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[Datumaro] Update LabelMe format #1296

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merged 6 commits into from
Mar 20, 2020
Merged

[Datumaro] Update LabelMe format #1296

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97fde15
Little refactoring
zhiltsov-max Mar 19, 2020
9ba7778
Add LabelMe format
zhiltsov-max Mar 19, 2020
0153d76
Add usernames
zhiltsov-max Mar 20, 2020
79840b2
Update tests
zhiltsov-max Mar 20, 2020
4ea4098
Add extractor test
zhiltsov-max Mar 20, 2020
144c89b
Merge branch 'develop' into zm/dm-labelme-format
zhiltsov-max Mar 20, 2020
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2 changes: 2 additions & 0 deletions datumaro/datumaro/components/project.py
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Original file line number Diff line number Diff line change
Expand Up @@ -367,6 +367,8 @@ def categories(self):
def get(self, item_id, subset=None, path=None):
if path:
raise KeyError("Requested dataset item path is not found")
if subset is None:
subset = ''
return self._subsets[subset].items[item_id]

def put(self, item, item_id=None, subset=None, path=None):
Expand Down
35 changes: 26 additions & 9 deletions datumaro/datumaro/plugins/labelme_format.py
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Expand Up @@ -59,7 +59,9 @@ def get_subset(self, name):

def _parse(self, path):
categories = {
AnnotationType.label: LabelCategories(attributes={'occluded'})
AnnotationType.label: LabelCategories(attributes={
'occluded', 'username'
})
}

items = []
Expand Down Expand Up @@ -136,10 +138,17 @@ def get_label_id(label):
if deleted_elem is not None and deleted_elem.text:
deleted = bool(int(deleted_elem.text))

user = ''

poly_elem = obj_elem.find('polygon')
segm_elem = obj_elem.find('segm')
type_elem = obj_elem.find('type') # the only value is 'bounding_box'
if poly_elem is not None:
user_elem = poly_elem.find('username')
if user_elem is not None and user_elem.text:
user = user_elem.text
attributes.append(('username', user))

points = []
for point_elem in poly_elem.iter('pt'):
x = float(point_elem.find('x').text)
Expand All @@ -153,20 +162,25 @@ def get_label_id(label):
ymin = min(points[1::2])
ymax = max(points[1::2])
ann_items.append(Bbox(xmin, ymin, xmax - xmin, ymax - ymin,
label=label, attributes=attributes,
label=label, attributes=attributes, id=obj_id,
))
else:
ann_items.append(Polygon(points,
label=label, attributes=attributes,
label=label, attributes=attributes, id=obj_id,
))
elif segm_elem is not None:
user_elem = segm_elem.find('username')
if user_elem is not None and user_elem.text:
user = user_elem.text
attributes.append(('username', user))

mask_path = osp.join(dataset_root, LabelMePath.MASKS_DIR,
segm_elem.find('mask').text)
if not osp.isfile(mask_path):
raise Exception("Can't find mask at '%s'" % mask_path)
mask = load_mask(mask_path)
mask = np.any(mask, axis=2)
ann_items.append(Mask(image=mask, label=label,
ann_items.append(Mask(image=mask, label=label, id=obj_id,
attributes=attributes))

if not deleted:
Expand Down Expand Up @@ -368,7 +382,7 @@ def _save_item(self, item, subset_dir):
ET.SubElement(obj_elem, 'deleted').text = '0'
ET.SubElement(obj_elem, 'verified').text = '0'
ET.SubElement(obj_elem, 'occluded').text = \
'yes' if ann.attributes.get('occluded') == True else 'no'
'yes' if ann.attributes.pop('occluded', '') == True else 'no'
ET.SubElement(obj_elem, 'date').text = ''
ET.SubElement(obj_elem, 'id').text = str(obj_id)

Expand All @@ -390,15 +404,17 @@ def _save_item(self, item, subset_dir):
ET.SubElement(point_elem, 'x').text = '%.2f' % x
ET.SubElement(point_elem, 'y').text = '%.2f' % y

