[
  {
    "path": ".gitmodules",
    "content": "[submodule \"leaderboard\"]\n\tpath = leaderboard\n\turl = https://github.com/bradyz/leaderboard.git\n[submodule \"scenario_runner\"]\n\tpath = scenario_runner\n\turl = https://github.com/bradyz/scenario_runner.git\n[submodule \"carla_project\"]\n\tpath = carla_project\n\turl = https://github.com/bradyz/carla_project.git\n"
  },
  {
    "path": "README.md",
    "content": "# Learning by Cheating\n\n![teaser](https://github.com/dianchen96/LearningByCheating/blob/release-0.9.6/figs/fig1.png \"Pipeline\")\n> [**Learning by Cheating**](https://arxiv.org/abs/1912.12294)    \n> Dian Chen, Brady Zhou, Vladlen Koltun, Philipp Krähenbühl,        \n> [Conference on Robot Learning](https://www.robot-learning.org) (CoRL 2019)      \n> _arXiv 1912.12294_\n\nIf you find our repo to be useful in your research, please consider citing our work\n```\n@inproceedings{chen2019lbc\n  author    = {Dian Chen and Brady Zhou and Vladlen Koltun and Philipp Kr\\\"ahenb\\\"uhl},\n  title     = {Learning by Cheating},\n  booktitle = {Conference on Robot Learning (CoRL)},\n  year      = {2019},\n}\n```\n\nThe code in this repo is based off of [link](https://github.com/dianchen96/LearningByCheating), which contains the code for the NoCrash and CoRL 17 benchmarks.\n\n## Installation\n\nClone this repo with all its submodules\n\n```bash\ngit clone https://github.com/bradyz/2020_CARLA_challenge.git --recursive\n```\n\nAll python packages used are specified in `carla_project/requirements.txt`.\n\nThis code uses CARLA 0.9.9 and works with CARLA 0.9.8, **0.9.10.1**.\n\nYou will also need to install CARLA 0.9.10.1, along with the additional maps.\nSee [link](https://github.com/carla-simulator/carla/releases/tag/0.9.10.1) for more instructions.\n\n## Dataset\n\nWe provide a dataset of over 70k samples collected over the 75 routes provided in `leaderboard/data/routes_*.xml`.\n\n[Link to full dataset (9 GB)](https://drive.google.com/file/d/1dwt9_EvXB1a6ihlMVMyYx0Bw0mN27SLy/view?usp=sharing).\n\n![sample](assets/sample_route.gif)\n\nThe dataset is collected using `leaderboard/team_code/autopilot.py`, using painfully hand-designed rules (i.e. if pedestrian is 5 meters ahead, then brake).\n\nAdditionally, we change the weather for a single route once every couple of seconds to add visual diversity as a sort of on-the-fly augmentation.\nThe simulator is run at 20 FPS, and we save the following data at 2 Hz.\n\n* Left, Center, and Right RGB Images at 256 x 144 resolution\n* A semantic segmentation rendered in the overhead view\n* World position and heading\n* Raw control (steer, throttle, brake)\n\nNote: the overhead view does nothing to address obstructions, like overhead highways, etc.\n\nWe provide a sample trajectory in `sample_data`, which you can visualize by running\n\n```\npython3 -m carla_project.src.dataset sample_data/route_00/\n```\n\n## Data Collection\n\nThe autopilot that we used to collect the data can use a lot of work and currently does not support stop signs.\n\nIf you're interested in recollecting data after changing the autopilot's driving behavior in `leaderboard/team_code/autopilot.py`, you can collect your own dataset by running the following.\n\nFirst, spin up a CARLA server\n\n```bash\n./CarlaUE4.sh -quality-level=Epic -world-port=2000 -resx=800 -resy=600 -opengl\n```\n\nthen run the agent.\n\n```bash\nexport CARLA_ROOT=/home/bradyzhou/software/CARLA_0.9.10.1           # change to where you installed CARLA\nexport PORT=2000                                                    # change to port that CARLA is running on\nexport ROUTES=leaderboard/data/routes_training/route_19.xml         # change to desired route\nexport TEAM_AGENT=auto_pilot.py                                     # no need to change\nexport TEAM_CONFIG=sample_data                                      # change path to save data\n\n./run_agent.sh\n```\n\n## Run a pretrained model\n\nDownload the checkpoint from our [Wandb project](https://app.wandb.ai/bradyz/2020_carla_challenge_lbc).