def run(network, dataset, config_file, experiment_id, recreate): environment.init(experiment_id) config = config_util.load(config_file) if network: network_class = module_loader.load_network_class(network) config.NETWORK_CLASS = network_class if dataset: dataset_class = module_loader.load_dataset_class(dataset) config.DATASET_CLASS = dataset_class config_util.display(config) executor.init_logging(config) executor.prepare_dirs(recreate) config_util.copy_to_experiment_dir(config_file) config_util.save_yaml(environment.EXPERIMENT_DIR, config) start_training(config)
def main(model): if model == "yolov2": weight_file = 'inputs/yolo-voc.weights' experiment_id = "convert_weight_from_darknet/yolo_v2" config_file = "configs/convert_weight_from_darknet/yolo_v2.py" if model == "darknet19": weight_file = 'inputs/darknet19_448.weights' experiment_id = "convert_weight_from_darknet/darknet19" config_file = "configs/convert_weight_from_darknet/darknet19.py" recreate = True environment.init(experiment_id) executor.prepare_dirs(recreate) config = config_util.load(config_file) config_util.display(config) config_util.copy_to_experiment_dir(config_file) convert(config, weight_file)