Top 23 C++ Machine learning Projects
An Open Source Machine Learning Framework for EveryoneLatest mention: Rtx 3090 Is 14 Times Slower On Inference Compared | reddit.com/r/tensorflow | 2021-01-09
That does seem to be the case. TF is much slower than pytorch for training, especially in backpropogation (depending on optimizers) https://github.com/tensorflow/tensorflow/issues/42475
Tensors and Dynamic neural networks in Python with strong GPU accelerationLatest mention: [P] Implementation of RealFormer using pytorch | reddit.com/r/MachineLearning | 2020-12-27
Tip: Use torch.bmm instead of torch.einsum. The former is considerably faster. Take a look at Pytorchs own MHA implementation to see how you have to do the reshaping for it.
Tesseract Open Source OCR Engine (main repository)Latest mention: How do i use matlab ocr to recognize math equations? | reddit.com/r/matlab | 2021-01-16
The code looks fine, I think for whatever reason the 'MathEquations' network just does a poor job of recognizing the equations. The support package that includes the language is based on this open-source tessaract repo which seems to struggle with math equation recognition (at least based on this issue).
Caffe: a fast open framework for deep learning.
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimationLatest mention: Kinect + jetson nano for tracking the bodies of the persons displayed inside of screen ? | reddit.com/r/JetsonNano | 2020-12-22
There probably a few projects that could help you out, the first one that comes to mind is called openpose.
> But you still lose something, e.g. if you use half precision on V100 you get virtually double speed, if you do on a 1080 / 2080 you get... nothing because it's not supported.
That's not true. FP16 is supported and can be fast on 2080, although some frameworks fail to see the speed-up. I filed a bug report about this a year ago: https://github.com/apache/incubator-mxnet/issues/17665
What consumer GPUs lack is ECC and fast FP64.
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.Latest mention: Any self hosted call transcription software? | reddit.com/r/selfhosted | 2021-01-19
Cross-platform, customizable ML solutions for live and streaming media.Latest mention: Weekly Developer Roundup #21 - Sun Nov 08 2020 | dev.to | 2020-11-07
google/mediapipe (C++): MediaPipe is the simplest way for researchers and developers to build world-class ML solutions and applications for mobile, edge, cloud and the web.
A toolkit for making real world machine learning and data analysis applications in C++
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
header only, dependency-free deep learning framework in C++14
Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.Latest mention: Basic Teaching | reddit.com/r/JetsonNano | 2021-01-18
Open3D: A Modern Library for 3D Data ProcessingLatest mention: LIDAR to OBJ similar to photogrammetry with Intel RealSense L515? | reddit.com/r/3DScanning | 2021-01-05
mlpack: a scalable C++ machine learning library --
MITIE: library and tools for information extractionLatest mention: Is it possible to build a recommendation system or do sentiment analysis in plain c++? | reddit.com/r/AskComputerScience | 2021-01-14
I would suggest you use something like LucenePlusPlus as the backbone of the system for processing the text, and maybe something like MITIE for further analysis (I've never used this to be honest).
Deep Learning API and Server in C++11 support for Caffe, Caffe2, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNELatest mention: [P] Benchmarking OpenBLAS on an Apple MacBook M1 | reddit.com/r/MachineLearning | 2020-12-30
Interesting, thanks. Recently benchmarked inference with Vulkan/MoltenVK/NCNN, M1 GPU is roughly 30% faster than M1 CPU, https://github.com/jolibrain/deepdetect/pull/1105 for single batch inference (NCNN does not really support batch size > 1).
The Triton Inference Server provides an optimized cloud and edge inferencing solution.Latest mention: [D] Deploying ML models - batching | reddit.com/r/MachineLearning | 2020-12-27
I've seen this called "dynamic batching" most places at work. Nvidia has Triton Inference server which works fine for us. I'd say likely you'll get more speedup from dymamic batching on GPU than CPU depending on model architecture. The overall structure probably looks something like one inference thread, then when requests come in (from many threads) you add them to your queue, and when the queue is full or The oldest enqueued request times out, you construct your batch then run inference
A C++ standalone library for machine learningLatest mention: Facebook To Release Xlsr53 A Wav2vec 20 Model | reddit.com/r/speechtech | 2021-01-09
Project moved to here: https://github.com/facebookresearch/flashlight/tree/master/flashlight/app/asr
Header-only library for using Keras models in C++.
What are some of the best open-source Machine learning projects in C++? This list will help you: