yolo_v2_high_res_kw18.conf

#  Groundtruth file extensions (txt, kw18, etc...). Note: this is indepedent of
#  the format that's stored in the file.
groundtruth_extensions = .kw18

#  Algorithm to use for 'groundtruth_reader'.
#  Must be one of the following options:
#  	- habcam :: Reads habcam detection/ground truth files.
#  	- kw18 :: Detected object set reader using kw18 format.
groundtruth_reader:type = kw18

#  Can be either: "one_per_file" or "one_per_folder".
groundtruth_style = one_per_folder

#  Semicolon list of seperated image extensions to use in training, images
#  without this extension will not be included.
image_extensions = .jpg;.jpeg;.JPG;.JPEG;.tif;.tiff;.TIF;.TIFF;.png;.PNG

#  Percent [0.0, 1.0] of test samples to use if no manual files specified.
default_percent_test = 0.05


#  Algorithm to use for 'detector_trainer'.
#  Must be one of the following options: darket, scallop_tk
detector_trainer:type = darknet

#  GPU index. Only used when darknet is compiled with GPU support.
detector_trainer:darknet:gpu_index = 0

#  Name of network config file.
detector_trainer:darknet:net_config = cfg/yolo_v2.cfg

#  Seed weights file.
detector_trainer:darknet:seed_weights = cfg/yolo_v2_seed.wt

#  Directory for all files used in training and output models.
detector_trainer:darknet:train_directory = darknet_training

#  Output weights file.
detector_trainer:darknet:output_weights = output_weights.wt

#  Only chips with valid groundtruth objects on them will be included in
#  training.
detector_trainer:darknet:chips_w_gt_only = false

#  Pre-processing resize option, can be: disabled, maintain_ar, scale, chip, or
#  chip_and_original.
detector_trainer:darknet:resize_option = chip_and_original

#  Image scaling factor used when resize_option is scale or chip.
detector_trainer:darknet:scale = 1.4

#  Width resolution for darknet base layer.
detector_trainer:darknet:resize_ni = 960

#  Height resolution for darknet base layer.
detector_trainer:darknet:resize_nj = 544

#  When in chip mode, the chip step size between chips.
detector_trainer:darknet:chip_step = 500

#  Only use the left side of the input image
detector_trainer:darknet:crop_left = true

#  Percentage of which a target must appear on a chip for it to be included as a
#  training sample for said chip.
detector_trainer:darknet:overlap_required = 0.05

#  Random intensity shift chip augmentation [0.0,1.0] - 0.0 is turned off.
detector_trainer:darknet:random_int_shift = 0.60

#  Skip file formatting, assume that the train_directory is pre-populated with
#  all files required for model training.
detector_trainer:darknet:skip_format = false