yolov3.yaml

PROJECT_NAME: "yolov3"
EXP_NAME: "yolov3-coco"
# random number seed
SEED: 42
# run device models
DEVICE_ID: 0

CLASS_NAMES: [ "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light",
               "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow",
               "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella", "handbag", "tie", "suitcase", "frisbee",
               "skis", "snowboard", "sports ball", "kite", "baseball bat", "baseball glove", "skateboard", "surfboard",
               "tennis racket", "bottle", "wine glass", "cup", "fork", "knife", "spoon", "bowl", "banana", "apple",
               "sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza", "donut", "cake", "chair", "couch",
               "potted plant", "bed", "dining table", "toilet", "tv", "laptop", "mouse", "remote", "keyboard", "cell phone",
               "microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors", "teddy bear",
               "hair drier", "toothbrush" ]

AUGMENT:
  HYP:
    HSV_H: 0.0138  # image HSV-Hue augmentation (fraction)
    HSV_S: 0.678  # image HSV-Saturation augmentation (fraction)
    HSV_V: 0.36  # image HSV-Value augmentation (fraction)
    DEGREES: 0  # image rotation (+/- deg)
    TRANSLATE: 0.0  # image translation (+/- fraction)
    SCALE: 0.0  # image scale (+/- gain)
    SHEAR: 0.0  # image shear (+/- gain)
    USE_LR_FLIP: True  # image left-right flip (probability)
    USE_UD_FLIP: False  # image up-down flip (probability)

MODEL:
  CONFIG_PATH: "./model_configs/COCO-Detection/yolov3.cfg"
  IMG_SIZE: 512
  GRAY: False
  NUM_CLASSES: 80
  COMPILE_MODE: False

  GRID_SIZE: 32

TRAIN:
  DATASET:
    ROOT: "./data/coco/train.txt"
    AUGMENT: True
    RECT_LABEL: False
    CACHE_IMAGES: False
    SINGLE_CLASSES: False

  # Multi scale training
  MULTI_SCALE:
    ENABLE: True
    IMG_SIZE_MIN: 320
    IMG_SIZE_MAX: 512

  WEIGHTS_PATH: ""

  # training hyperparameters
  HYP:
    IMGS_PER_BATCH: 8
    ACCUMULATE_BATCH_SIZE: 64

    EPOCHS: 300

  OPTIM:
    NAME: "sgd"
    LR: 0.01  # SGD 0.01, Adam 0.001
    MOMENTUM: 0.9
    WEIGHT_DECAY: 0.0005
    NESTEROV: True

    LR_SCHEDULER:
      NAME: "one_cycle"

  IOU_THRESH: 0.20  # iou training threshold

  # Loss function
  LOSSES:
    GIOU_LOSS:
      WEIGHT: 3.54
    CLS_LOSS:
      WEIGHT: 37.4
    CLS_BCE_PW_LOSS:
      WEIGHT: 1.0
    OBJ_LOSS:
      WEIGHT: 64.3
    OBJ_BCE_PW_LOSS:
      WEIGHT: 1.0
    FL_GAMMA_LOSS:
      WEIGHT: 0.0

  PRINT_FREQ: 100
  SAVE_EVERY_EPOCH: 5

VAL:
  DATASET:
    ROOT: "./data/coco/test.txt"
    AUGMENT: False
    RECT_LABEL: False
    CACHE_IMAGES: False
    SINGLE_CLASSES: False

  WEIGHTS_PATH: ""

  # test hyperparameters
  HYP:
    IMGS_PER_BATCH: 16

  CONF_THRESH: 0.01
  IOU_THRESH: 0.5
  IOUV: (0.5, 0.95)  # mAP 0.5:0.95
  GT_JSON_PATH: ""  # "./data/coco/annotations/instances_val2014.json"
  PRED_JSON_PATH: "" # "./results/YOLOv3-coco.json"
  VERBOSE: False