witignite/Frustum-PointNet

KITTI Dataset

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#7 建立於 2019年10月25日

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描述

KITTI Dataset

Overview

Excerpts from the following papers:

Data Description

  • Image: image_2

    • 8-bit PNG file: training/image_2/000085.png 000085 000085_groundtruth
  • Velodyne: velodyne

    • Each point stored as floating point binaries: [x, y, z, reflectance]
    • Number of points per scan is not constant
  • Calibration: calib

    • Variables
      • P0:
      • P1:
      • P2:
      • P3:
      • R0_rect:
      • Tr_velo_to_cam:
      • Tr_imu_to_velo:
    • To project a point from Velodyne coordinates into the color image, you can use this formula
      • x = P2 * R0_rect * Tr_velo_to_cam * y (for the left color image)
      • x = P3 * R0_rect * Tr_velo_to_cam * y (for the right color image)
  • Label: label_2

    • For each dynamic object within the reference camera’s field of view, we provide annotations in the form of 3D bounding box tracklets. Fig7_ObjectCoordinates
    Values Name Description
    1 type Describes the type of object: 'Car', 'Van', 'Truck', 'Pedestrian', 'Person_sitting', 'Cyclist', 'Tram', 'Misc' or 'DontCare'
    1 truncated Float from 0 (non-truncated) to 1 (truncated), where truncated refers to the object leaving image boundaries
    1 occluded Integer (0,1,2,3) indicating occlusion state: 0 = fully visible, 1 = partly occluded, 2 = largely occluded, 3 = unknown
    1 alpha Observation angle of object, ranging [-pi..pi]
    4 bbox 2D bounding box of object in the image (0-based index): contains left, top, right, bottom pixel coordinates
    3 dimensions 3D object dimensions: height, width, length (in meters)
    3 location 3D object location x,y,z in camera coordinates (in meters)
    1 rotation_y Rotation ry around Y-axis in camera coordinates [-pi..pi]
    1 score Only for results: Float, indicating confidence in detection, needed for p/r curves, higher is better.
    • training/label_2/000085.txt
    Van 0.90 0 -0.79 0.00 57.67 245.43 374.00 2.46 2.03 5.35 -5.26 1.68 5.45 -1.53
    Cyclist 0.00 0 -1.54 678.16 164.16 705.93 243.78 1.82 0.59 1.89 1.96 1.63 17.42 -1.43
    Pedestrian 0.00 0 0.90 304.95 177.99 359.91 304.07 1.57 0.52 0.62 -3.69 1.64 9.37 0.54
    Car 0.27 3 -2.42 0.00 179.86 156.79 244.69 1.44 1.62 3.91 -13.19 1.62 17.05 -3.07
    DontCare -1 -1 -10 644.98 164.60 670.02 188.60 -1 -1 -1 -1000 -1000 -1000 -10
    DontCare -1 -1 -10 739.77 173.98 799.19 209.44 -1 -1 -1 -1000 -1000 -1000 -10
    

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