142 lines
5.0 KiB
Python
142 lines
5.0 KiB
Python
# Copyright (c) 2021 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 numpy as np
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import paddle
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from paddle.io import Dataset
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import os
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import cv2
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from ppcls.data import preprocess
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from ppcls.data.preprocess import transform
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from ppcls.utils import logger
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from .common_dataset import create_operators
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class CompCars(Dataset):
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def __init__(self,
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image_root,
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cls_label_path,
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label_root=None,
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transform_ops=None,
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bbox_crop=False):
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self._img_root = image_root
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self._cls_path = cls_label_path
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self._label_root = label_root
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if transform_ops:
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self._transform_ops = create_operators(transform_ops)
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self._bbox_crop = bbox_crop
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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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if self._bbox_crop:
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assert os.path.exists(self._label_root)
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self.images = []
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self.labels = []
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self.bboxes = []
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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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if not self._bbox_crop:
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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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else:
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label_path = os.path.join(self._label_root,
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l[0].split('.')[0] + '.txt')
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assert os.path.exists(label_path)
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with open(label_path) as f:
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bbox = f.readlines()[-1].strip().split()
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bbox = [int(x) for x in bbox]
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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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self.bboxes.append(bbox)
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assert os.path.exists(self.images[-1])
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def __getitem__(self, idx):
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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._bbox_crop:
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bbox = self.bboxes[idx]
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img = img[bbox[1]:bbox[3], bbox[0]:bbox[2], :]
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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])
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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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class VeriWild(Dataset):
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def __init__(self, image_root, cls_label_path, 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(
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self._cls_path), f"path {self._cls_path} does not exist."
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assert os.path.exists(
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self._img_root), f"path {self._img_root} does not exist."
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self.images = []
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self.labels = []
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self.cameras = []
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with open(self._cls_path) as fd:
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lines = fd.readlines()
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for line in lines:
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line = line.strip().split()
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self.images.append(os.path.join(self._img_root, line[0]))
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self.labels.append(np.int64(line[1]))
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if len(line) >= 3:
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self.cameras.append(np.int64(line[2]))
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assert os.path.exists(self.images[-1])
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self.has_camera = len(self.cameras) > 0
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def __getitem__(self, idx):
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try:
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with open(self.images[idx], 'rb') as f:
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img = f.read()
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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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if self.has_camera:
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return (img, self.labels[idx], self.cameras[idx])
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else:
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return (img, 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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