\n\nNavigate to one of the runs, like https://app.wandb.ai/bradyz/2020_carla_challenge_lbc/runs/command_coefficient=0.01_sample_by=even_stage2/files\n\nGo to the \"files\" tab, and download the model weights, named \"epoch=24.ckpt\", and pass in the file path as the `TEAM_CONFIG` below.\n\nSpin up a CARLA server\n\n```bash\n./CarlaUE4.sh -quality-level=Epic -world-port=2000 -resx=800 -resy=600 -opengl\n```\n\nthen run the agent.\n\n```bash\nexport CARLA_ROOT=/home/bradyzhou/software/CARLA_0.9.10.1           # change to where you installed CARLA\nexport PORT=2000                                                    # change to port that CARLA is running on\nexport ROUTES=leaderboard/data/routes_training/route_19.xml         # change to desired route\nexport TEAM_AGENT=image_agent.py                                    # no need to change\nexport TEAM_CONFIG=model.ckpt                                       # change path to checkpoint\nexport HAS_DISPLAY=1                                                # set to 0 if you don't want a debug window\n\n./run_agent.sh\n```\n\n## Training models from scratch\n\nFirst, download and extract our provided dataset.\n\nThen run the stage 1 training of the privileged agent.\n\n```python\npython3 -m carla_project.src.map_model --dataset_dir /path/to/data --hack\n```\n\nWe use wandb for logging, so navigate to the generated experiment page to visualize training.\n\n**Important**: If you're interested in tuning hyperparameters, see `carla_project/src/map_model.py` for more detail.  \nTo see what hyperparameters we used for our models, you can see all of them by navigating to the corresponding [wandb run config](https://wandb.ai/bradyz/2020_carla_challenge_lbc/runs/command_coefficient=0.01_sample_by=even_stage2/overview).\n\n![sample](assets/stage_1.gif)\n\nTraining the sensorimotor agent (acts only on raw images) is similar, and can be done by\n\n```python\npython3 -m carla_project.src.image_model --dataset_dir /path/to/data\n```\n\n## Docker\n\nBuild the docker container to submit, make sure to edit `scripts/Dockerfile.master` appropriately.\n\n```bash\nsudo ./scripts/make_docker.sh\n```\n\nSpin up a CARLA server\n\n```bash\n./CarlaUE4.sh -quality-level=Epic -world-port=2000 -resx=800 -resy=600 -opengl\n```\n\nNow you can either run the docker container or run it interactively.\n\nTo run the docker container,\n\n```bash\nsudo docker run --net=host --gpus all -e NVIDIA_VISIBLE_DEVICES=0 -e REPETITIONS=1 -e DEBUG_CHALLENGE=0 -e PORT=2000 -e ROUTES=leaderboard/data/routes_devtest.xml -e CHECKPOINT_ENDPOINT=tmp.txt -e SCENARIOS=leaderboard/data/all_towns_traffic_scenarios_public.json leaderboard-user:latest ./leaderboard/scripts/run_evaluation.sh\n```\n\nOr if you need to debug something, you can run it interactively\n\n```bash\nsudo docker run --net=host --gpus all -it leaderboard-user:latest /bin/bash\n```\n\nRun the evaluation through the interactive shell.\n\n```bash\nexport PORT=2000\nexport DEBUG_CHALLENGE=0\nexport REPETITIONS=1\nexport ROUTES=leaderboard/data/routes_devtest/route_00.xml         # change to desired route\nexport CHECKPOINT_ENDPOINT=tmp.txt\nexport SCENARIOS=leaderboard/data/all_towns_traffic_scenarios_public.json\n\nconda activate python37\n\n./leaderboard/scripts/run_evaluation.sh\n```\n"
  },
  {
    "path": "run_agent.sh",
    "content": "#!/bin/bash\nexport PYTHONPATH=$PYTHONPATH:$CARLA_ROOT/PythonAPI/carla\nexport PYTHONPATH=$PYTHONPATH:$CARLA_ROOT/PythonAPI/carla/dist/carla-0.9.10-py3.7-linux-x86_64.egg\nexport PYTHONPATH=$PYTHONPATH:leaderboard\nexport PYTHONPATH=$PYTHONPATH:leaderboard/team_code\nexport PYTHONPATH=$PYTHONPATH:scenario_runner\n\nif [ -d \"$TEAM_CONFIG\" ]; then\n    CHECKPOINT_ENDPOINT=\"$TEAM_CONFIG/$(basename $ROUTES .xml).txt\"\nelse\n    CHECKPOINT_ENDPOINT=\"$(dirname $TEAM_CONFIG)/$(basename $ROUTES .xml).txt\"\nfi\n\npython3 leaderboard/leaderboard/leaderboard_evaluator.py \\\n--track=SENSORS \\\n--scenarios=leaderboard/data/all_towns_traffic_scenarios_public.json  \\\n--agent=${TEAM_AGENT} \\\n--agent-config=${TEAM_CONFIG} \\\n--routes=${ROUTES} \\\n--checkpoint=${CHECKPOINT_ENDPOINT} \\\n--port=${PORT}\n\necho \"Done. See $CHECKPOINT_ENDPOINT for detailed results.\"\n"
