Top 23 C++ Deep Learning Projects
An Open Source Machine Learning Framework for EveryoneProject mention: Top Github repo trends in 2021 | dev.to | 2022-01-12
No surprises here: deep learning is the most popular subcategory, with hugging face transformers repo, YOLOv5, Tensorflow and Deepmind’s Alphafold all in the mix. Surprisingly, the only proper infrastructure-ey repos on the list are Meilisearch and Clickhouse, a tad bit surprising given all the hype data infrastructure receives in VC-world, but again, probably just a question of size of end-user populations + whether data scientists spend tons of time on Github vs. Web Developers…
Open Source Computer Vision LibraryProject mention: google.protobuf.message.DecodeError: Error parsing message with type 'tensorflow.GraphDef' | reddit.com/r/tensorflow | 2022-01-19
Tried to convert my model.pb file to .pbtxt using this script: https://github.com/opencv/opencv/wiki/TensorFlow-text-graphs
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Tensors and Dynamic neural networks in Python with strong GPU accelerationProject mention: [D] Does PyTorch credit contributors? | reddit.com/r/MachineLearning | 2022-01-14
If you look at the commit that you committed: https://github.com/pytorch/pytorch/commit/fdcb78df38f61e9c18b105e1fd56490e4f285064
Caffe: a fast open framework for deep learning.Project mention: How do I install Caffe framework on Mac M1? | reddit.com/r/MLQuestions | 2022-01-04
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimationProject mention: Technology-assisted Martial Arts Training? | reddit.com/r/martialarts | 2021-12-27
Have you considered using an already trained open source pose model? Something like openpose would work. Then you could have estimated "boxes" relative to the top of the torso and the head cut in half, where the bottom half flags it as a low guard for example. This approach would be more accurate and easier than making a whole new model for a specific necessity, though there is the problem that the dataset used for this may lack people in things like gloves or martial arts equipment.
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: I have 10,000 hours of audio files I'd like transcribed. | reddit.com/r/software | 2022-01-18
You might be able to get some success with Project DeepSpeech
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit (by microsoft)
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Cross-platform, customizable ML solutions for live and streaming media.Project mention: First try to replicate mediapipe codepen hand detection. | reddit.com/r/cpp | 2021-12-28
I have used mediapipie library to make this. https://github.com/google/mediapipe
ncnn is a high-performance neural network inference framework optimized for the mobile platformProject mention: ncnn convert | dev.to | 2021-09-29
ncnn install ncnn
A toolkit for making real world machine learning and data analysis applications in C++Project mention: [D] Is Rust stable/mature enough to be used for production ML? Is making Rust-based python wrappers a good choice for performance heavy uses and internal ML dependencies in 2021? | reddit.com/r/MachineLearning | 2021-12-30
Why not do it all in C++? Dlib has good support for ML. For instance, this is how one would do a simple MNIST example:
Open-source simulator for autonomous driving research.Project mention: What interesting things are people making using a game engine that's not actually a game? | reddit.com/r/gamedev | 2021-12-27
https://carla.org , autonomous driving stuff in unreal,
MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in AlibabaProject mention: Newbie having error code of cannot build selected target abi x86 no suitable splits configured | reddit.com/r/AndroidStudio | 2021-04-12
I found a solution on GitHub check your app's build.gradle, defaultConfig section - you need to add x86 to your ndk abiFilters ndk.abiFilters 'armeabi-v7a','arm64-v8a', 'x86' GitHub Hope it will help. You have to find that file and edit it as given here
ONNX Runtime: cross-platform, high performance ML inferencing and training acceleratorProject mention: 💡 What's new in txtai 4.0 | dev.to | 2022-01-06
txtai supports generating vectors with Hugging Face Transformers, PyTorch, ONNX and Word Vector models.
header only, dependency-free deep learning framework in C++14
A flexible, high-performance serving system for machine learning modelsProject mention: Running concurrent inference processes in Flask or should I use FastAPI? | reddit.com/r/flask | 2021-03-29
Don't roll this yourself. Look at Tensorflow Serving: https://github.com/tensorflow/serving.
Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.Project mention: Jetson Nano 2GB Issues During Training (Out Of Memory / Process Killed) & Other Questions! | reddit.com/r/JetsonNano | 2021-11-05
I’m trying to do the tutorial, where they retrain the neural network to detect fruits (jetson-inference/pytorch-ssd.md at master · dusty-nv/jetson-inference · GitHub 1)
TensorRT is a C++ library for high performance inference on NVIDIA GPUs and deep learning accelerators.Project mention: [P] Python library to optimize Hugging Face transformer for inference: < 0.5 ms latency / 2850 infer/sec | reddit.com/r/MachineLearning | 2021-11-23
On the other side of the spectrum, there is Nvidia demos (here or there) showing us how to build manually a full Transformer graph (operator by operator) in TensorRT to get best performance from their hardware. It’s out of reach for many NLP practitioners and it’s time consuming to debug/maintain/adapt to a slightly different architecture (I tried). Plus, there is a secret: the very optimized model only works for specific sequence lengths and batch sizes. Truth is that, so far (and it will improve soon), it’s mainly for MLPerf benchmark (the one used to compare DL hardware), marketing content, and very specialized engineers.
A C++ standalone library for machine learning (by flashlight)Project mention: Python. | reddit.com/r/ProgrammerHumor | 2022-01-06
Flashlight bro, not flash. Read again
mlpack: a scalable C++ machine learning library --
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] Efficiently loading videos in PyTorch without extracting frames | reddit.com/r/MachineLearning | 2021-10-26
The Triton Inference Server provides an optimized cloud and edge inferencing solution. (by triton-inference-server)Project mention: [D] patterns for scaling video inference service? | reddit.com/r/MachineLearning | 2021-12-22
If you are working at an infrastructure level I would use ECS and utilize the NVIDIA Triton Inference Server. It can handle the multimodel paradigm through their ensemble method (bit of a misnomer since its really just a DAG of data flow through your models though you can add an ensembling method at the end of desired). Also provides a nice HTTP or GRPC interface. With ECS you can also use Application Load Balancer to further scale but how you set that up will also heavily depend on if you are using stateful models or not.
OneFlow is a performance-centered and open-source deep learning framework.Project mention: Optimization of CUDA Elementwise Template Library: Practical, Efficient, and Extensible | reddit.com/r/CUDA | 2022-01-20
Elementwise operation refers to applying a function transformation to every element of a tensor. In deep learning, many operators can be regraded as elementwise operators, such as common activation functions (like ReLU and GELU) and ScalarMultiply (multiplying each element of a tensor by a scalar). For this elementwise operation, OneFlow(https://github.com/Oneflow-Inc/oneflow/) abstracts a CUDA template. this article will introduce the design thoughts and optimization techniques of CUDA template.
A tensorflow implementation of EAST text detector (by argman)Project mention: How the network architecture in EAST text detector translates to keras? | reddit.com/r/MLQuestions | 2021-12-03
I'm not sure whether I'm among a few or many who struggle translating academic papers to code. I tried looking for EAST reliable implementation, and so far I only found this (TF 1.x), this (pytorch), this (pytorch), ... and a few others. The problem is that I cannot tell the differences between each and the paper's implementation. Here's the network architecture below, can someone explain how I should read and interpret / convert what is understood from the figure to a keras model. The parts I find tricky:
C++ Deep Learning related posts
Optimization of CUDA Elementwise Template Library: Practical, Efficient, and Extensible
1 project | reddit.com/r/CUDA | 20 Jan 2022
google.protobuf.message.DecodeError: Error parsing message with type 'tensorflow.GraphDef'
1 project | reddit.com/r/tensorflow | 19 Jan 2022
I have 10,000 hours of audio files I'd like transcribed.
1 project | reddit.com/r/software | 18 Jan 2022
Pytorch Distributed Parallel Computing or Hpc Research
1 project | reddit.com/r/deeplearning | 16 Jan 2022
[D] Is there an open-source implementation of the Retrieval-Enhanced Transformer (RETRO)?
4 projects | reddit.com/r/MachineLearning | 15 Jan 2022
[D] Does PyTorch credit contributors?
3 projects | reddit.com/r/MachineLearning | 14 Jan 2022
Audio to text transcription
1 project | reddit.com/r/software | 9 Jan 2022
What are some of the best open-source Deep Learning projects in C++? This list will help you:
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