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All Projects → umautobots → pedx

umautobots / pedx

Licence: MIT license
Python tools for working with PedX dataset.

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python
139335 projects - #7 most used programming language

Labels

trackingdemodatasetsegmentationkeypointspedestriansintersections

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PedX

This package provides basic tools for working with the PedX dataset [1] in Python.

Data

The dataset is available from the webpage (http://pedx.io/downloads/). You can download the entire dataset by running the script download_data.py. The data will be organized as in the following directory tree.

Directory Tree

pedx/
├── pedx/
├── data/
│   ├── images/
│   │   ├── 20171130T2000/
│   │   ├── 20171207T2024/
│   │   └── 20171212T2030/
│   │       ├── ylw79D0/
│   │       ├── red707B/
│   │       ├── blu79CF/
│   │       └── grn43E3/
│   │           └── 20171212T2030_grn43E3_0001234.jpg
│   ├── pointclouds/
│   │   ├── 20171130T2000/
│   │   ├── 20171207T2024/
│   │   └── 20171212T2030/
│   │       └── 20171212T2030_0001234.ply
│   ├── labels/
│   |   ├── 2d/
│   |   │   ├── 20171130T2000/
│   |   │   ├── 20171207T2024/
│   |   │   └── 20171212T2030/
│   |   └── 3d/
│   |       ├── smpl/
│   |       │   ├── 20171130T2000/
│   |       │   ├── 20171207T2024/
│   |       |   └── 20171212T2030/
│   |       └── segment/
│   |           ├── 20171130T2000/
│   |           ├── 20171207T2024/
│   |           └── 20171212T2030/
│   ├── calib/
│   │   ├── calib_cam_to_cam_blu79CF-grn43E3.txt
│   │   ├── calib_cam_to_cam_blu79CF-red707B.txt
│   │   ├── calib_cam_to_range_blu79CF.txt
│   │   └── calib_cam_to_range_ylw79D0.txt
│   └── timestamps/
│       ├── timestamps-images-20171130T2000.txt
│       ├── timestamps-images-20171207T2024.txt
│       ├── timestamps-images-20171212T2030.txt
│       ├── timestamps-pointclouds-20171130T2000.txt
│       ├── timestamps-pointclouds-20171207T2024.txt
│       └── timestamps-pointclouds-20171212T2030.txt
├── demo.py
└── README.md
  • data contains the rectified images, point clouds, calibrated parameters and frame metadata.
  • All the manual/automatic annotations are in data/labels. 2D/3D annotations are provided in an instance-level.
  • We provide 3 video sequences captured at different 4-way stop intersections on different dates.
    • Capture dates: 20171130T2000, 20171207T2024, 20171212T2030
  • The cameras are color-coded for our convenience.
    • Cameras: ylw79D0, red707B, blu79CF, grn43E3
    • Stereo pairs: ylw79D0-red707B, blu79CF-grn43E3 (left-right camera)
  • We provide a simple Python demo script: demo.py. pedx provides Python helper functions to load and visualize the data. We have tested the script with the Python packages listed in requirements.txt.

Contact

Email: [email protected]

References

[1] Kim, Wonhui, et al. "Pedx: Benchmark dataset for metric 3d pose estimation of pedestrians in complex urban intersections." IEEE Robotics and Automation Letters (2019). http://pedx.io/

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