def test_unpack_numpy(self):
buffer = struct.pack("<ffff", 1., 2.5, 3.5, 4.5)
reader = BufferReader(buffer)
arr = reader.unpack_numpy(ConstStructs.float, (2, 2))
res = np.array([[1., 2.5], [3.5, 4.5]])
self.assertTrue(np.all(arr == res), msg="Numpy unpacked array is not equal to expected array")
def test_unpack_torch(self):
buffer = struct.pack("<ffff", 1., 2.5, 3.5, 4.5)
reader = BufferReader(buffer)
arr = reader.unpack_torch(ConstStructs.float, (2, 2))
res = torch.tensor([[1., 2.5], [3.5, 4.5]])
self.assertTrue(torch.all(arr == res), msg="Torch unpacked array is not equal to expected array")
def read_body(pose_bytes: bytes, header: PoseHeader, read_offset: Optional[int] = None):
reader = BufferReader(pose_bytes)
if header is None:
header = PoseHeader.read(reader)
else:
reader.read_offset = read_offset
return NumPyPoseBody.read(header, reader)
def test_unpack_tensorflow(self):
buffer = struct.pack("<ffff", 1., 2.5, 3.5, 4.5)
reader = BufferReader(buffer)
arr = reader.unpack_tensorflow(ConstStructs.float, (2, 2))
res = tf.constant([[1., 2.5], [3.5, 4.5]])
self.assertTrue(tf.reduce_all(tf.equal(arr, res)),
msg="Tensorflow unpacked array is not equal to expected array")
def get_openpose_header(): """Get pose header with OpenPose components description.""" dir_path = os.path.dirname(os.path.realpath(__file__)) header_path = os.path.join(dir_path, "assets/openpose.poseheader") f = open(header_path, "rb") reader = BufferReader(f.read()) header = PoseHeader.read(reader) return header
def read_v0_1(cls, header: PoseHeader, reader: BufferReader):
fps, _frames = reader.unpack(ConstStructs.double_ushort)
_people = reader.unpack(ConstStructs.ushort)
_points = sum([len(c.points) for c in header.components])
_dims = max([len(c.format) for c in header.components]) - 1
# _frames is defined as short, which sometimes is not enough! TODO change to int
_frames = int(reader.bytes_left() / (_people * _points *
(_dims + 1) * 4))
tensor_reader = reader.__getattribute__(cls.tensor_reader)
data = tensor_reader(ConstStructs.float,
shape=(_frames, _people, _points, _dims))
confidence = tensor_reader(ConstStructs.float,
shape=(_frames, _people, _points))
return cls(fps, data, confidence)
def get_pose_header():
"""Get pose header with components description."""
dir_path = os.path.dirname(os.path.realpath(__file__))
header_path = os.path.join(dir_path, "holistic.poseheader")
f = open(header_path, "rb")
reader = BufferReader(f.read())
header = PoseHeader.read(reader)
header.components.pop(1) # Remove face from holistic pose
return header
def read(buffer: bytes, pose_body: PoseBody):
reader = BufferReader(buffer)
header = PoseHeader.read(reader)
body = pose_body.read(header, reader)
return Pose(header, body)
def test_unpack_str(self):
s = "hello"
buffer = struct.pack("<H%ds" % len(s), len(s), bytes(s, 'utf8'))
reader = BufferReader(buffer)
unpacked_s = reader.unpack_str()
self.assertEqual(unpacked_s, s)
def test_unpack_f(self):
buffer = struct.pack("<fh", 5.5, 3)
reader = BufferReader(buffer)
unpacked_f, unpacked_short = reader.unpack_f("fh")
self.assertEqual(unpacked_f, 5.5)
self.assertEqual(unpacked_short, 3)
def test_unpack(self):
buffer = struct.pack("<f", 5.5)
reader = BufferReader(buffer)
unpacked_f = reader.unpack(ConstStructs.float)
self.assertEqual(unpacked_f, 5.5)
def test_advance(self):
reader = BufferReader(bytes())
reader.advance(ConstStructs.float, 10)
self.assertEqual(reader.read_offset, 40)
def test_bytes_left(self):
reader = BufferReader(bytes(range(6)))
reader.unpack_f("f")
bytes_left = reader.bytes_left()
self.assertEqual(bytes_left, 2)
rep_modules1 = []
rep_modules2 = []
if args.rep_points:
rep_modules1.append(PointsRepresentation())
if args.rep_distance:
rep_modules2.append(DistanceRepresentation())
if args.rep_angles:
rep_modules2.append(AngleRepresentation())
pose_headers = []
HOLISTIC_POSE_HEADER = OPENPOSE_POSE_HEADER = None
if args.holistic:
with open("holistic.poseheader", "rb") as f:
HOLISTIC_POSE_HEADER = PoseHeader.read(BufferReader(f.read()))
components = []
for c in HOLISTIC_POSE_HEADER.components:
if c.name in args.holistic_pose_components:
c_copy = pickle.loads(pickle.dumps(c))
c_copy.format = c_copy.format[:args.pose_dims]
components.append(c_copy)
rep_header = PoseHeader(version=HOLISTIC_POSE_HEADER.version,
dimensions=HOLISTIC_POSE_HEADER.dimensions,
components=components)
pose_headers.append(rep_header)
if args.openpose:
with open("openpose_135.poseheader", "rb") as f:
def read_header(header_path: str):
with open(header_path, "rb") as f:
reader = BufferReader(f.read())
header = PoseHeader.read(reader)
return header, reader.read_offset
