Top 23 Python Deep Learning Projects
Deep Learning for humansLatest mention: Tensorflow .predict on Pandas rows | reddit.com/r/learnpython | 2020-12-22
Then it's maybe a version bug problem, try to update to the latest tensorflow and keras version. It seems to appear in this issue and hasn't been resolved, switch to Pytorch maybe ?
DeepFaceLab is the leading software for creating deepfakes.Latest mention: [DEEPFAKE] THE LORD OF THE RINGS STARRING CHIRSTOPHER REEVE | reddit.com/r/SFWdeepfakes | 2021-01-15
Clone a voice in 5 seconds to generate arbitrary speech in real-timeLatest mention: I used AI tools to generate audio of SpongeBob rapping a portion of "Gangster's Paradise" | reddit.com/r/videos | 2021-01-05
I've been struggling to get this https://github.com/CorentinJ/Real-Time-Voice-Cloning to work. But I always get stuck on mis-matching python libraries.
PyTorch Tutorial for Deep Learning ResearchersLatest mention: [P] Probabilistic Machine Learning: An Introduction, Kevin Murphy's 2021 e-textbook is out | reddit.com/r/MachineLearning | 2021-01-01
💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython
Deezer source separation library including pretrained models.Latest mention: REQUEST: The hardest part (Studio Acapella) | reddit.com/r/Coldplay | 2021-01-13
I couldn't find the official stems for this track either but you could use a source separation library called Spleeter to extract the vocals. Although it's not ideal, the results can be pretty impressive. Here's a link to the vocal track of The Hardest Part that I extracted using Spleeter: https://we.tl/t-IN4U5Xss5s. I know it's not perfect and you might know about this method already, but I thought I'd share it here anyway just in case.
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.Latest mention: JAX Implementations of Actor-Critic Algorithms | reddit.com/r/reinforcementlearning | 2021-01-10
Folks like me using RLLib have observed this behavior: https://github.com/ray-project/ray/issues/12494
Image-to-Image Translation in PyTorchLatest mention: This Wojak Does Not Exist | news.ycombinator.com | 2020-12-31
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）
🖍️ LabelImg is a graphical image annotation tool and label object bounding boxes in imagesLatest mention: Sitting Posture Identifier using AI | dev.to | 2021-01-08
You get the idea. Images with people having their necks upright would be labelled as neck_good and vice versa. Labelimg made by tzutalin was used for labeling the images. You just need to draw a rectangle around the region, and then assign the respective label.
Face recognition using TensorflowLatest mention: Facial recognition using cluster | reddit.com/r/RASPBERRY_PI_PROJECTS | 2021-01-15
ML training is practically impossible on micro-controllers. Inferencing on the other hand is quite doable, especially if aided by a [TPU coprocessor](https://coral.ai/products/accelerator/). Supposedly with the TPU you can do some quantization-aware training, but I haven't tried this. I am working on a security system that does facial recognition to recognize me and some friends and considers anyone else as an intruder. How I am doing this is by retraining [Facenet](https://github.com/davidsandberg/facenet) with my facial embeddings. Use something like Haar Cascade in OpenCV to get the bounding box for a face and put it through the model to extract face embeddings. You can then save these embeddings as a sort of databases for the faces you want it to recognize during the inferencing phase. After that you can impose something like a SVM classifier to say who in your face database it is. One thing I will note is that the problem is even easier if you are only concerned with one face - in which case it is technically face identification - not recognition. If that is the case, you only need to do a difference calculation between the embeddings you saved during training and the result output from inferencing. If you do end up using the TPU, you can connect to it over USB from inside a container (I only know how to do this in Docker though) too. Hope this was helpful. I am actually looking to use a k8s cluster eventually too as a sort of smart hub for my security system and other devices so I can handle much more traffic (not sure if this is overkill or not on the pi 4s).
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.Latest mention: Weekly Developer Roundup #23 - Sun Nov 22 2020 | dev.to | 2020-11-21
PyTorchLightning/pytorch-lightning (Python): The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
Decensoring Hentai with Deep Neural NetworksLatest mention: Looking for “NEW” uncensored hentai starter pack | reddit.com/r/Hentai_memes | 2021-01-09
Ever heard of the recent technology of decensoring mosaics with deep learning boss?
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
Deep learning library featuring a higher-level API for TensorFlow.
Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.
Mapping a variable-length sentence to a fixed-length vector using BERT modelLatest mention: Needed 100% to pass a safety quiz, need to wait a week to retake | reddit.com/r/mildlyinfuriating | 2021-01-12
You joke but
A MNIST-like fashion product database. Benchmark :point_right:Latest mention: Machine Learning in Light of the Jedi | reddit.com/r/Highrepublic | 2021-01-14
I'm in my third year of a computer science degree and I've literally had an exam for a Neural Computation module and a separate Machine Learning module in the last three days. I worked on a group project to implement a neural network to classify the Fashion-MNIST data set. Not trying to big myself up, I'm still an undergrad so hardly an expert on this stuff, I'm just saying I have a decent grasp of neural networks & machine learning.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.Latest mention: Top 10 Developer Trends, Sun Oct 18 2020 | dev.to | 2020-10-18
microsoft / nni
Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
Official Stanford NLP Python Library for Many Human Languages
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.Latest mention: I forced a bot to read 4000 Dan Andrews Facebook posts and asked it to write its own. Here's what it came up with. | reddit.com/r/melbourne | 2020-12-25
For Danbot V1 (The one using 4,000 posts and GPT-2), I used Kevinzg's Facebook Scraper to get my source material, and used minimaxir's text generator to write the posts.
End-to-End Speech Processing ToolkitLatest mention: Don’t Share That. Yet | news.ycombinator.com | 2021-01-05
Yes, there are really good open source speech to text tools (automatic speech recognition (ASR) is the common name for that).
Kaldi (https://kaldi-asr.org/) is probably the most well known, and supports hybrid NN-HMM and lattice-free MMI models. Kaldi is used by many people both in research and in production.
Lingvo (https://github.com/tensorflow/lingvo) is the open source version of Google speech recognition toolkit, with support mostly for end-to-end models.
ESPNet (https://github.com/espnet/espnet) is good and well known for end-to-end models as well.
RASR (https://github.com/rwth-i6/rasr) + RETURNN (https://github.com/rwth-i6/returnn) are very good as well, both for end-to-end models and hybrid NN-HMM, but they are for non-commercial applications only (or you need a commercial licence) (disclaimer: I work at the university chair which develops these frameworks).
What are some of the best open-source Deep Learning projects in Python? This list will help you:
- 1. keras
- 2. DeepFaceLab
- 3. Real-Time-Voice-Cloning
- 4. pytorch-tutorial
- 5. spaCy
- 6. spleeter
- 7. ray
- 8. pytorch-CycleGAN-and-pix2pix
- 9. Paddle
- 10. labelImg
- 11. facenet
- 12. pytorch-lightning
- 13. DeepCreamPy
- 14. EasyOCR
- 15. tflearn
- 16. Theano
- 17. bert-as-service
- 18. fashion-mnist
- 19. nni
- 20. SerpentAI
- 21. stanza
- 22. textgenrnn
- 23. espnet