Metadata-Version: 2.1
Name: carla-birdeye-view
Version: 1.0.11
Summary: Bird-eye's view for CARLA simulator
Home-page: https://github.com/deepsense-ai/carla-birdeye-view
Author: Michał Martyniak
Author-email: michal.martyniak@linux.pl
License: MIT
Description: ![](https://img.shields.io/badge/contributions%20welcome-forking&gt;copying-orange.svg?style=popout-square)
        ![](https://img.shields.io/badge/release-v1.0-brightgreen.svg?style=popout-square)
        ![](https://img.shields.io/badge/pypi-v1.0-brightgreen.svg?style=popout-square)
        ![](https://img.shields.io/badge/CARLA-0.9.6+-blue.svg?style=popout-square)
        ![](https://img.shields.io/badge/python-3.6%20|%203.7%20|3.8-blue.svg?style=popout-square)
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        ## Bird eye's view for CARLA
        
        
        Freeway-oriented shape | *[Learning By Cheating](https://arxiv.org/abs/1912.12294)*-like shape
        :-------------------------:|:-------------------------:
        ![cruising](https://user-images.githubusercontent.com/64484917/80508193-04edde00-8978-11ea-956d-721e50a6a3c9.gif) | ![square-cruising](https://user-images.githubusercontent.com/64484917/80508095-e4258880-8977-11ea-8601-0e88942711ff.gif)
        
        (GIFs above present feature maps after applying `as_rgb()` function)
        
        ### Motivation
        
        During our [research](https://arxiv.org/abs/1911.12905) we found a very inspiring paper called [Learning By Cheating]( https://arxiv.org/abs/1912.12294). **Bird-eye's view** is made specifically to **learn faster thanks to much simpler, 2D world representation** (cheating oracle) which we think fits well in **Reinforcement Learning** setup.
        
        This repository is an almost complete reimplementation that gives better performance and compatibility with most recent versions of CARLA. You can use it out-of-the-box as input for your model, and if necessary convert and visualize into RGB.
        
        
        ### Features
        - **one-hot 3D feature map** (8x2D layers, each representing other entities, e.g. road layer, pedestrians layer) - made specifically to feed your CNN
        - feature map **can be converted to an RGB** image
        - layers can be easily removed
        - caching mechanism for static layers like: roads and lanes
        - using **OpenCV rendering** (efficient, multi-threading friendly) instead of slow Pygame method
        - huge **FPS speedup** thanks to restricted rendering (only agent's surroundings, not whole map)
        - all CARLA maps are supported out-of-the-box, custom maps with valid OpenDrive file made in RoadRunner are also supported
        - current implementation is specifically  adjusted for highway scenarios (prolonged shape), but other shapes and crops are easy to implement 
        
        ### Installation
        ```bash
        pip install carla-birdeye-view
        ```
        
        ### How to run
        Make sure that `PYTHONPATH` env variable contains CARLA distribution egg, so that `carla` package can be imported.
        ```bash
        # Launch server instance
        ./CarlaUE4.sh
        
        # (optional) For CARLA 0.9.8+ you may get additional performance improvement with this
        python PythonAPI/util/config.py --no-rendering
        
        # Preview while cruising on autopilot (birdview/__main__.py)
        birdview-demo
        ```
        
        ### Development
        
        ```bash
        # From repo root
        python -m birdview
        ```
        
        
        ### Contribution and feedback
        We'd :heart: to collct any feedback, issues and pull requests!
        
        ### Credits
        
        Project born at [deepsense.ai](deepsense.ai), made by:
        
        ![](https://avatars2.githubusercontent.com/u/12485656?s=22&v=4) [Michał Martyniak (@micmarty)](https://micmarty.github.io)
        
        
        
Keywords: CARLA,birdview,bird-eye's view,Reinforcement Learning,RL
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