ET.SubElement(poly_elem, 'username').text = ''
ET.SubElement(poly_elem, 'username').text = \
str(ann.attributes.pop('username', ''))
elif ann.type == AnnotationType.polygon:
poly_elem = ET.SubElement(obj_elem, 'polygon')
for x, y in zip(ann.points[::2], ann.points[1::2]):
point_elem = ET.SubElement(poly_elem, 'pt')
ET.SubElement(point_elem, 'x').text = '%.2f' % x
ET.SubElement(point_elem, 'y').text = '%.2f' % y

ET.SubElement(poly_elem, 'username').text = ''
ET.SubElement(poly_elem, 'username').text = \
str(ann.attributes.pop('username', ''))
elif ann.type == AnnotationType.mask:
mask_filename = '%s_mask_%s.png' % (item.id, obj_id)
save_image(osp.join(subset_dir, LabelMePath.MASKS_DIR,
Expand All @@ -416,13 +432,14 @@ def _save_item(self, item, subset_dir):
'%.2f' % (bbox[0] + bbox[2])
ET.SubElement(box_elem, 'ymax').text = \
'%.2f' % (bbox[1] + bbox[3])

ET.SubElement(segm_elem, 'username').text = \
str(ann.attributes.pop('username', ''))
else:
raise NotImplementedError("Unknown shape type '%s'" % ann.type)

attrs = []
for k, v in ann.attributes.items():
if k == 'occluded':
continue
if isinstance(v, bool):
attrs.append(k)
else:
Expand Down
Binary file added datumaro/tests/assets/labelme_dataset/Masks/img1_mask_1.png
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Binary file added datumaro/tests/assets/labelme_dataset/Masks/img1_mask_5.png
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Binary file added datumaro/tests/assets/labelme_dataset/Scribbles/img1_scribble_1.png
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Binary file added datumaro/tests/assets/labelme_dataset/Scribbles/img1_scribble_5.png
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Binary file added datumaro/tests/assets/labelme_dataset/img1.png
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1 change: 1 addition & 0 deletions datumaro/tests/assets/labelme_dataset/img1.xml
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Original file line number Diff line number Diff line change
@@ -0,0 +1 @@
<annotation><filename>img1.png</filename><folder>example_folder</folder><source><sourceImage>The MIT-CSAIL database of objects and scenes</sourceImage><sourceAnnotation>LabelMe Webtool</sourceAnnotation></source><object><name>window</name><deleted>0</deleted><verified>0</verified><date>25-May-2012 00:09:48</date><id>0</id><polygon><username>admin</username><pt><x>43</x><y>34</y></pt><pt><x>45</x><y>34</y></pt><pt><x>45</x><y>37</y></pt><pt><x>43</x><y>37</y></pt></polygon><parts><hasparts/><ispartof/></parts></object><imagesize><nrows>77</nrows><ncols>102</ncols></imagesize><object><name>license plate</name><deleted>0</deleted><verified>0</verified><occluded>no</occluded><attributes/><parts><hasparts/><ispartof/></parts><date>27-Jul-2014 02:58:50</date><id>1</id><segm><username>brussell</username><box><xmin>58</xmin><ymin>66</ymin><xmax>62</xmax><ymax>68</ymax></box><mask>img1_mask_1.png</mask><scribbles><xmin>58</xmin><ymin>66</ymin><xmax>62</xmax><ymax>68</ymax><scribble_name>img1_scribble_1.png</scribble_name></scribbles></segm></object><object><name>o1</name><deleted>0</deleted><verified>0</verified><occluded>yes</occluded><attributes>a1</attributes><parts><hasparts>3,4</hasparts><ispartof></ispartof></parts><date>15-Nov-2019 14:38:51</date><id>2</id><polygon><username>anonymous</username><pt><x>30</x><y>12</y></pt><pt><x>42</x><y>21</y></pt><pt><x>24</x><y>26</y></pt><pt><x>15</x><y>22</y></pt><pt><x>18</x><y>14</y></pt><pt><x>22</x><y>12</y></pt><pt><x>27</x><y>12</y></pt></polygon></object><object><name>q1</name><deleted>0</deleted><verified>0</verified><occluded>no</occluded><attributes>kj</attributes><parts><hasparts></hasparts><ispartof>2</ispartof></parts><date>15-Nov-2019 14:39:00</date><id>3</id><polygon><username>anonymous</username><pt><x>35</x><y>21</y></pt><pt><x>43</x><y>22</y></pt><pt><x>40</x><y>28</y></pt><pt><x>28</x><y>31</y></pt><pt><x>31</x><y>22</y></pt><pt><x>32</x><y>25</y></pt></polygon></object><object><name>b1</name><deleted>0</deleted><verified>0</verified><occluded>yes</occluded><attributes>hg</attributes><parts><hasparts></hasparts><ispartof>2</ispartof></parts><date>15-Nov-2019 14:39:09</date><id>4</id><type>bounding_box</type><polygon><username>anonymous</username><pt><x>13</x><y>19</y></pt><pt><x>23</x><y>19</y></pt><pt><x>23</x><y>30</y></pt><pt><x>13</x><y>30</y></pt></polygon></object><object><name>m1</name><deleted>0</deleted><verified>0</verified><occluded>no</occluded><attributes>d</attributes><parts><hasparts>6</hasparts><ispartof></ispartof></parts><date>15-Nov-2019 14:39:30</date><id>5</id><type>bounding_box</type><segm><username>anonymous</username><box><xmin>56</xmin><ymin>14</ymin><xmax>70</xmax><ymax>23</ymax></box><mask>img1_mask_5.png</mask><scribbles><xmin>55</xmin><ymin>13</ymin><xmax>70</xmax><ymax>23</ymax><scribble_name>img1_scribble_5.png</scribble_name></scribbles></segm></object><object><name>hg</name><deleted>0</deleted><verified>0</verified><occluded>no</occluded><attributes>gfd lkj lkj hi</attributes><parts><hasparts></hasparts><ispartof>5</ispartof></parts><date>15-Nov-2019 14:41:57</date><id>6</id><polygon><username>anonymous</username><pt><x>64</x><y>21</y></pt><pt><x>74</x><y>24</y></pt><pt><x>72</x><y>32</y></pt><pt><x>62</x><y>34</y></pt><pt><x>60</x><y>27</y></pt><pt><x>62</x><y>22</y></pt></polygon></object></annotation>
144 changes: 119 additions & 25 deletions datumaro/tests/test_labelme_format.py
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Original file line number Diff line number Diff line change
@@ -1,11 +1,14 @@
import numpy as np
import os.path as osp

