yukitsuji / 3D_CNN_tensorflow

KITTI data processing and 3D CNN for Vehicle Detection

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Is there a particular code set for converting the output to the KITTI label format?

spbayley opened this issue · comments

I am testing this code with the KITTI evaluation development kit which takes in the ground truth labels as well as text files of results. The text files have to be in the same format as the ground truth. The output of the test function in the model_01_deconv script seems to output the coordinates and objectness scores. However, the text file labels need to have the 2D bounding box coordinates with the 3D coordinates of the car. The readme file for the evaluation script shows the structure of the result files:

#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.

Thanks in advance!