faster_rcnn_bet365.yaml

_BASE_: "./bases/Base-RCNN-FPN.yaml"
MODEL:
  # COCO ResNet50 weights
  WEIGHTS: "https://dl.fbaipublicfiles.com/detectron2/COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl"
  MASK_ON: False # Not doing segmentation
  RESNETS:
    DEPTH: 50 # ResNet50
  ROI_HEADS:
    NUM_CLASSES: 2 # Change to suit own task
    # Can reduce this for lower memory/faster training; Default 512
    BATCH_SIZE_PER_IMAGE: 512
  BACKBONE:
    FREEZE_AT: 2 # Default 2
DATASETS:
  TRAIN: ("benign_bet365",)
  TEST: ("benign_test",)
DATALOADER:
  NUM_WORKERS: 0
SOLVER:
  IMS_PER_BATCH: 8 # Batch size; Default 16
  BASE_LR: 0.00001
  # (2/3, 8/9)
  STEPS: (600, 900) # The iteration number to decrease learning rate by GAMMA.
  MAX_ITER: 1000 # Number of training iterations
  CHECKPOINT_PERIOD: 100 # Saves checkpoint every number of steps
INPUT:
  MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800) # Image input sizes
TEST:
  # The period (in terms of steps) to evaluate the model during training.
  # Set to 0 to disable.
  EVAL_PERIOD: 100
OUTPUT_DIR: "./output" # Specify output directory