  },
  {
    "path": "sample_data/route_00/measurements/0000.json",
    "content": "{'x': -226.46817199206743, 'y': 338.76315306981644, 'theta': 0.0005980199784971774, 'speed': 3.3797341881785896e-08, 'target_speed': 7.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0001.json",
    "content": "{'x': -226.46817199206743, 'y': 338.76315306981644, 'theta': 0.0005980199784971774, 'speed': 3.352230199313333e-08, 'target_speed': 7.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0002.json",
    "content": "{'x': -226.46817199206743, 'y': 338.76315306981644, 'theta': 0.0005980199784971774, 'speed': -4.4254745117890757e-08, 'target_speed': 7.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0003.json",
    "content": "{'x': -226.3955796335324, 'y': 338.76315306981644, 'theta': 0.0009134905994869769, 'speed': 1.1073648751585912, 'target_speed': 7.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': -0.0, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0004.json",
    "content": "{'x': -225.19018341192762, 'y': 338.7655334409221, 'theta': 0.0013372133253142238, 'speed': 3.2242275164501613, 'target_speed': 7.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': -0.001, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0005.json",
    "content": "{'x': -223.24619833424183, 'y': 338.7608947689973, 'theta': 6.2812323570251465, 'speed': 4.484101990680977, 'target_speed': 7.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.003, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0006.json",
    "content": "{'x': -220.7225743557678, 'y': 338.75619506205896, 'theta': 6.282495021820068, 'speed': 5.548496461942215, 'target_speed': 7.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.004, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0007.json",
    "content": "{'x': -218.01816523498735, 'y': 338.7507018979989, 'theta': 6.275488376617432, 'speed': 3.7197551879255757, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0055, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0008.json",
    "content": "{'x': -217.50249628750353, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -0.01753278274022307, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.007, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0009.json",
    "content": "{'x': -217.49488150422113, 'y': 338.7487182553244, 'theta': 6.275613307952881, 'speed': -0.0041927202363261145, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0075, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0010.json",
    "content": "{'x': -217.4941337571747, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -0.00022642588155692982, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.008, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0011.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -3.757994374547926e-05, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0012.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -1.9669654469562847e-06, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0013.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -7.362043902331187e-07, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0014.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -7.33916745849816e-08, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0015.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -4.7163590824656944e-08, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0016.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -2.6494531292559518e-08, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0017.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -4.812141621617573e-09, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0018.