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import numpy as np
def _concat(arr_list, axis=0):
"""Avoids a copy if there is only a single element in a list.
"""
if len(arr_list) == 1:
return arr_list[0]
return np.concatenate(arr_list, axis)
def convert_boxes_list_to_boxes_and_indices(boxes_list):
"""
Args:
boxes_list (np.ndarray): list or tuple of ndarray with shape (N_i, 4+K)
Returns:
boxes (ndarray): shape (M, 4+K) where M is sum of N_i.
indices (ndarray): shape (M, 1) where M is sum of N_i.
References:
`mmdet.core.bbox.bbox2roi` in mmdetection
`convert_boxes_to_roi_format` in TorchVision
`modeling.poolers.convert_boxes_to_pooler_format` in detectron2
"""
assert isinstance(boxes_list, (list, tuple))
boxes = _concat(boxes_list, axis=0)
indices_list = [np.full((len(b), 1), i, boxes.dtype)
for i, b in enumerate(boxes_list)]
indices = _concat(indices_list, axis=0)
return boxes, indices
def convert_boxes_and_indices_to_boxes_list(boxes, indices, num_indices):
"""
Args:
boxes (np.ndarray): shape (N, 4+K)
indices (np.ndarray): shape (N,) or (N, 1), maybe batch index
in mini-batch or class label index.
num_indices (int): number of index.
Returns:
list (ndarray): boxes list of each index
References:
`mmdet.core.bbox2result` in mmdetection
`mmdet.core.bbox.roi2bbox` in mmdetection
`convert_boxes_to_roi_format` in TorchVision
`modeling.poolers.convert_boxes_to_pooler_format` in detectron2
"""
boxes = np.asarray(boxes)
indices = np.asarray(indices)
assert boxes.ndim == 2, "boxes ndim must be 2, got {}".format(boxes.ndim)
assert (indices.ndim == 1) or (indices.ndim == 2 and indices.shape[-1] == 1), \
"indices ndim must be 1 or 2 if last dimension size is 1, got shape {}".format(indices.shape)
assert boxes.shape[0] == indices.shape[0], "the 1st dimension size of boxes and indices "\
"must be the same, got {} != {}".format(boxes.shape[0], indices.shape[0])
if boxes.shape[0] == 0:
return [np.zeros((0, boxes.shape[1]), dtype=np.float32)
for i in range(num_indices)]
else:
if indices.ndim == 2:
indices = np.squeeze(indices, axis=-1)
return [boxes[indices == i, :] for i in range(num_indices)]
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