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- # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
- #
- # 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 __future__ import print_function
- import numpy as np
- import paddle
- from paddle.io import Dataset
- import os
- import cv2
- from paddlex.ppcls.data import preprocess
- from paddlex.ppcls.data.preprocess import transform
- from paddlex.ppcls.utils import logger
- from .common_dataset import create_operators
- class CompCars(Dataset):
- def __init__(self,
- image_root,
- cls_label_path,
- label_root=None,
- transform_ops=None,
- bbox_crop=False):
- self._img_root = image_root
- self._cls_path = cls_label_path
- self._label_root = label_root
- if transform_ops:
- self._transform_ops = create_operators(transform_ops)
- self._bbox_crop = bbox_crop
- self._dtype = paddle.get_default_dtype()
- self._load_anno()
- def _load_anno(self):
- assert os.path.exists(self._cls_path)
- assert os.path.exists(self._img_root)
- if self._bbox_crop:
- assert os.path.exists(self._label_root)
- self.images = []
- self.labels = []
- self.bboxes = []
- with open(self._cls_path) as fd:
- lines = fd.readlines()
- for l in lines:
- l = l.strip().split()
- if not self._bbox_crop:
- self.images.append(os.path.join(self._img_root, l[0]))
- self.labels.append(int(l[1]))
- else:
- label_path = os.path.join(self._label_root,
- l[0].split('.')[0] + '.txt')
- assert os.path.exists(label_path)
- with open(label_path) as f:
- bbox = f.readlines()[-1].strip().split()
- bbox = [int(x) for x in bbox]
- self.images.append(os.path.join(self._img_root, l[0]))
- self.labels.append(int(l[1]))
- self.bboxes.append(bbox)
- assert os.path.exists(self.images[-1])
- def __getitem__(self, idx):
- img = cv2.imread(self.images[idx])
- img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
- if self._bbox_crop:
- bbox = self.bboxes[idx]
- img = img[bbox[1]:bbox[3], bbox[0]:bbox[2], :]
- if self._transform_ops:
- img = transform(img, self._transform_ops)
- img = img.transpose((2, 0, 1))
- return (img, self.labels[idx])
- def __len__(self):
- return len(self.images)
- @property
- def class_num(self):
- return len(set(self.labels))
- class VeriWild(Dataset):
- def __init__(
- self,
- image_root,
- cls_label_path,
- transform_ops=None, ):
- self._img_root = image_root
- self._cls_path = cls_label_path
- if transform_ops:
- self._transform_ops = create_operators(transform_ops)
- self._dtype = paddle.get_default_dtype()
- self._load_anno()
- def _load_anno(self):
- assert os.path.exists(self._cls_path)
- assert os.path.exists(self._img_root)
- self.images = []
- self.labels = []
- self.cameras = []
- with open(self._cls_path) as fd:
- lines = fd.readlines()
- for l in lines:
- l = l.strip().split()
- self.images.append(os.path.join(self._img_root, l[0]))
- self.labels.append(np.int64(l[1]))
- self.cameras.append(np.int64(l[2]))
- assert os.path.exists(self.images[-1])
- def __getitem__(self, idx):
- try:
- with open(self.images[idx], 'rb') as f:
- img = f.read()
- if self._transform_ops:
- img = transform(img, self._transform_ops)
- img = img.transpose((2, 0, 1))
- return (img, self.labels[idx], self.cameras[idx])
- except Exception as ex:
- logger.error("Exception occured when parse line: {} with msg: {}".
- format(self.images[idx], ex))
- rnd_idx = np.random.randint(self.__len__())
- return self.__getitem__(rnd_idx)
- def __len__(self):
- return len(self.images)
- @property
- def class_num(self):
- return len(set(self.labels))
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