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -9.20385336979367e-09, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0019.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': 2.3740653472839056e-08, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0020.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -1.128490337153138e-08, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0021.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': 5.178855062527387e-08, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0022.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -4.8126899073037395e-09, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0023.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -1.13892073934647e-08, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0024.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -1.2318421021989945e-08, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0025.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': 4.105473234744735e-08, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0026.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': 1.5888131301566665e-09, 'target_speed': 0.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.0085, 'throttle': 0.0, 'brake': True}"
  },
  {
    "path": "sample_data/route_00/measurements/0027.json",
    "content": "{'x': -217.4940421994759, 'y': 338.7487182553244, 'theta': 6.275605201721191, 'speed': -7.710912178132837e-10, 'target_speed': 7.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.017, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0028.json",
    "content": "{'x': -217.40336675088193, 'y': 338.7483215268933, 'theta': 6.277693748474121, 'speed': 0.6541252962001288, 'target_speed': 7.0, 'x_command': -209.17174534259908, 'y_command': 338.77359008151757, 'command': 4, 'steer': 0.014, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0029.json",
    "content": "{'x': -216.52907056233923, 'y': 338.7536315853938, 'theta': 0.001035801018588245, 'speed': 2.5728384660417736, 'target_speed': 7.0, 'x_command': -195.17150706875657, 'y_command': 325.6698608337601, 'command': 4, 'steer': 0.008, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0030.json",
    "content": "{'x': -214.90045335991232, 'y': 338.76751708346694, 'theta': 0.006224398966878653, 'speed': 3.8815104007893946, 'target_speed': 7.0, 'x_command': -195.17150706875657, 'y_command': 325.6698608337601, 'command': 4, 'steer': -0.0, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0031.json",
    "content": "{'x': -212.65488701192297, 'y': 338.77636718118407, 'theta': 0.003068801248446107, 'speed': 5.034492407600175, 'target_speed': 7.0, 'x_command': -195.17150706875657, 'y_command': 325.6698608337601, 'command': 1, 'steer': -0.001, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0032.json",
    "content": "{'x': -209.88883114681377, 'y': 338.77774047216667, 'theta': 6.282840251922607, 'speed': 5.921043552742379, 'target_speed': 7.0, 'x_command': -195.17150706875657, 'y_command': 325.6698608337601, 'command': 1, 'steer': -0.0, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0033.json",
    "content": "{'x': -206.7336451425754, 'y': 338.755340569794, 'theta': 6.2716875076293945, 'speed': 6.650376741956694, 'target_speed': 4, 'x_command': -195.17150706875657, 'y_command': 325.6698608337601, 'command': 1, 'steer': -0.067, 'throttle': 0.109375, 'brake': False}"
  },
  {
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    "path": "sample_data/route_00/measurements/0450.json",
    "content": "{'x': -124.71476000222813, 'y': 1.9494270084480163, 'theta': 0.00048828125, 'speed': 7.1671050600896695, 'target_speed': 7.0, 'x_command': -91.60394999982427, 'y_command': 1.9419636724793692, 'command': 4, 'steer': 0.002, 'throttle': 0.08049525211670379, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0451.json",