from unittest import TestCase

from datumaro.components.extractor import (Extractor, DatasetItem,
AnnotationType, Bbox, Mask, Polygon, LabelCategories
)
from datumaro.plugins.labelme_format import LabelMeImporter, LabelMeConverter
from datumaro.components.project import Dataset
from datumaro.plugins.labelme_format import LabelMeExtractor, LabelMeImporter, \
LabelMeConverter
from datumaro.util.test_utils import TestDir, compare_datasets


Expand Down Expand Up @@ -35,7 +38,8 @@ def __iter__(self):
Polygon([0, 4, 4, 4, 5, 6], label=3, attributes={
'occluded': True
}),
Mask(np.array([[0, 1], [1, 0], [1, 1]]), group=2),
Mask(np.array([[0, 1], [1, 0], [1, 1]]), group=2,
attributes={ 'username': 'test' }),
Bbox(1, 2, 3, 4, group=3),
Mask(np.array([[0, 0], [0, 0], [1, 1]]), group=3,
attributes={ 'occluded': True }
Expand All @@ -58,20 +62,28 @@ def __iter__(self):
DatasetItem(id=1, subset='train',
image=np.ones((16, 16, 3)),
annotations=[
Bbox(0, 4, 4, 8, label=0, group=2, attributes={
'occluded': False
}),
Polygon([0, 4, 4, 4, 5, 6], label=1, attributes={
'occluded': True
}),
Bbox(0, 4, 4, 8, label=0, group=2, id=0,
attributes={
'occluded': False, 'username': '',
}
),
Polygon([0, 4, 4, 4, 5, 6], label=1, id=1,
attributes={
'occluded': True, 'username': '',
}
),
Mask(np.array([[0, 1], [1, 0], [1, 1]]), group=2,
attributes={ 'occluded': False }
id=2, attributes={
'occluded': False, 'username': 'test'
}
),
Bbox(1, 2, 3, 4, group=1, attributes={
'occluded': False
Bbox(1, 2, 3, 4, group=1, id=3, attributes={
'occluded': False, 'username': '',
}),
Mask(np.array([[0, 0], [0, 0], [1, 1]]), group=1,
attributes={ 'occluded': True }
id=4, attributes={
'occluded': True, 'username': ''
}
),
]
),
Expand All @@ -90,31 +102,113 @@ def categories(self):
SrcExtractor(), LabelMeConverter(save_images=True),
test_dir, target_dataset=DstExtractor())

