We explain preprocessing steps more details here. Feel free to contact if you have problems running them.

2D object detection

We use Yolo to detect 2D object bounding box, which can be replaced by other algorithms. We add functions to batch predict all images under a folder and save results to images and txts. See the modification code under 2D_object_detect. Might need to change rgb file name in line 495 of detector.c

Create two folders to save results of images and txts: yolov2_obj yolov2_obj_txts. After compiling Yolo, run command:

./darknet detect_folder cfg/yolo.cfg trained_model/yolo.weights  path/to/rgb path/to/yolov2_obj -thresh 0.25

Pay attention to the cfg and weights for different yolo version.