114 lines
3.4 KiB
Markdown
114 lines
3.4 KiB
Markdown
# ScenarioNet
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**Open-Source Platform for Large-Scale Traffic Scenario Simulation and Modeling**
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[**Webpage**](https://metadriverse.github.io/scenarionet/) |
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[**Code**](https://github.com/metadriverse/scenarionet) |
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[**Video**](https://youtu.be/3bOqswXP6OA) |
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[**Paper**](http://arxiv.org/abs/2306.12241) |
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ScenarioNet allows users to load scenarios from real-world dataset like Waymo, nuPlan, nuScenes, l5 and synthetic
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dataset such as procedural generated ones and safety-critical ones generated by adversarial attack.
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The built database provides tools for building training and test sets for ML applications.
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Powered by [MetaDrive Simulator](https://github.com/metadriverse/metadrive), the scenarios can be reconstructed for
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various applications like AD stack test, reinforcement learning, imitation learning, scenario generation and so on.
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## Installation
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```
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git clone git@github.com:metadriverse/scenarionet.git
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cd scenarionet
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pip install -e .
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```
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## Usage
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We provide some explanation and demo for all scripts here.
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**You are encouraged to try them on your own, add ```-h``` or ```--help``` argument to know more details about these
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scripts.**
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### Convert
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**Waymo**: the following script can convert Waymo tfrecord to Metadrive scenario description and
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store them at directory ./waymo
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```
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python -m scenarionet.convert_waymo -d waymo --raw_data_path /path/to/tfrecords --num_workers=16
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```
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**nuPlan**: the following script will convert nuPlan split containing .db files to Metadrive scenario description and
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store them at directory ./nuplan
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```
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python -m scenarionet.convert_nuplan -d nuplan -raw_data_path /path/to/.db files --num_workers=16
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```
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**nuScenes**: as nuScenes split can be read by specifying version like v1.0-mini and v1.0-training, the following script
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will convert all scenarios in that split
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```
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python -m scenarionet.convert_nuscenes -d nuscenes --version v1.0-mini --num_workers=16
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```
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**PG**: the following script can generate 10000 scenarios stored at directory ./pg
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```
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python -m scenarionet.scripts.convert_pg -d pg --num_workers=16 --num_scenarios=10000
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```
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### Merge & move
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For merging two or more database, use
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```
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python -m scenarionet.merge_database -d /destination/path --from /database1 /2 ...
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```
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As a database contains a path mapping, one should move database folder with the following script instead of ```cp```
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command.
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Using ```--copy_raw_data``` will copy the raw scenario file into target directory and cancel the virtual mapping.
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```
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python -m scenarionet.copy_database --to /destination/path --from /source/path
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```
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### Verify
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The following scripts will check whether all scenarios exist or can be loaded into simulator.
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The missing or broken scenarios will be recorded and stored into the error file. Otherwise, no error file will be
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generated.
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With teh error file, one can build a new database excluding or including the broken or missing scenarios.
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**Existence check**
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```
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python -m scenarionet.check_existence -d /database/to/check --error_file_path /error/file/path
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```
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**Runnable check**
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```
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python -m scenarionet.check_simulation -d /database/to/check --error_file_path /error/file/path
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```
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**Generating new database**
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```
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python -m scenarionet.generate_from_error_file -d /new/database/path --file /error/file/path
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```
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### visualization
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Visualizing the simulated scenario
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```
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python -m scenarionet.run_simulation -d /path/to/database --render --scenario_index
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```
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