TensorFlow_Lite_Classification_RPi_zero
flashlight
| TensorFlow_Lite_Classification_RPi_zero | flashlight | |
|---|---|---|
| 1 | 16 | |
| 8 | 5,169 | |
| - | 0.9% | |
| 10.0 | 7.4 | |
| over 1 year ago | about 2 months ago | |
| C++ | C++ | |
| BSD 3-clause "New" or "Revised" License | MIT License |
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TensorFlow_Lite_Classification_RPi_zero
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?
Maple-Syrup-Pi-Camera - Low power smart camera (3D printed) based on the Raspberry Pi Zero W and Google Coral EdgeTPU
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
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.
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.
STT - 🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.
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)
DNS-Challenge - This repo contains the scripts, models, and required files for the Deep Noise Suppression (DNS) Challenge.
oneflow - OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
serving - A flexible, high-performance serving system for machine learning models
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
common-voice - Common Voice is part of Mozilla's initiative to help teach machines how real people speak.
marian - Fast Neural Machine Translation in C++