def minmax_scale(pose):
from ufunclab import minmax
bbox = minmax(pose, axes=[(0, ), (1, )])[:2]
bbox = numpy.transpose(bbox).reshape(-1)
xywh_bbox = x1y1x2y2_to_cxywh(bbox)
return (pose - xywh_bbox[:2]) / xywh_bbox[2:]
def norm_mat(self, mat):
from ufunclab import minmax
bbox = minmax(mat, axes=[(0, ), (1, )])[:2]
bbox = np.transpose(bbox).reshape(-1)
xywh_bbox = x1y1x2y2_to_xywh(bbox)
origin = np.hstack([xywh_bbox[:2], [0]])
return xywh_bbox[2:], mat - origin
def fod_from_body_25_all_face68(skel, conf_thresh):
face_kps = get_face_kps(skel.all())
if not conf_thresh(face_kps[:, 2]):
return None
kps_existing = face_kps[:, :2][face_kps[:, 2] > 0]
if not len(kps_existing):
return None
bbox = minmax(kps_existing, axes=[(0,), (1,)])
rect = lazyimp.dlib.rectangle(
rnd(bbox[0, 0]), rnd(bbox[1, 0]), rnd(bbox[0, 1]), rnd(bbox[1, 1])
)
return lazyimp.dlib.full_object_detection(
rect, [lazyimp.dlib.point(rnd(x), rnd(y)) for x, y in face_kps[:, :2]]
)
def test_minmax_basic(x, expected):
mm = minmax(x)
assert_equal(mm, expected)
def points_bbox_x1y1x2y2(points: np.ndarray):
bbox = minmax(points, axes=[(0, ), (1, )])
return np.transpose(bbox).reshape(-1)