def train_nuscenes_all(): config = Path( __file__).resolve().parent / "configs/nuscenes/all-s.fhd.proto" ckpt_path = "/home/yy/deeplearning/voxelnet_torch_sparse/car_fhd_small_v1/voxelnet-27855.tckpt" # config = Path(__file__).resolve().parent() / "configs/car.fhd.nu.config" config = _get_config(config) _nuscenes_modify_step(config, 50, 5, 8) model_dir_root = Path("/home/yy/deeplearning/model_dirs/nuscene") date_str = datetime.datetime.now().strftime("%y%m%d_%H%M%S") train(config, model_dir_root / "all_fhd" / ("test_" + date_str))
def train_nuscenes_pp_car(): config = Path(__file__).resolve().parent / "configs/nuscenes/car.pp.config" ckpt_path = "/home/yy/deeplearning/model_dirs/kitti/car_pp_long_v0/voxelnet-296960.tckpt" ckpt_path = "/home/yy/deeplearning/model_dirs/kitti/car_pp_long_v0/voxelnet-296960.tckpt" # config = Path(__file__).resolve().parent() / "configs/car.fhd.nu.config" config = _get_config(config) _nuscenes_modify_step(config, 50, 5, 8) model_dir_root = Path("/home/yy/deeplearning/model_dirs/nuscene") date_str = datetime.datetime.now().strftime("%y%m%d_%H%M%S") train(config, model_dir_root / "pp_car" / ("test_" + date_str))
def resume_nuscenes_pp_all(): config = Path(__file__).resolve().parent / "configs/nuscenes/all.pp.config" ckpt_path = "/home/yy/deeplearning/model_dirs/kitti/car_pp_long_v0/voxelnet-296960.tckpt" ckpt_path = "/home/yy/deeplearning/model_dirs/kitti/car_pp_long_v0/voxelnet-296960.tckpt" # config = Path(__file__).resolve().parent() / "configs/car.fhd.nu.config" config = _get_config(config) _nuscenes_modify_step(config, 50, 5, 8) model_dir_root = Path("/home/yy/deeplearning/model_dirs/nuscene") train(config, model_dir_root / "all_pp" / ("test_190424_232942"), resume=True)
def train_nuscenes_lite(): config = Path( __file__).resolve().parent / "configs/nuscenes/car.lite.nu.config" ckpt_path = "/home/yy/deeplearning/voxelnet_torch_sparse/car_lite_small_v1/voxelnet-15500.tckpt" # config = Path(__file__).resolve().parent() / "configs/car.fhd.nu.config" config = _get_config(config) _nuscenes_modify_step(config, 50, 5, 8) model_dir_root = Path("/home/yy/deeplearning/model_dirs/nuscene") date_str = datetime.datetime.now().strftime("%y%m%d_%H%M%S") train(config, model_dir_root / "car_lite_with_pretrain" / ("test_" + date_str), pretrained_path=ckpt_path)
def train_multi_rpn_layer_num(): config_path = "./configs/nuscenes/all.fhd.config" model_root = Path.home() / "second_test" # don't forget to change this. config = pipeline_pb2.TrainEvalPipelineConfig() with open(config_path, "r") as f: proto_str = f.read() text_format.Merge(proto_str, config) input_cfg = config.eval_input_reader model_cfg = config.model.second layer_nums = [2, 4, 7, 9] for l in layer_nums: model_dir = str(model_root / f"all_fhd_{l}") model_cfg.rpn.layer_nums[:] = [l] train(config, model_dir, resume=True)