def get_annotations(self):
"""
Returns the 'annotations' key of the COCO dataset annotation
"""
if not self._annotations:
ann_id = 1
ret = []
label_to_category_id_map = self.get_label_to_category_id_map()
for f in self.list_annotations():
data = util.load_json(f)
for i, shape in enumerate(data['shapes']):
if i % 2 == 0:
d = {
'area': None,
'bbox': self.get_annotation_bbox(shape['points']),
'category_id':
label_to_category_id_map[shape['label']],
'id': ann_id,
'image_id': self.get_image_id(f),
'iscrowd': 0,
}
else:
# every 2nd loop the annotation is complete, so add it
# to the return and increment the annotation id
d['segmentation'] = self.get_segmentation(
shape['points'])
ret.append(d)
ann_id += 1
self._annotations = ret
return self._annotations
def get_image_ann(self, path):
"""
Takes the path of a "labelme" style annotation and returns
a COCO dataset syle image annotation
"""
ann = util.load_json(path)
filename, _ = os.path.splitext(os.path.basename(ann['imagePath']))
return {
'id': int(filename),
'height': ann['imageHeight'],
'width': ann['imageWidth'],
'file_name': os.path.basename(ann['imagePath'])
}
def test_generate(self):
# rm file file if present
output_path = os.path.join(config.OUTPUT_DIR, 'annotations.json')
if os.path.isfile(output_path):
os.remove(output_path)
assert not os.path.isfile(output_path)
self.ann.generate(output_path)
assert os.path.isfile(output_path)
data = util.load_json(output_path)
assert data == self.ann.all()
# cleanup file when done
os.remove(output_path)
def get_categories(self):
"""
Returns the 'categories' key of the COCO dataset annotation
"""
if not self._categories:
cats = {}
i = 1
for file in self.list_annotations():
data = util.load_json(file)
for shape in data['shapes']:
label = shape['label']
if label not in cats:
cats[label] = {
'id': i,
'supercategory': label,
'name': label
}
i += 1
self._categories = list(cats.values())
return self._categories
def test_load_json(self):
ret = util.load_json(os.path.join(config.ANNOTATIONS_DIR, '1.json'))
assert isinstance(ret, dict)