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openpilot is an operating system for robotics. Currently, it upgrades the driver assistance system on 300+ supported cars.
🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
A toolkit for developing and comparing reinforcement learning algorithms.
Instant voice cloning by MIT and MyShell. Audio foundation model.
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
TensorFlow CNN for fast style transfer ⚡🖥🎨🖼
A faster pytorch implementation of faster r-cnn
A tool that automatically formats Python code to conform to the PEP 8 style guide.
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
A series of convenience functions to make basic image processing operations such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and Python.
Example code for Fluent Python, 2nd edition (O'Reilly 2022)
Modularized Implementation of Deep RL Algorithms in PyTorch
A minimalist environment for decision-making in autonomous driving
Hands-on Deep Reinforcement Learning, published by Packt
Building a Real-time Hand-Detector using Neural Networks (SSD) on Tensorflow
A collection of reference environments for offline reinforcement learning
An offline deep reinforcement learning library
[PAMI'23] TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving; [CVPR'21] Multi-Modal Fusion Transformer for End-to-End Autonomous Driving
Live training loss plot in Jupyter Notebook for Keras, PyTorch and others
A generalized framework for prototyping full-stack cooperative driving automation applications under CARLA+SUMO.
League Director is a tool for staging and recording videos from League of Legends replays
Offline Reinforcement Learning (aka Batch Reinforcement Learning) on Atari 2600 games
PyTorch Agent Net: reinforcement learning toolkit for pytorch
Distributed Machine Learning Patterns from Manning Publications by Yuan Tang https://bit.ly/2RKv8Zo
Multi-Agent Connected Autonomous Driving (MACAD) Gym environments for Deep RL. Code for the paper presented in the Machine Learning for Autonomous Driving Workshop at NeurIPS 2019:
A basic 2D maze environment where an agent start from the top left corner and try to find its way to the bottom left corner.