* model: add kernel_regularizer argument
  * tf: remove subdivision
  * tf: dataset: fix issue where coordinates become 0 due to repeated division
  * tf: dataset: modify to shuffle when augmentation
  * tf: train: modify order of declaration
  * tf: train: give xiou_loss to more weight
  * tf: train: use keras.losses.BinaryCrossentropy to avoid nan problem
  * tf: train: add verbose argument
  * tf: dataset: change converted_coco format
  * tf: add image_path_prefix argument to load_dataset()
  * tf: add loss_verbose argument to compile()
  * tf: reflect dataset format change to save_dataset_for_mAP()