Traffic Light recognition

Pre-requisites:

  • Vector Map
  • NDT working
  • Calibration publisher
  • Tf between camera and localizer

Traffic light recognition is splitted in two parts

  1. feat_proj finds the ROIs of the traffic signals in the current camera FOV
  2. region_tlr checks each ROI and publishes result, it also publishes /tlr_superimpose_image image with the traffic lights overlayed
    2a. region_tlr_ssd deep learning based detector.

Launch Feature Projection

roslaunch road_wizard feat_proj.launch camera_id:=/camera0

Launch HSV classifier

roslaunch road_wizard traffic_light_recognition.launch camera_id:=/camera0 image_src:=/image_XXXX

SSD Classifier

roslaunch road_wizard traffic_light_recognition_ssd.launch camera_id:=/camera0 image_src:=/image_XXXX network_definition_file:=/PATH_TO_NETWORK_DEFINITION/deploy.prototxt pretrained_model_file:=/PATH_TO_MODEL/Autoware_tlrSSD.caffemodel use_gpu:=true gpu_device_id:=0