:34

I have managed to figure this out. The simplest way is to tell OpenCV which memory location to use. This can be done by using the 7th and 8th overload of the cv::cuda::GpuMat constructor shown below:

Source https://stackoverflow.com/questions/45484051

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install caffe2_cpp_tutorial

Install the dependencies CMake, leveldb and OpenCV. If you're on macOS, use Homebrew:.
Install dependencies Install the dependencies CMake, leveldb and OpenCV. If you're on macOS, use Homebrew: brew install cmake glog protobuf leveldb opencv eigen On Ubuntu: apt-get install cmake libgoogle-glog-dev libprotobuf-dev libleveldb-dev libopencv-dev libeigen3-dev curl In case you're using CUDA an run into CMake issues with NCCL, try adding this to your .bashrc (assuming Caffe2 at $HOME/caffe2): export CMAKE_LIBRARY_PATH=$CMAKE_LIBRARY_PATH:$HOME/caffe2/third_party/nccl/build/lib
Install Caffe2 Follow the Caffe2 installation instructions: https://caffe2.ai/docs/getting-started.html
Build using CMake This project uses CMake. However easiest way to just build the whole thing is: make Internally it creates a build folder and runs CMake from there. This also downloads the resources that are required for running some of the tutorials. Check out the Build alternatives section below if you wish to be more involved in the build process.
The easiest way to build all sources is to run:.

Support

See http://rpg.ifi.uzh.ch/docs/glog.html for more info on logging. Try running the tools and examples with --logtostderr=1, --caffe2_log_level=1, and --v=1.

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