mirror of
https://github.com/PaddlePaddle/PaddleClas.git
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105 lines
3.3 KiB
Python
105 lines
3.3 KiB
Python
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import io
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import tarfile
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import numpy as np
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from PIL import Image #all use default backend
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import paddle
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from paddle.io import Dataset
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import pickle
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import os
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import cv2
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import random
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from feature_extractor.data import preprocess
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from feature_extractor.data.preprocess import transform
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from feature_extractor.utils import logger
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def create_operators(params):
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"""
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create operators based on the config
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Args:
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params(list): a dict list, used to create some operators
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"""
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assert isinstance(params, list), ('operator config should be a list')
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ops = []
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for operator in params:
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print(operator)
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assert isinstance(operator,
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dict) and len(operator) == 1, "yaml format error"
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op_name = list(operator)[0]
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param = {} if operator[op_name] is None else operator[op_name]
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op = getattr(preprocess, op_name)(**param)
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ops.append(op)
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return ops
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class ImageNetDataset(Dataset):
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def __init__(
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self,
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image_root,
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cls_label_path,
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transform_ops=None, ):
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self._img_root = image_root
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self._cls_path = cls_label_path
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if transform_ops:
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self._transform_ops = create_operators(transform_ops)
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self._dtype = paddle.get_default_dtype()
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self._load_anno()
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def _load_anno(self):
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assert os.path.exists(self._cls_path)
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assert os.path.exists(self._img_root)
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self.images = []
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self.labels = []
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with open(self._cls_path) as fd:
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lines = fd.readlines()
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for l in lines:
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l = l.strip().split(" ")
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self.images.append(os.path.join(self._img_root, l[0]))
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self.labels.append(int(l[1]))
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assert os.path.exists(self.images[-1])
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def __getitem__(self, idx):
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try:
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img = cv2.imread(self.images[idx])
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img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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if self._transform_ops:
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img = transform(img, self._transform_ops)
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img = img.transpose((2, 0, 1))
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return (img, self.labels[idx], img, self.labels[idx])
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#print(img.shape, self.labels[idx])
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#return {'image':img, 'label':self.labels[idx]}
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except Exception as ex:
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logger.error("Exception occured when parse line: {} with msg: {}".
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format(self.images[idx], ex))
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rnd_idx = np.random.randint(self.__len__())
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return self.__getitem__(rnd_idx)
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def __len__(self):
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return len(self.images)
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@property
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def class_num(self):
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return len(set(self.labels))
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