    "content": "{'x': -121.49891124975527, 'y': 1.9561527966298826, 'theta': 0.0015440810238942504, 'speed': 6.031691016460928, 'target_speed': 7.0, 'x_command': -91.60394999982427, 'y_command': 1.9419636724793692, 'command': 4, 'steer': -0.0, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0452.json",
    "content": "{'x': -118.4332896176899, 'y': 1.9552521704035133, 'theta': 6.282495021820068, 'speed': 6.306721833708328, 'target_speed': 7.0, 'x_command': -91.60394999982427, 'y_command': 1.9419636724793692, 'command': 4, 'steer': 0.0, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0453.json",
    "content": "{'x': -115.02245468940544, 'y': 1.960314750607499, 'theta': 0.0021836606319993734, 'speed': 7.119129070675858, 'target_speed': 7.0, 'x_command': -91.60394999982427, 'y_command': 1.9419636724793692, 'command': 4, 'steer': -0.003, 'throttle': 0.08489955638098402, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0454.json",
    "content": "{'x': -111.70308145674684, 'y': 1.9704083203075933, 'theta': 0.003921481780707836, 'speed': 6.196536055482532, 'target_speed': 7.0, 'x_command': -91.60394999982427, 'y_command': 1.9419636724793692, 'command': 4, 'steer': -0.008, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0455.json",
    "content": "{'x': -108.59898005425619, 'y': 1.9735459087808178, 'theta': 0.0, 'speed': 6.349978134088587, 'target_speed': 7.0, 'x_command': -91.60394999982427, 'y_command': 1.9419636724793692, 'command': 4, 'steer': -0.005, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0456.json",
    "content": "{'x': -105.17634773755582, 'y': 1.9516910313199656, 'theta': 6.278040885925293, 'speed': 7.185473595178107, 'target_speed': 7.0, 'x_command': -91.60394999982427, 'y_command': 1.9419636724793692, 'command': 4, 'steer': 0.001, 'throttle': 0.08563349997398492, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0457.json",
    "content": "{'x': -101.86113868901533, 'y': 1.942475199635089, 'theta': 6.281172275543213, 'speed': 6.097931954158989, 'target_speed': 7.0, 'x_command': -91.60394999982427, 'y_command': 1.9419636724793692, 'command': 4, 'steer': 0.001, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0458.json",
    "content": "{'x': -98.88594963416959, 'y': 1.9342013596093173, 'theta': 6.280359268188477, 'speed': 6.088933953224664, 'target_speed': 7.0, 'x_command': -49.60330090480868, 'y_command': 1.9547302721487383, 'command': 4, 'steer': 0.004, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0459.json",
    "content": "{'x': -95.63176809971029, 'y': 1.9207265376250557, 'theta': 6.279371738433838, 'speed': 6.9283395060041055, 'target_speed': 7.0, 'x_command': -49.60330090480868, 'y_command': 1.9547302721487383, 'command': 4, 'steer': 0.009, 'throttle': 0.36616304389376575, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0460.json",
    "content": "{'x': -92.17152088906577, 'y': 1.9217460153778245, 'theta': 0.0003452669770922512, 'speed': 6.596248036437406, 'target_speed': 7.0, 'x_command': -49.60330090480868, 'y_command': 1.9547302721487383, 'command': 4, 'steer': 0.005, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0461.json",
    "content": "{'x': -89.11083673775262, 'y': 1.9375100134217127, 'theta': 0.0058593833819031715, 'speed': 6.12891563241729, 'target_speed': 7.0, 'x_command': -49.60330090480868, 'y_command': 1.9547302721487383, 'command': 4, 'steer': -0.003, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0462.json",
    "content": "{'x': -85.8698300830936, 'y': 1.9536088703225778, 'theta': 0.0023670317605137825, 'speed': 6.783157989639636, 'target_speed': 7.0, 'x_command': -49.60330090480868, 'y_command': 1.9547302721487383, 'command': 4, 'steer': -0.003, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0463.json",
    "content": "{'x': -82.36247458704038, 'y': 1.9521121977308162, 'theta': 6.282149791717529, 'speed': 6.6613357158105435, 'target_speed': 7.0, 'x_command': -49.60330090480868, 'y_command': 1.9547302721487383, 'command': 4, 'steer': -0.001, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0464.json",
