text: #! /usr/bin/env python
  # coding=utf-8
  from easydict import EasyDict as edict
  
  
  __C                           = edict()
  # Consumers can get config by: from config import cfg
  
  cfg                           = __C
  
  # YOLO options
  __C.YOLO                      = edict()
  
  __C.YOLO.CLASSES              = "/home/user/Downloads/rtsp/tensorflow-yolov4-tflite/data/classes/obj.names"
  __C.YOLO.ANCHORS              = [12,16, 19,36, 40,28, 36,75, 76,55, 72,146, 142,110, 192,243, 459,401]
  __C.YOLO.ANCHORS_V3           = [10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326]
  __C.YOLO.ANCHORS_TINY         = [23,27, 37,58, 81,82, 81,82, 135,169, 344,319]
  __C.YOLO.STRIDES              = [8, 16, 32]
  __C.YOLO.STRIDES_TINY         = [16, 32]
  __C.YOLO.XYSCALE              = [1.2, 1.1, 1.05]
  __C.YOLO.XYSCALE_TINY         = [1.05, 1.05]
  __C.YOLO.ANCHOR_PER_SCALE     = 3
  __C.YOLO.IOU_LOSS_THRESH      = 0.5
  
  
  # Train options
  __C.TRAIN                     = edict()
  
  __C.TRAIN.ANNOT_PATH          = "./data/dataset/val2017.txt"
  __C.TRAIN.BATCH_SIZE          = 2
  # __C.TRAIN.INPUT_SIZE            = [320, 352, 384, 416, 448, 480, 512, 544, 576, 608]
  __C.TRAIN.INPUT_SIZE          = 416
  __C.TRAIN.DATA_AUG            = True
  __C.TRAIN.LR_INIT             = 1e-3
  __C.TRAIN.LR_END              = 1e-6
  __C.TRAIN.WARMUP_EPOCHS       = 2
  __C.TRAIN.FISRT_STAGE_EPOCHS    = 20
  __C.TRAIN.SECOND_STAGE_EPOCHS   = 30
  
  
  
  # TEST options
  __C.TEST                      = edict()
  
  __C.TEST.ANNOT_PATH           = "./data/dataset/val2017.txt"
  __C.TEST.BATCH_SIZE           = 2
  __C.TEST.INPUT_SIZE           = 416
  __C.TEST.DATA_AUG             = False
  __C.TEST.DECTECTED_IMAGE_PATH = "./data/detection/"
  __C.TEST.SCORE_THRESHOLD      = 0.25
  __C.TEST.IOU_THRESHOLD        = 0.5
  
  
  