C++ Deep Learning

Open-source C++ projects categorized as Deep Learning

Top 23 C++ Deep Learning Projects

  • tensorflow

    An Open Source Machine Learning Framework for Everyone

  • Project mention: TensorFlow-metal on Apple Mac is junk for training | news.ycombinator.com | 2024-01-16
  • OpenCV

    Open Source Computer Vision Library

  • Project mention: การจำแนกสายพันธุ์มะม่วง โดยใช้ Visual Geometry Group 16 (VGG16) ใน Python | dev.to | 2024-04-16

    Referenceshttps https://www.kaggle.com/datasets/riyaelizashaju/skin-disease-image-dataset-balanced?fbclid=IwAR3wbTp8l5yo_5fx6HAX8Vd2-9cca3khAc8EiBGFObaALfdVid29IuB_rYE https://keras.io/api/applications/vgg/ https://www.tensorflow.org/tutorials/images/cnn?hl=th https://opencv.org/

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • Caffe

    Caffe: a fast open framework for deep learning.

  • Project mention: List of AI-Models | /r/GPT_do_dah | 2023-05-16

    Click to Learn more...

  • openpose

    OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

  • Project mention: AI "Artists" Are Lazy, and the Ultimate Goal of AI Image Generation (hint: its sloth) | /r/ArtistHate | 2023-11-25

    Open Pose, a multi-person keypoint detection library for body, face, hands, and foot estimation [10], is used for posing generated characters;

  • mediapipe

    Cross-platform, customizable ML solutions for live and streaming media.

  • Project mention: Mediapipe openpose Controlnet model for SD | /r/localdiffusion | 2023-11-15

    mediapipe/docs/solutions/pose.md at master · google/mediapipe · GitHub

  • DeepSpeech

    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.

  • Project mention: Common Voice | news.ycombinator.com | 2023-12-05
  • PaddlePaddle

    PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)

  • Project mention: List of AI-Models | /r/GPT_do_dah | 2023-05-16

    Click to Learn more...

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • ncnn

    ncnn is a high-performance neural network inference framework optimized for the mobile platform

  • Project mention: AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source | news.ycombinator.com | 2024-02-12

    ncnn uses Vulkan for GPU acceleration, I've seen it used in a few projects to get AMD hardware support.

    https://github.com/Tencent/ncnn

  • CNTK

    Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

  • Dlib

    A toolkit for making real world machine learning and data analysis applications in C++

  • Project mention: Modern Image Processing Algorithms Implementation in C | news.ycombinator.com | 2023-06-06
  • onnxruntime

    ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

  • Project mention: AI Inference now available in Supabase Edge Functions | dev.to | 2024-04-16

    Embedding generation uses the ONNX runtime under the hood. This is a cross-platform inferencing library that supports multiple execution providers from CPU to specialized GPUs.

  • carla

    Open-source simulator for autonomous driving research.

  • Project mention: Tesla braces for its first trial involving Autopilot fatality | news.ycombinator.com | 2023-08-28
  • TensorRT

    NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.

  • Project mention: AMD MI300X 30% higher performance than Nvidia H100, even with optimized stack | news.ycombinator.com | 2023-12-17

    > It's not rocket science to implement matrix multiplication in any GPU.

    You're right, it's harder. Saying this as someone who's done more work on the former than the latter. (I have, with a team, built a rocket engine. And not your school or backyard project size, but nozzle bigger than your face kind. I've also written CUDA kernels and boy is there a big learning curve to the latter that you gotta fundamentally rethink how you view a problem. It's unquestionable why CUDA devs are paid so much. Really it's only questionable why they aren't paid more)

    I know it is easy to think this problem is easy, it really looks that way. But there's an incredible amount of optimization that goes into all of this and that's what's really hard. You aren't going to get away with just N for loops for a tensor rank N. You got to chop the data up, be intelligent about it, manage memory, how you load memory, handle many data types, take into consideration different results for different FMA operations, and a whole lot more. There's a whole lot of non-obvious things that result in high optimization (maybe obvious __after__ the fact, but that's not truthfully "obvious"). The thing is, the space is so well researched and implemented that you can't get away with naive implementations, you have to be on the bleeding edge.