    "content": "{'x': -79.2547272789586, 'y': 1.9504520891603574, 'theta': 0.0009134905994869769, 'speed': 6.149916718387963, 'target_speed': 7.0, 'x_command': -49.60330090480868, 'y_command': 1.9547302721487383, 'command': 4, 'steer': -0.003, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0465.json",
    "content": "{'x': -76.02015072303631, 'y': 1.9418799875708617, 'theta': 6.279435157775879, 'speed': 6.754148725200663, 'target_speed': 7.0, 'x_command': -49.60330090480868, 'y_command': 1.9547302721487383, 'command': 4, 'steer': 0.003, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0466.json",
    "content": "{'x': -72.47677332688953, 'y': 1.9376970528195105, 'theta': 0.001091830083169043, 'speed': 7.015113105744557, 'target_speed': 7.0, 'x_command': -49.60330090480868, 'y_command': 1.9547302721487383, 'command': 4, 'steer': 0.001, 'throttle': 0.07298502653689104, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0467.json",
    "content": "{'x': -69.36506404187817, 'y': 1.938217520658387, 'theta': 6.282840251922607, 'speed': 5.964717504839965, 'target_speed': 7.0, 'x_command': -49.60330090480868, 'y_command': 1.9547302721487383, 'command': 4, 'steer': 0.003, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0468.json",
    "content": "{'x': -66.26770059879027, 'y': 1.9428750274736335, 'theta': 0.003686444601044059, 'speed': 6.429802398307369, 'target_speed': 7.0, 'x_command': -49.60330090480868, 'y_command': 1.9547302721487383, 'command': 4, 'steer': -0.001, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0469.json",
    "content": "{'x': -62.79649619673312, 'y': 1.9500118492834577, 'theta': 0.0, 'speed': 7.191577066323018, 'target_speed': 7.0, 'x_command': -49.60330090480868, 'y_command': 1.9547302721487383, 'command': 4, 'steer': 0.001, 'throttle': 0.07960881254449988, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0470.json",
    "content": "{'x': -59.50491916888778, 'y': 1.9560453890793275, 'theta': 0.004041249398142099, 'speed': 6.29340054426118, 'target_speed': 7.0, 'x_command': -49.60330090480868, 'y_command': 1.9547302721487383, 'command': 4, 'steer': -0.004, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "sample_data/route_00/measurements/0471.json",
    "content": "{'x': -56.264257903521305, 'y': 1.9593985079913425, 'theta': 0.0005980199784971774, 'speed': 6.6995370139187544, 'target_speed': 7.0, 'x_command': -49.60330090480868, 'y_command': 1.9547302721487383, 'command': 4, 'steer': -0.002, 'throttle': 0.75, 'brake': False}"
  },
  {
    "path": "scripts/Dockerfile.master",
    "content": "FROM nvidia/cuda:9.0-cudnn7-devel-ubuntu16.04\n\nARG HTTP_PROXY\nARG HTTPS_PROXY\nARG http_proxy\n\nRUN apt-get update && apt-get install --reinstall -y locales && locale-gen en_US.UTF-8\nENV LANG en_US.UTF-8\nENV LANGUAGE en_US\nENV LC_ALL en_US.UTF-8\n\nRUN apt-get update && apt-get install -y --no-install-recommends \\\n         build-essential \\\n         cmake \\\n         git \\\n         curl \\\n         vim \\\n         ca-certificates \\\n         libjpeg-dev \\\n\t     libpng16-16 \\\n\t     libtiff5 \\\n         libpng-dev \\\n         python-dev \\\n         python3.5 \\\n         python3.5-dev \\\n         python-networkx \\\n         python-setuptools \\\n         python3-setuptools \\\n         python-pip \\\n         python3-pip && \\\n         pip install --upgrade pip && \\\n         pip3 install --upgrade pip && \\\n         rm -rf /var/lib/apt/lists/*\n\n# installing conda\nRUN curl -o ~/miniconda.sh -LO https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh  && \\\n     chmod +x ~/miniconda.sh && \\\n     ~/miniconda.sh -b -p /opt/conda && \\\n     rm ~/miniconda.sh && \\\n     /opt/conda/bin/conda clean -ya && \\\n     /opt/conda/bin/conda create -n python37 python=3.7 numpy networkx scipy six requests\n\nRUN packages='py_trees==0.8.3 shapely six dictor requests' \\\n\t&& pip3 install ${packages}\n\nWORKDIR /workspace\nCOPY .tmp/PythonAPI /workspace/CARLA/PythonAPI\nENV CARLA_ROOT /workspace/CARLA\n\nENV