# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from pathlib import Path import pickle from ...base import BaseDatasetChecker from .dataset_src import check, deep_analyse from ..model_list import MODELS class BEVFusionDatasetChecker(BaseDatasetChecker): entities = MODELS def check_dataset(self, dataset_dir: str) -> dict: """check if the dataset meets the specifications and get dataset summary Args: dataset_dir (str): the root directory of dataset. sample_num (int): the number to be sampled. Returns: dict: dataset summary. """ return check(dataset_dir) def analyse(self, dataset_dir: str) -> dict: """deep analyse dataset Args: dataset_dir (str): the root directory of dataset. Returns: dict: the deep analysis results. """ return deep_analyse(dataset_dir, self.output) def get_data(self, ann_file, max_sample_num): infos = self.data_infos(ann_file, max_sample_num) meta = [] for info in infos: image_paths = [] cam_orders = [ "CAM_FRONT_LEFT", "CAM_FRONT", "CAM_FRONT_RIGHT", "CAM_BACK_RIGHT", "CAM_BACK", "CAM_BACK_LEFT", ] for cam_type in cam_orders: cam_info = info["cams"][cam_type] cam_data_path = cam_info["data_path"] image_paths.append(cam_data_path) meta.append( { "sample_idx": info["token"], "lidar_path": info["lidar_path"], "image_paths": image_paths, } ) return meta def data_infos(self, ann_file, max_sample_num): data = pickle.load(open(ann_file, "rb")) data_infos = list(sorted(data["infos"], key=lambda e: e["timestamp"])) data_infos = data_infos[:max_sample_num] return data_infos def get_show_type(self) -> str: """get the show type of dataset Returns: str: show type """ return "txt" def get_dataset_type(self) -> str: """return the dataset type Returns: str: dataset type """ return "NuscenesMMDataset"