def bbox_flip(self, bboxes, img_shape):
"""Flip bboxes horizontally.
Args:
bboxes(ndarray): shape (..., 5*k)
img_shape(tuple): (height, width)
"""
assert bboxes.shape[-1] % 5 == 0
w = img_shape[1]
# x_ctr and angle
bboxes[..., 0::5] = w - bboxes[..., 0::5] - 1
bboxes[..., 4::5] = norm_angle(np.pi - bboxes[..., 4::5])
return bboxes
def get_ann_info(self, idx):
"""Get annotation from XML file by index.
Args:
idx (int): Index of data.
Returns:
dict: Annotation info of specified index.
"""
img_id = self.img_infos[idx]['id']
xml_path = osp.join(self.img_prefix, 'Annotations', f'{img_id}.xml')
tree = ET.parse(xml_path)
root = tree.getroot()
bboxes = []
labels = []
bboxes_ignore = []
labels_ignore = []
for obj in root.findall('HRSC_Objects')[0].findall('HRSC_Object'):
label = self.cat2label['ship']
difficult = int(obj.find('difficult').text)
bbox = []
for key in ['mbox_cx', 'mbox_cy', 'mbox_w', 'mbox_h', 'mbox_ang']:
bbox.append(obj.find(key).text)
# TODO: check whether it is necessary to use int
# Coordinates may be float type
cx, cy, w, h, a = list(map(float, bbox))
# set w the long side and h the short side
new_w, new_h = max(w, h), min(w, h)
# adjust angle
a = a if w > h else a + np.pi / 2
# normalize angle to [-np.pi/4, pi/4*3]
a = norm_angle(a)
bbox = [cx, cy, new_w, new_h, a]
ignore = False
if self.min_size:
assert not self.test_mode
if bbox[2] < self.min_size or bbox[3] < self.min_size:
ignore = True
if difficult or ignore:
bboxes_ignore.append(bbox)
labels_ignore.append(label)
else:
bboxes.append(bbox)
labels.append(label)
if not bboxes:
bboxes = np.zeros((0, 5))
labels = np.zeros((0,))
else:
bboxes = np.array(bboxes, ndmin=2)
labels = np.array(labels)
if not bboxes_ignore:
bboxes_ignore = np.zeros((0, 5))
labels_ignore = np.zeros((0,))
else:
bboxes_ignore = np.array(bboxes_ignore, ndmin=2)
labels_ignore = np.array(labels_ignore)
ann = dict(
bboxes=bboxes.astype(np.float32),
labels=labels.astype(np.int64),
bboxes_ignore=bboxes_ignore.astype(np.float32),
labels_ignore=labels_ignore.astype(np.int64))
return ann
def get_ann_info(self, idx):
img_id = self.img_infos[idx]['id']
xml_path = osp.join(self.img_prefix, 'Annotations',
'{}.xml'.format(img_id))
tree = ET.parse(xml_path)
root = tree.getroot()
bboxes = []
labels = []
bboxes_ignore = []
labels_ignore = []
for obj in root.findall('object'):
name = obj.find('name').text
label = self.cat2label[name]
difficult = int(obj.find('difficult').text)
bnd_box = obj.find('robndbox')
bbox = [
float(bnd_box.find('cx').text),
float(bnd_box.find('cy').text),
float(bnd_box.find('w').text),
float(bnd_box.find('h').text),
float(bnd_box.find('angle').text) + 1 # important!
]
# TODO: check whether it is necessary to use int
# Coordinates may be float type
cx, cy, w, h, a = list(map(float, bbox))
# set w the long side and h the short side
new_w, new_h = max(w, h), min(w, h)
# adjust angle
a = a if w > h else a + np.pi / 2
# normalize angle to [-np.pi/4, pi/4*3]
a = norm_angle(a)
bbox = [cx, cy, new_w, new_h, a]
ignore = False
if self.min_size:
assert not self.test_mode
w = bbox[2] - bbox[0]
h = bbox[3] - bbox[1]
if w < self.min_size or h < self.min_size:
ignore = True
if difficult or ignore:
bboxes_ignore.append(bbox)
labels_ignore.append(label)
else:
bboxes.append(bbox)
labels.append(label)
if not bboxes:
bboxes = np.zeros((0, 5))
labels = np.zeros((0, ))
else:
bboxes = np.array(bboxes, ndmin=2) - 1
labels = np.array(labels)
if not bboxes_ignore:
bboxes_ignore = np.zeros((0, 5))
labels_ignore = np.zeros((0, ))
else:
bboxes_ignore = np.array(bboxes_ignore, ndmin=2) - 1
labels_ignore = np.array(labels_ignore)
ann = dict(bboxes=bboxes.astype(np.float32),
labels=labels.astype(np.int64),
bboxes_ignore=bboxes_ignore.astype(np.float32),
labels_ignore=labels_ignore.astype(np.int64))
return ann