TrafficSigns: [object detection] Improve the dataset for the object detection in the CaroloCup

[Christiaan1990]

Goal:

Create a 2nd dataset for the object detection in the carolo-cup with a second folder with additional data for the same labels as the original dataset. A second should be created such that we still have the original one for comparison purposes.

Background:

• When this is completed, the object detection algorithm can train on both datasets to improve the accuracy

Assigments:

• get an overview which data for which label exist
• create a second dataset: check how data should be labeled, and then a program such as LabelImg might be used
  • documentation in the TUM-Wiki which data in the dataset exist: https://wiki.tum.de/display/phoenix/Machine+Learning

Notes:

• a dataset for object detection not only requires the label, but also the bounding box
  • /drive_ml/blob/master/tf_object_detection
  • Quality and quantity are both important
  • Make sure, that also images exist that are photographed from further away
  • Training requires a dataset that is i.i.d. (Independent and identically distributed)
  • information about the current YOLOv3 implementation and the current datasets: https://wiki.tum.de/display/phoenix/Sign+Detection