class LabelMeImporterTest(TestCase):
def test_can_detect(self):
class TestExtractor(Extractor):

DUMMY_DATASET_DIR = osp.join(osp.dirname(__file__), 'assets', 'labelme_dataset')

class LabelMeExtractorTest(TestCase):
def test_can_load(self):
class DstExtractor(Extractor):
def __iter__(self):
img1 = np.ones((77, 102, 3)) * 255
img1[6:32, 7:41] = 0

mask1 = np.zeros((77, 102), dtype=int)
mask1[67:69, 58:63] = 1

mask2 = np.zeros((77, 102), dtype=int)
mask2[13:25, 54:71] = [
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
]

return iter([
DatasetItem(id=1, subset='train',
image=np.ones((16, 16, 3)),
DatasetItem(id='img1', image=img1,
annotations=[
Bbox(0, 4, 4, 8, label=2),
Polygon([43, 34, 45, 34, 45, 37, 43, 37],
label=0, id=0,
attributes={
'occluded': False,
'username': 'admin'
}
),
Mask(mask1, label=1, id=1,
attributes={
'occluded': False,
'username': 'brussell'
}
),
Polygon([30, 12, 42, 21, 24, 26, 15, 22, 18, 14, 22, 12, 27, 12],
label=2, group=2, id=2,
attributes={
'a1': '1',
'occluded': True,
'username': 'anonymous'
}
),
Polygon([35, 21, 43, 22, 40, 28, 28, 31, 31, 22, 32, 25],
label=3, group=2, id=3,
attributes={
'kj': '1',
'occluded': False,
'username': 'anonymous'
}
),
Bbox(13, 19, 10, 11, label=4, group=2, id=4,
attributes={
'hg': '1',
'occluded': True,
'username': 'anonymous'
}
),
Mask(mask2, label=5, group=1, id=5,
attributes={
'd': '1',
'occluded': False,
'username': 'anonymous'
}
),
Polygon([64, 21, 74, 24, 72, 32, 62, 34, 60, 27, 62, 22],
label=6, group=1, id=6,
attributes={
'gfd lkj lkj hi': '1',
'occluded': False,
'username': 'anonymous'
}
),
]
),
])

def categories(self):
label_cat = LabelCategories()
for label in range(10):
label_cat.add('label_' + str(label))
label_cat.add('window')
label_cat.add('license plate')
label_cat.add('o1')
label_cat.add('q1')
label_cat.add('b1')
label_cat.add('m1')
label_cat.add('hg')
return {
AnnotationType.label: label_cat,
}

def generate_dummy(path):
LabelMeConverter()(TestExtractor(), save_dir=path)
parsed = Dataset.from_extractors(LabelMeExtractor(DUMMY_DATASET_DIR))
compare_datasets(self, expected=DstExtractor(), actual=parsed)

with TestDir() as test_dir:
generate_dummy(test_dir)
class LabelMeImporterTest(TestCase):
def test_can_detect(self):
self.assertTrue(LabelMeImporter.detect(DUMMY_DATASET_DIR))

self.assertTrue(LabelMeImporter.detect(test_dir))
def test_can_import(self):
parsed = LabelMeImporter()(DUMMY_DATASET_DIR).make_dataset()
self.assertEqual(1, len(parsed))