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'''
crop
for numpy array
Given image, bbox(center, bboxsize)
return: cropped image, tform(used for transform the keypoint accordingly)
only support crop to squared images
'''
import numpy as np
from skimage.transform import estimate_transform, warp, resize, rescale
def points2bbox(points, points_scale=None):
# recover range
if points_scale:
points[:, 0] = points[:, 0] * points_scale[1] / 2 + points_scale[1] / 2
points[:, 1] = points[:, 1] * points_scale[0] / 2 + points_scale[0] / 2
left = np.min(points[:, 0])
right = np.max(points[:, 0])
top = np.min(points[:, 1])
bottom = np.max(points[:, 1])
size = max(right - left, bottom - top)
# + old_size*0.1])
center = np.array(
[right - (right - left) / 2.0, bottom - (bottom - top) / 2.0])
return center, size
# translate center
def augment_bbox(center, bbox_size, scale=[1.0, 1.0], trans_scale=0.):
trans_scale = (np.random.rand(2) * 2 - 1) * trans_scale
center = center + trans_scale * bbox_size # 0.5
scale = np.random.rand() * (scale[1] - scale[0]) + scale[0]
size = int(bbox_size * scale)
return center, size
def crop_array(image, center, bboxsize, crop_size):
''' for single image only
Args:
image (numpy.Array): the reference array of shape HxWXC.
size (Tuple[int, int]): a tuple with the height and width that will be
used to resize the extracted patches.
Returns:
cropped_image
tform: 3x3 affine matrix
'''
# points: top-left, top-right, bottom-right
src_pts = np.array([[center[0] - bboxsize / 2, center[1] - bboxsize / 2],
[center[0] + bboxsize / 2, center[1] - bboxsize / 2],
[center[0] + bboxsize / 2, center[1] + bboxsize / 2]])
DST_PTS = np.array([[0, 0], [crop_size - 1, 0],
[crop_size - 1, crop_size - 1]])
# estimate transformation between points
tform = estimate_transform('similarity', src_pts, DST_PTS)
# warp images
cropped_image = warp(image,
tform.inverse,
output_shape=(crop_size, crop_size))
return cropped_image, tform.params.T
class Cropper(object):
def __init__(self, crop_size, scale=[1, 1], trans_scale=0.):
self.crop_size = crop_size
self.scale = scale
self.trans_scale = trans_scale
def crop(self, image, points, points_scale=None):
# points to bbox
center, bbox_size = points2bbox(points, points_scale)
# argument bbox.
center, bbox_size = augment_bbox(center,
bbox_size,
scale=self.scale,
trans_scale=self.trans_scale)
# crop
cropped_image, tform = crop_array(image, center, bbox_size,
self.crop_size)
return cropped_image, tform
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