# 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. import os import os.path as osp from collections import defaultdict from PIL import Image import json import numpy as np from .....utils.errors import DatasetFileNotFoundError def check(dataset_dir, output, sample_num=10): """check dataset""" dataset_dir = osp.abspath(dataset_dir) if not osp.exists(dataset_dir) or not osp.isdir(dataset_dir): raise DatasetFileNotFoundError(file_path=dataset_dir) sample_cnts = dict() sample_paths = defaultdict(list) delim = "\t" valid_num_parts = 2 tags = ["train", "val"] for _, tag in enumerate(tags): file_list = osp.join(dataset_dir, f"{tag}.txt") if not osp.exists(file_list): if tag in ("train", "val"): # train and val file lists must exist raise DatasetFileNotFoundError( file_path=file_list, solution=f"Ensure that both `train.txt` and `val.txt` exist in \ {dataset_dir}", ) else: continue else: with open(file_list, "r", encoding="utf-8") as f: all_lines = f.readlines() sample_cnts[tag] = len(all_lines) for idx, line in enumerate(all_lines): substr = line.strip("\n").split(delim) if len(line.strip("\n")) < 1: continue assert ( len(substr) == valid_num_parts or len(line.strip("\n")) <= 1 ), f"Error in {line}, \ The number of delimiter-separated items in each row in {file_list} \ should be {valid_num_parts} (current delimiter is '{delim}')." file_name = substr[0] label = substr[1] img_path = osp.join(dataset_dir, file_name) if len(sample_paths[tag]) < sample_num: sample_paths[tag].append(os.path.relpath(img_path, output)) if not osp.exists(img_path): raise DatasetFileNotFoundError(file_path=img_path) # check det label label = json.loads(label) for item in label: assert ( "points" in item and "transcription" in item ), f"line {idx} is not in the correct format." box = np.array(item["points"]) assert ( box.shape[1] == 2 ), f"{box} in line {idx} is not in the correct format." txt = item["transcription"] assert isinstance( txt, str ), f"{txt} in line {idx} is not in the correct format." attrs = {} attrs["train_samples"] = sample_cnts["train"] attrs["train_sample_paths"] = sample_paths["train"][:sample_num] attrs["val_samples"] = sample_cnts["val"] attrs["val_sample_paths"] = sample_paths["val"][:sample_num] return attrs