PATH \"/workspace/CARLA/PythonAPI/carla/dist/carla-0.9.9-py3.7-linux-x86_64.egg\":/opt/conda/envs/python37/bin:/opt/conda/envs/bin:$PATH\n\n# adding CARLA egg to default python environment\nRUN pip install --user setuptools py_trees==0.8.3 psutil shapely six dictor requests\n\nENV SCENARIO_RUNNER_ROOT \"/workspace/scenario_runner\"\nENV LEADERBOARD_ROOT \"/workspace/leaderboard\"\nENV TEAM_CODE_ROOT \"/workspace/team_code\"\nENV PYTHONPATH \"/workspace/CARLA/PythonAPI/carla/dist/carla-0.9.9-py3.7-linux-x86_64.egg\":\"${SCENARIO_RUNNER_ROOT}\":\"${CARLA_ROOT}/PythonAPI/carla\":\"${LEADERBOARD_ROOT}\":${PYTHONPATH}\n\nCOPY .tmp/scenario_runner /workspace/scenario_runner\nCOPY .tmp/leaderboard /workspace/leaderboard\nCOPY .tmp/team_code ${TEAM_CODE_ROOT}\n\nRUN mkdir -p /workspace/results\nRUN chmod +x /workspace/leaderboard/scripts/run_evaluation.sh\n\n########################################################################################################################\n########################################################################################################################\n############                                BEGINNING OF USER COMMANDS                                      ############\n########################################################################################################################\n########################################################################################################################\n\nCOPY .tmp/carla_project /workspace/carla_project\n\nENV PYTHONPATH \"/workspace/CARLA/PythonAPI/carla/dist/carla-0.9.9-py3.7-linux-x86_64.egg\":${PYTHONPATH}\nENV PYTHONPATH \"/workspace/\":${PYTHONPATH}\nENV TEAM_AGENT /workspace/team_code/image_agent.py\nENV TEAM_CONFIG /workspace/team_code/model.ckpt\nENV CHALLENGE_PHASE_CODENAME SENSORS\n\nRUN apt-get update && apt-get install -y --no-install-recommends \\\n         libgtk2.0-dev\n\nENV PATH=\"/opt/conda/bin:${PATH}\"\nRUN /opt/conda/envs/python37/bin/pip install -r /workspace/carla_project/requirements.txt\nRUN /opt/conda/bin/conda install -c anaconda libgcc=7.2.0\nRUN /opt/conda/bin/conda init bash\n\nRUN cp /opt/conda/lib/libstdc++.so.6.0.26 /usr/lib/x86_64-linux-gnu/libstdc++.so.6\nENV CONDA_DEFAULT_ENV python37\nENV PATH /opt/conda/envs/python37/bin:$PATH\n\n########################################################################################################################\n########################################################################################################################\n############                                   END OF USER COMMANDS                                         ############\n########################################################################################################################\n########################################################################################################################\n\nENV SCENARIOS ${LEADERBOARD_ROOT}/data/all_towns_traffic_scenarios_public.json\nENV ROUTES ${LEADERBOARD_ROOT}/data/routes_training.xml\nENV REPETITIONS 1\nENV CHECKPOINT_ENDPOINT /workspace/results/results.json\nENV DEBUG_CHALLENGE 0\n\nENV HTTP_PROXY \"\"\nENV HTTPS_PROXY \"\"\nENV http_proxy \"\"\nENV https_proxy \"\"\n\nCMD [\"/bin/bash\"]\n"
  },
  {
    "path": "scripts/make_docker.sh",
    "content": "#!/bin/bash\n\nCARLA_ROOT=/home/bradyzhou/software/CARLA_0.9.9\nSCENARIO_RUNNER_ROOT=/home/bradyzhou/code/2020_CARLA_challenge/scenario_runner\nLEADERBOARD_ROOT=/home/bradyzhou/code/2020_CARLA_challenge/leaderboard\nTEAM_CODE_ROOT=/home/bradyzhou/code/2020_CARLA_challenge/leaderboard/team_code\n\nmkdir .tmp\n\ncp -fr ${CARLA_ROOT}/PythonAPI  .tmp\ncp -fr ${SCENARIO_RUNNER_ROOT}/ .tmp\ncp -fr ${LEADERBOARD_ROOT}/ .tmp\ncp -fr ${TEAM_CODE_ROOT}/ .tmp/team_code\ncp -fr /home/bradyzhou/code/2020_CARLA_challenge/carla_project .tmp\n\n# build docker image\ndocker build --force-rm -t leaderboard-user -f scripts/Dockerfile.master .\n\nrm -fr .tmp\n"
  }
]