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Top 23 C++ Deep Learning Projects
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Project mention: None of the top 10 projects in GitHub is actually a software project 🤯 | dev.to | 2025-05-10
We see an addition to the AI community with AutoGPT. Along with Tensorflow they represent the AI community in the software category, which is getting relevant (2 out of 8). We can expect in the future to have new AI projects in the top 25 such as Transformers or Ollama (currently top 34 and 36, respectively).
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InfluxDB
InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.
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git clone https://github.com/opencv/opencv.git cd opencv git checkout 4.x
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openpose
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
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Project mention: Integrating MediaPipe with DeepSeek for Enhanced AI Performance | dev.to | 2025-02-03
Code Examples: Check out the MediaPipe and LLM Integration Examples provided by Google AI Edge.
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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: From Voice to Text: Exploring Speech-to-Text Tools and APIs for Developers | dev.to | 2025-05-19Setup: Install deepspeech with pip install deepspeech. Download pre-trained models from DeepSpeech Releases. Use a 16kHz mono WAV file.
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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）
PaddlePaddle (so good they named it twice) predates Ray and supports both data parallel and model-parallel training. It is still being developed.
https://github.com/PaddlePaddle/Paddle
They have pedigry.
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ncnn
ncnn is a high-performance neural network inference framework optimized for the mobile platform
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Github Source Code: CNTK
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Project mention: Generative AI Interview for Senior Data Scientists: 50 Key Questions and Answers | dev.to | 2025-05-06
How it works: A model trained in one framework can be converted to the ONNX format. This format can then be run on various hardware or inference engines that support it (e.g., ONNX Runtime). It facilitates easy model transfer and execution even if the development framework and deployment environment differ.
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Project mention: Dlib: Modern C++ toolkit containing machine learning algorithms | news.ycombinator.com | 2025-03-19
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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: Generative AI Interview for Senior Data Scientists: 50 Key Questions and Answers | dev.to | 2025-05-06What is the purpose of using ONNX or TensorRT for deployment? When deploying a trained deep learning model into a real-world service environment for inference, optimization to increase execution speed and reduce resource consumption is crucial. ONNX and TensorRT are prominent tools and frameworks widely used for this purpose.
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MNN
MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba. Full multimodal LLM Android App:[MNN-LLM-Android](./apps/Android/MnnLlmChat/README.md)
Project mention: Alibaba mnn android app support DeepSeek R1 model | news.ycombinator.com | 2025-02-06 -
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Project mention: Court is in session: Top 10 most notorious C and C++ errors in 2024 | dev.to | 2024-12-28
V766 An item with the same key '"SoftPlus"' has already been added. cpu_types.cpp 198
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jetson-inference
Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
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Years ago I started a collection of convolution optimization resources: https://github.com/mratsim/laser/wiki/Convolution-optimisati...
Also checked and apparently Nvidia Cutlass now supports generic convolutions: https://github.com/NVIDIA/cutlass
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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.
How to Accomplish: Use a combination of geometric transformations (e.g., rotation, scaling, cropping, flipping), color space adjustments (e.g., brightness, contrast, saturation), and other techniques (e.g., noise injection, blurring, cutout). Libraries such as ImgAug, DeepMind Augmentation, Albumentations, and NVIDIA DALI offer a wide range of ready-to-use augmentation techniques that can introduce the necessary diversity into your dataset.
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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).
C++ Deep Learning discussion
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Dlib: Modern C++ toolkit containing machine learning algorithms
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A note from our sponsor - SaaSHub
www.saashub.com | 20 May 2025
Index
What are some of the best open-source Deep Learning projects in C++? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | tensorflow | 189,943 |
| 2 | OpenCV | 82,169 |
| 3 | Caffe | 34,356 |
| 4 | openpose | 32,454 |
| 5 | mediapipe | 29,728 |
| 6 | DeepSpeech | 26,336 |
| 7 | PaddlePaddle | 22,774 |
| 8 | ncnn | 21,474 |
| 9 | CNTK | 17,552 |
| 10 | onnxruntime | 16,629 |
| 11 | Dlib | 13,994 |
| 12 | carlo | 12,475 |
| 13 | TensorRT | 11,592 |
| 14 | MNN | 10,862 |
| 15 | oneflow | 8,448 |
| 16 | openvino | 8,290 |
| 17 | jetson-inference | 8,275 |
| 18 | cutlass | 7,451 |
| 19 | wav2letter | 6,425 |
| 20 | serving | 6,281 |
| 21 | tiny-cnn | 5,909 |
| 22 | DALI | 5,395 |
| 23 | flashlight | 5,372 |
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