    Then you have to do that and make it reasonably usable for the programmer too, abstracting away all of that. Cuda also has a huge head start and momentum is not a force to be reckoned with (pun intended).

    Look at TensorRT[0]. The software isn't even complete and it still isn't going to cover all neural networks on all GPUs. I've had stuff work on a V100 and H100 but not an A100, then later get fixed. They even have the "Apple Advantage" in that they have control of the hardware. I'm not certain AMD will have the same advantage. We talk a lot about the difficulties of being first mover, but I think we can also recognize that momentum is an advantage of being first mover. And it isn't one to scoff at.

    [0] https://github.com/NVIDIA/TensorRT

  • MNN

    MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba

  • Project mention: [D][R] Deploying deep models on memory constrained devices | /r/MachineLearning | 2023-10-03

    However, I am looking on this subject through the problem of training/finetuning deep models on the edge devices, being increasingly available thing to do. Looking at tflite, alibaba's MNN, mit-han-lab's tinyengine etc..

  • jetson-inference

    Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

  • wav2letter

    Facebook AI Research's Automatic Speech Recognition Toolkit

  • serving

    A flexible, high-performance serving system for machine learning models

  • Project mention: Llama.cpp: Full CUDA GPU Acceleration | news.ycombinator.com | 2023-06-12

    Yet another TEDIOUS BATTLE: Python vs. C++/C stack.

    This project gained popularity due to the HIGH DEMAND for running large models with 1B+ parameters, like `llama`. Python dominates the interface and training ecosystem, but prior to llama.cpp, non-ML professionals showed little interest in a fast C++ interface library. While existing solutions like tensorflow-serving [1] in C++ were sufficiently fast with GPU support, llama.cpp took the initiative to optimize for CPU and trim unnecessary code, essentially code-golfing and sacrificing some algorithm correctness for improved performance, which isn't favored by "ML research".

    NOTE: In my opinion, a true pioneer was DarkNet, which implemented the YOLO model series and significantly outperformed others [2]. Same trick basically like llama.cpp

    [1] https://github.com/tensorflow/serving

  • openvino

    OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference

  • Project mention: FLaNK Stack 05 Feb 2024 | dev.to | 2024-02-05
  • tiny-cnn

    header only, dependency-free deep learning framework in C++14

  • oneflow

    OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.

  • flashlight

    A C++ standalone library for machine learning (by flashlight)

  • Project mention: MatX: Efficient C++17 GPU numerical computing library with Python-like syntax | news.ycombinator.com | 2023-10-03

    I think a comparison to PyTorch, TensorFlow and/or JAX is more relevant than a comparison to CuPy/NumPy.

    And then maybe also a comparison to Flashlight (https://github.com/flashlight/flashlight) or other C/C++ based ML/computing libraries?

    Also, there is no mention of it, so I suppose this does not support automatic differentiation?

  • DALI

    A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

  • Project mention: [D] Will data augmentations work faster on TPUs? | /r/MachineLearning | 2023-12-07

    Another option is DALI https://github.com/NVIDIA/DALI For my project while training EfficientNet2, it was a game changer. But it a way harder to implement in code than TorchVision or Kornia.

  • mace

    MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020). The latest post mention was on 2024-04-16.

C++ Deep Learning related posts

Index

What are some of the best open-source Deep Learning projects in C++? This list will help you:

Project Stars
1 tensorflow 182,323
2 OpenCV 75,423
3 Caffe 33,837
4 openpose 29,802
5 mediapipe 25,331
6 DeepSpeech 24,212
7 PaddlePaddle 21,584
8 ncnn 19,125
9 CNTK 17,435
10 Dlib 12,991
11 onnxruntime 12,583
12 carla 10,467
13 TensorRT 9,031
14 MNN 8,278
15 jetson-inference 7,294
16 wav2letter 6,328
17 serving 6,070
18 openvino 5,864
19 tiny-cnn 5,763
20 oneflow 5,715
21 flashlight 5,139
22 DALI 4,902
23 mace 4,874
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
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