config.example.yaml

#######################
### PATH MANAGEMENT ###
#######################

ANNOTATION_PATH: # The path for the non-tiled data: "/home/taheera.ahmed/data/reindeerdrone/whole/test/result.json"
IMAGES_FOLDER_PATH: # The image directory for the non-tiled data: "/home/taheera.ahmed/data/reindeerdrone/whole/test"

TILE_ANNOTATION_PATH: # File with annotations for the tiled data: "/home/taheera.ahmed/data/reindeerdrone/tiles/train/new_annotations.json"
TILE_FOLDER_PATH: # Directory for the tiled images: "/home/taheera.ahmed/data/reindeerdrone/tiles/train/images"

TILE_TEST_ANNOTATION_PATH: # Test set file with annotations for the tiled data: "/home/taheera.ahmed/data/reindeerdrone/tiles/test/new_annotations.json"
TILE_TEST_FOLDER_PATH: # Teset set image directory for tiled data: "/home/taheera.ahmed/data/reindeerdrone/tiles/test"

OUTPUT_FOLDER: # Output folder for all files created with the python scripts: "/home/taheera.ahmed/code/reindeerdrone/output/02_hyperparam_opt"

###################
# DATA PROCESSING #
###################

TILE_SIZE: 1024
OVERLAP: 100
PLOT_ANNOTATION: False

#########
# TRAIN #
#########

OPTUNA_TRAILS: # Number of trials for hyperparameter optimization: 20

##############
# EVALUATION #
##############

STORE_EVALUATION_RESULTS: # Store the evaluation results in a json file: True
EVALUATION_OUTPUT_PATH: # Output file where metrics will be stored: "/home/taheera.ahmed/code/reindeerdrone/output"


###############
# PREDICTIONS #
###############

CONFIG_FILE: "COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml"
MODEL_WEIGHTS: # Path to the trained model weights: "/home/taheera.ahmed/code/reindeerdrone/output/02_hyperparam_opt/model_final.pth"

USE_FILTER: # Used to remove duplicate bboxes: True
PLOT_PREDICTION: # To save prediction images with ground truth: True