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--- |
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license: mit |
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dataset_info: |
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features: |
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- name: segment_id |
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dtype: string |
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- name: preview |
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dtype: image |
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- name: log |
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struct: |
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- name: global_pose__frame_gps_times |
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list: |
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list: float64 |
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- name: global_pose__frame_orientations |
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list: |
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list: float64 |
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- name: global_pose__frame_positions |
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list: |
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list: float64 |
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- name: global_pose__frame_times |
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list: float64 |
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- name: global_pose__frame_velocities |
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list: |
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list: float64 |
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- name: processed_log__CAN__radar__t |
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list: float64 |
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- name: processed_log__CAN__radar__value |
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list: |
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list: float64 |
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- name: processed_log__CAN__raw_can__address |
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list: int64 |
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- name: processed_log__CAN__raw_can__data |
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list: binary |
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- name: processed_log__CAN__raw_can__src |
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list: int64 |
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- name: processed_log__CAN__raw_can__t |
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list: float64 |
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- name: processed_log__CAN__speed__t |
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list: float64 |
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- name: processed_log__CAN__speed__value |
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list: |
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list: float64 |
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- name: processed_log__CAN__steering_angle__t |
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list: float64 |
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- name: processed_log__CAN__steering_angle__value |
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list: float64 |
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- name: processed_log__CAN__wheel_speed__t |
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list: float64 |
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- name: processed_log__CAN__wheel_speed__value |
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list: |
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list: float64 |
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- name: processed_log__GNSS__live_gnss_qcom__t |
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list: float64 |
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- name: processed_log__GNSS__live_gnss_qcom__value |
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list: |
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list: float64 |
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- name: processed_log__GNSS__live_gnss_ublox__t |
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list: float64 |
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- name: processed_log__GNSS__live_gnss_ublox__value |
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list: |
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list: float64 |
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- name: processed_log__GNSS__raw_gnss_qcom__t |
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list: float64 |
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- name: processed_log__GNSS__raw_gnss_qcom__value |
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list: |
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list: float64 |
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- name: processed_log__GNSS__raw_gnss_ublox__t |
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list: float64 |
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- name: processed_log__GNSS__raw_gnss_ublox__value |
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list: |
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list: float64 |
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- name: processed_log__IMU__accelerometer__t |
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list: float64 |
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- name: processed_log__IMU__accelerometer__value |
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list: |
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list: float64 |
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- name: processed_log__IMU__gyro__t |
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list: float64 |
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- name: processed_log__IMU__gyro__value |
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list: |
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list: float64 |
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- name: processed_log__IMU__gyro_bias__t |
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list: float64 |
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- name: processed_log__IMU__gyro_bias__value |
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list: |
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list: float64 |
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- name: processed_log__IMU__gyro_uncalibrated__t |
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list: float64 |
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- name: processed_log__IMU__gyro_uncalibrated__value |
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list: |
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list: float64 |
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- name: processed_log__IMU__magnetometer__t |
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list: float64 |
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- name: processed_log__IMU__magnetometer__value |
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list: |
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list: float64 |
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- name: processed_log__IMU__magnetometer_uncalibrated__t |
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list: float64 |
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- name: processed_log__IMU__magnetometer_uncalibrated__value |
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list: |
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list: float64 |
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splits: |
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- name: demo |
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num_bytes: 537452565 |
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num_examples: 64 |
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download_size: 227930673 |
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dataset_size: 537452565 |
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configs: |
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- config_name: default |
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data_files: |
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- split: demo |
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path: data/demo-* |
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--- |
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# comma2k19 |
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[comma.ai](https://comma.ai) presents comma2k19, a dataset of over 33 hours of commute in California's 280 highway. This means 2019 segments, 1 minute long each, on a 20km section of highway driving between California's San Jose and San Francisco. comma2k19 is a fully reproducible and scalable dataset. The data was collected using comma [EONs](https://comma.ai/shop/products/eon-gold-dashcam-devkit/) that has sensors similar to those of any modern smartphone including a road-facing camera, phone GPS, thermometers and 9-axis IMU. Additionally, the EON captures raw GNSS measurements and all CAN data sent by the car with a comma [grey panda](https://comma.ai/shop/products/panda-obd-ii-dongle/). |
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<img src="https://github.com/commaai/comma2k19/blob/master/assets/testmesh3d.png?raw=true"/> |
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Here we also introduced [Laika](https://github.com/commaai/laika), an open-source GNSS processing library. Laika produces 40% more accurate positions than the GNSS module used to collect the raw data. This dataset includes pose (position + orientation) estimates in a global reference frame of the recording camera. These poses were computed with a tightly coupled INS/GNSS/Vision optimizer that relies on data processed by Laika. comma2k19 is ideal for development and validation of tightly coupled GNSS algorithms and mapping algorithms that work with commodity sensors. |
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<img src="https://github.com/commaai/comma2k19/blob/master/assets/merged.png?raw=true"/> |
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## Publication |
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For a detailed write-up about this dataset, please refer to our [paper](https://arxiv.org/abs/1812.05752v1). If you use comma2k19 or Laika in your research, please consider citing |
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```text |
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@misc{1812.05752, |
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Author = {Harald Schafer and Eder Santana and Andrew Haden and Riccardo Biasini}, |
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Title = {A Commute in Data: The comma2k19 Dataset}, |
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Year = {2018}, |
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Eprint = {arXiv:1812.05752}, |
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} |
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``` |
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