def extend_with_flipped_entries(roidb, dataset):
"""Flip each entry in the given roidb and return a new roidb that is the
concatenation of the original roidb and the flipped entries.
"Flipping" an entry means that that image and associated metadata (e.g.,
ground truth boxes and object proposals) are horizontally flipped.
"""
flipped_roidb = []
for entry in roidb:
width = entry['width']
boxes = entry['boxes'].copy()
oldx1 = boxes[:, 0].copy()
oldx2 = boxes[:, 2].copy()
boxes[:, 0] = width - oldx2 - 1
boxes[:, 2] = width - oldx1 - 1
assert (boxes[:, 2] >= boxes[:, 0]).all()
flipped_entry = {}
dont_copy = ('boxes', 'segms', 'gt_keypoints', 'flipped')
for k, v in entry.items():
if k not in dont_copy:
flipped_entry[k] = v
flipped_entry['boxes'] = boxes
flipped_entry['segms'] = segm_utils.flip_segms(entry['segms'],
entry['height'],
entry['width'])
if dataset.keypoints is not None:
flipped_entry['gt_keypoints'] = keypoint_utils.flip_keypoints(
dataset.keypoints, dataset.keypoint_flip_map,
entry['gt_keypoints'], entry['width'])
flipped_entry['flipped'] = True
flipped_roidb.append(flipped_entry)
roidb.extend(flipped_roidb)
def extend_with_flipped_entries(roidb, dataset):
"""Flip each entry in the given roidb and return a new roidb that is the
concatenation of the original roidb and the flipped entries.
"Flipping" an entry means that that image and associated metadata (e.g.,
ground truth boxes and object proposals) are horizontally flipped.
"""
flipped_roidb = []
for entry in roidb:
width = entry['width']
boxes = entry['boxes'].copy()
oldx1 = boxes[:, 0].copy()
oldx2 = boxes[:, 2].copy()
boxes[:, 0] = width - oldx2 - 1
boxes[:, 2] = width - oldx1 - 1
assert (boxes[:, 2] >= boxes[:, 0]).all()
flipped_entry = {}
dont_copy = ('boxes', 'segms', 'gt_keypoints', 'flipped')
for k, v in entry.items():
if k not in dont_copy:
flipped_entry[k] = v
flipped_entry['boxes'] = boxes
flipped_entry['segms'] = segm_utils.flip_segms(
entry['segms'], entry['height'], entry['width']
)
if dataset.keypoints is not None:
flipped_entry['gt_keypoints'] = keypoint_utils.flip_keypoints(
dataset.keypoints, dataset.keypoint_flip_map,
entry['gt_keypoints'], entry['width']
)
flipped_entry['flipped'] = True
flipped_roidb.append(flipped_entry)
roidb.extend(flipped_roidb)
def extend_with_flipped_entries(roidb, dataset):
"""Flip each entry in the given roidb and return a new roidb that is the
concatenation of the original roidb and the flipped entries.
"Flipping" an entry means that that image and associated metadata (e.g.,
ground truth boxes and object proposals) are horizontally flipped.
"""
flipped_roidb = []
for entry in roidb:
width = entry['width']
boxes = entry['boxes'].copy()
oldx1 = boxes[:, 0].copy()
oldx2 = boxes[:, 2].copy()
boxes[:, 0] = width - oldx2 - 1
boxes[:, 2] = width - oldx1 - 1
assert (boxes[:, 2] >= boxes[:, 0]).all()
flipped_entry = {}
dont_copy = ('boxes', 'segms', 'gt_keypoints', 'flipped') # original
if not cfg.Ignore_left: # when filpped, the right is changed to left
dont_copy = ('boxes', 'gt_keypoints', 'flipped', 'gt_classes',
'max_classes', 'gt_overlaps')
gt_classes_ = copy.deepcopy(entry['gt_classes'])
gt_classes = copy.deepcopy(entry['gt_classes'])
max_classes = copy.deepcopy(entry['max_classes'])
gt_overlaps = copy.deepcopy(entry['gt_overlaps'])
dataset_name = cfg.TRAIN.DATASETS[0]
if 'LIP' in dataset_name:
orig_class_2_flipped = {
14: 15,
15: 14,
16: 17,
17: 16,
18: 19,
19: 18
}
if 'ATR' in dataset_name:
orig_class_2_flipped = {
9: 10,
10: 9,
12: 13,
13: 12,
14: 15,
15: 14
}
for i in orig_class_2_flipped.keys():
idx = np.where(gt_classes_ == i)[0]
if len(idx) == 0:
continue
gt_classes[idx] = orig_class_2_flipped[i]
max_classes[idx] = orig_class_2_flipped[i]
gt_overlaps[idx, i] = 0
gt_overlaps[idx, orig_class_2_flipped[i]] = 1
flipped_entry['gt_classes'] = gt_classes
flipped_entry['max_classes'] = max_classes
flipped_entry['gt_overlaps'] = gt_overlaps
for k, v in entry.items():
if k not in dont_copy:
flipped_entry[k] = v
flipped_entry['boxes'] = boxes
# flipped_entry['segms'] = segm_utils.flip_segms(
# entry['segms'], entry['height'], entry['width']
# )
if dataset.keypoints is not None:
flipped_entry['gt_keypoints'] = keypoint_utils.flip_keypoints(
dataset.keypoints, dataset.keypoint_flip_map,
entry['gt_keypoints'], entry['width'])
flipped_entry['flipped'] = True
flipped_roidb.append(flipped_entry)
roidb.extend(flipped_roidb)
