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)
