Python Deep Learning

Open-source Python projects categorized as Deep Learning

Top 23 Python Deep Learning Projects

  • keras

    Deep Learning for humans

    Latest 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

    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
  • Real-Time-Voice-Cloning

    Clone a voice in 5 seconds to generate arbitrary speech in real-time

    Latest 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

    PyTorch Tutorial for Deep Learning Researchers

    Latest mention: [P] Probabilistic Machine Learning: An Introduction, Kevin Murphy's 2021 e-textbook is out | reddit.com/r/MachineLearning | 2021-01-01
  • spaCy

    💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython

  • spleeter

    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.

  • ray

    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

  • pytorch-CycleGAN-and-pix2pix

    Image-to-Image Translation in PyTorch

    Latest mention: This Wojak Does Not Exist | news.ycombinator.com | 2020-12-31

    https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix

  • Paddle

    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

    🖍️ LabelImg is a graphical image annotation tool and label object bounding boxes in images

    Latest 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.

  • facenet

    Face recognition using Tensorflow

    Latest 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).

  • pytorch-lightning

    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.

  • DeepCreamPy

    Decensoring Hentai with Deep Neural Networks

    Latest 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?

  • EasyOCR

    Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

  • tflearn

    Deep learning library featuring a higher-level API for TensorFlow.

  • Theano

    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.

  • bert-as-service

    Mapping a variable-length sentence to a fixed-length vector using BERT model

    Latest 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

  • fashion-mnist

    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.

  • nni

    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

  • SerpentAI

    Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!

  • stanza

    Official Stanford NLP Python Library for Many Human Languages

  • textgenrnn

    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.

  • espnet

    End-to-End Speech Processing Toolkit

    Latest 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).

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).