deepdetect
flashlight
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deepdetect | flashlight | |
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4 | 16 | |
2,495 | 5,145 | |
0.3% | 1.1% | |
6.7 | 7.7 | |
3 days ago | 24 days ago | |
C++ | C++ | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
deepdetect
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
For those seeking a lightweight solution for setting up deep learning REST APIs across platforms without the complexity of Kubernetes, Deepdetect is worth considering.
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[D] Deep Learning Framework for C++.
But you need to have good reasons to do it. Ours is that we have a multi-backend framework, and that we don't want any step in between dev & run. C++ allows for this since the same code can run on training server and edge device as needed. It also allows for building full AI applicatioms with great performances (e g. real time) We dev & use https://github.com/jolibrain/deepdetect for these purposes and it serves us very well, but it's not the faint of heart !
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[P] Real-time AR for jewelry virtual try on that looks real, done with joliGAN, based on a few 2D videos and no 3D model
- Real-time is achieved through our full C++ Open Source backend DeepDetect, https://github.com/jolibrain/deepdetect. We use CUDA along with OpenCV and TensorRT to chain multiple models (ring detection and generator mostly), and we make sure the data remain within CUDA memory at all time. This allows us to reach ~60 FPS on 1080Ti and 20% more on average on an RTX3090.
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[P] Benchmarking OpenBLAS on an Apple MacBook M1
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).
flashlight
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MatX: Efficient C++17 GPU numerical computing library with Python-like syntax
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?
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Project Resources
This Facebook ai project seems reasonably structured after looking at its CMakeLists.txt. CMake is a build generator for c++, it's how you make binaries to run your project: https://github.com/flashlight/flashlight
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Meta AI Open Sources Flashlight: Fast and Flexible Machine Learning Toolkit in C++
Continue reading | Check out the paper and github link
- Flashlight: A C++ standalone library for machine learning
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[D] Deep Learning Framework for C++.
I built and maintain Flashlight, a C++-first library for ML/DL. We built Flashlight to be:
- [R] C++ for Machine Learning
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What is the most used library for AI in C++ ?
I’ve never used it, but Facebook’s flashlight looks interesting
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Python.
Flashlight bro, not flash. Read again
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Mozilla Common Voice Adds 16 New Languages and 4,600 New Hours of Speech
I've had good results with https://github.com/flashlight/flashlight/blob/master/flashli.... Seems to work well with spoken english in a variety of accents. Biggest limitation is that the architecture they have pretrained models for doesn't really work well with clips longer than ~15 seconds, so you have to segment your input files.
- [D] C++ in Machine Learning.
What are some alternatives?
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
netron - Visualizer for neural network, deep learning and machine learning models
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.
tensorflow-wheels - Tensorflow Wheels
PaddleSpeech - Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.
YoloV7-ncnn-Jetson-Nano - YoloV7 for a Jetson Nano using ncnn.
STT - 🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.
mdspan - Reference implementation of mdspan targeting C++23
NeMo - A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
mmaction2 - OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark
DNS-Challenge - This repo contains the scripts, models, and required files for the Deep Noise Suppression (DNS) Challenge.