Automatic-Parking
deepdrive
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| Automatic-Parking | deepdrive | |
|---|---|---|
| 2 | 1 | |
| 292 | 871 | |
| 5.5% | 0.1% | |
| 2.3 | 0.0 | |
| 11 months ago | 7 months ago | |
| Python | Python | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 or later |
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Automatic-Parking
deepdrive
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Is it possible to train a self driving car on google colab?
I've been trying for a while now and I started thinking it may not be possible. If anyone has managed to train a self-driving car simulator using openai gym on google colab(preferably), or on any remote server (AWS, GCP, ...) please let me know. So far, I tried carla, airsim, svl, deepdrive and they are all equally useless unless run locally with a gui. I'd really appreciate if someone suggests some way that actually can make it possible.
What are some alternatives?
Autonomous-Parking - Automatic parallel parking system including path planning, path tracking, and parallel parking in a designed environment written in python. [Moved to: https://github.com/Pandas-Team/Automatic-Parking]
carla - Open-source simulator for autonomous driving research.
aleatorpy - Python decorator to control randomness of functions, methods and properties
simulator - A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles
PythonRobotics - Python sample codes for robotics algorithms.
AirSim - Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
waymo-motion-prediction-challenge-2022-multipath-plus-plus - Solution for Waymo Motion Prediction Challenge 2022. Our implementation of MultiPath++
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
CppRobotics - Header-only C++ library for robotics, control, and path planning algorithms. Work in progress, contributions are welcome!
tensorforce - Tensorforce: a TensorFlow library for applied reinforcement learning
simglucose - A Type-1 Diabetes simulator implemented in Python for Reinforcement Learning purpose
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)