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Merge pull request #2785 from wanghaoshuang/voc_dataset
Add voc2012 dataset for image segment
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# Copyright (c) 2016 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. | ||
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import paddle.v2.dataset.voc2012 | ||
import unittest | ||
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class TestVOC(unittest.TestCase): | ||
def check_reader(self, reader): | ||
sum = 0 | ||
label = 0 | ||
for l in reader(): | ||
self.assertEqual(l[0].size, 3 * l[1].size) | ||
sum += 1 | ||
return sum | ||
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def test_train(self): | ||
count = self.check_reader(paddle.v2.dataset.voc_seg.train()) | ||
self.assertEqual(count, 2913) | ||
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def test_test(self): | ||
count = self.check_reader(paddle.v2.dataset.voc_seg.test()) | ||
self.assertEqual(count, 1464) | ||
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def test_val(self): | ||
count = self.check_reader(paddle.v2.dataset.voc_seg.val()) | ||
self.assertEqual(count, 1449) | ||
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if __name__ == '__main__': | ||
unittest.main() |
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# Copyright (c) 2016 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. | ||
""" | ||
Image dataset for segmentation. | ||
The 2012 dataset contains images from 2008-2011 for which additional | ||
segmentations have been prepared. As in previous years the assignment | ||
to training/test sets has been maintained. The total number of images | ||
with segmentation has been increased from 7,062 to 9,993. | ||
""" | ||
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import tarfile | ||
import io | ||
import numpy as np | ||
from paddle.v2.dataset.common import download | ||
from paddle.v2.image import * | ||
from PIL import Image | ||
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__all__ = ['train', 'test', 'val'] | ||
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VOC_URL = 'http://host.robots.ox.ac.uk/pascal/VOC/voc2012/\ | ||
VOCtrainval_11-May-2012.tar' | ||
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VOC_MD5 = '6cd6e144f989b92b3379bac3b3de84fd' | ||
SET_FILE = 'VOCdevkit/VOC2012/ImageSets/Segmentation/{}.txt' | ||
DATA_FILE = 'VOCdevkit/VOC2012/JPEGImages/{}.jpg' | ||
LABEL_FILE = 'VOCdevkit/VOC2012/SegmentationClass/{}.png' | ||
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CACHE_DIR = 'voc2012' | ||
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def reader_creator(filename, sub_name): | ||
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tarobject = tarfile.open(filename) | ||
name2mem = {} | ||
for ele in tarobject.getmembers(): | ||
name2mem[ele.name] = ele | ||
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def reader(): | ||
set_file = SET_FILE.format(sub_name) | ||
sets = tarobject.extractfile(name2mem[set_file]) | ||
for line in sets: | ||
line = line.strip() | ||
data_file = DATA_FILE.format(line) | ||
label_file = LABEL_FILE.format(line) | ||
data = tarobject.extractfile(name2mem[data_file]).read() | ||
label = tarobject.extractfile(name2mem[label_file]).read() | ||
data = Image.open(io.BytesIO(data)) | ||
label = Image.open(io.BytesIO(label)) | ||
data = np.array(data) | ||
label = np.array(label) | ||
yield data, label | ||
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return reader | ||
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def train(): | ||
""" | ||
Create a train dataset reader containing 2913 images in HWC order. | ||
""" | ||
return reader_creator(download(VOC_URL, CACHE_DIR, VOC_MD5), 'trainval') | ||
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def test(): | ||
""" | ||
Create a test dataset reader containing 1464 images in HWC order. | ||
""" | ||
return reader_creator(download(VOC_URL, CACHE_DIR, VOC_MD5), 'train') | ||
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def val(): | ||
""" | ||
Create a val dataset reader containing 1449 images in HWC order. | ||
""" | ||
return reader_creator(download(VOC_URL, CACHE_DIR, VOC_MD5), 'val') |
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