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from typing import Type
import pytest
import torch
from torch.testing import assert_allclose
from kornia.geometry.camera import StereoCamera
@pytest.fixture(params=[1, 2, 4])
def batch_size(request):
return request.param
class _TestParams:
"""Collection of test parameters for smoke test."""
height = 4
width = 6
fx = 1
fy = 2
cx = width / 2
cy = height / 2
class _RealTestData:
"""Collection of data from a real stereo setup."""
@property
def height(self):
return 375
@property
def width(self):
return 1242
@staticmethod
def _get_real_left_camera(batch_size, device, dtype):
cam = torch.tensor(
[
9.9640068207290187e02,
0.0,
3.7502582168579102e02,
0.0,
0.0,
9.9640068207290187e02,
2.4026374816894531e02,
0.0,
0.0,
0.0,
1.0,
0.0,
],
device=device,
dtype=dtype,
).reshape(3, 4)
return cam.expand(batch_size, -1, -1)
@staticmethod
def _get_real_right_camera(batch_size, device, dtype):
cam = torch.tensor(
[
9.9640068207290187e02,
0.0,
3.7502582168579102e02,
-5.4301732344712009e03,
0.0,
9.9640068207290187e02,
2.4026374816894531e02,
0.0,
0.0,
0.0,
1.0,
0.0,
],
device=device,
dtype=dtype,
).reshape(3, 4)
return cam.expand(batch_size, -1, -1)
@staticmethod
def _get_real_stereo_camera(batch_size, device, dtype):
return (
_RealTestData._get_real_left_camera(batch_size, device, dtype),
_RealTestData._get_real_right_camera(batch_size, device, dtype),
)
@staticmethod
def _get_real_disparity(batch_size, device, dtype):
# First 10 cols of 1 row in a real disparity map.
disp = torch.tensor(
[
[
[
[67.5039],
[67.5078],
[67.5117],
[67.5156],
[67.5195],
[67.5234],
[67.5273],
[67.5312],
[67.5352],
[67.5391],
]
]
],
device=device,
dtype=dtype,
).permute(0, 2, 3, 1)
return disp.expand(batch_size, -1, -1, -1)
@staticmethod
def _get_real_point_cloud(batch_size, device, dtype):
# First 10 cols of 1 row in the ground truth point cloud computed from above disparity map.
pc = torch.tensor(
[
[
[[-30.2769, -19.3972, 80.4424]],
[[-30.1945, -19.3961, 80.4377]],
[[-30.1120, -19.3950, 80.4330]],
[[-30.0295, -19.3938, 80.4284]],
[[-29.9471, -19.3927, 80.4237]],
[[-29.8646, -19.3916, 80.4191]],
[[-29.7822, -19.3905, 80.4144]],
[[-29.6998, -19.3893, 80.4098]],
[[-29.6174, -19.3882, 80.4051]],
[[-29.5350, -19.3871, 80.4005]],
]
],
device=device,
dtype=dtype,
)
return pc.expand(batch_size, -1, -1, -1)
class _SmokeTestData:
"""Collection of smoke test data."""
@staticmethod
def _create_rectified_camera(params: Type[_TestParams], batch_size, device, dtype, tx_fx=None):
intrinsics = torch.zeros((3, 4), device=device, dtype=dtype)
intrinsics[..., 0, 0] = params.fx
intrinsics[..., 1, 1] = params.fy
intrinsics[..., 0, 2] = params.cx
intrinsics[..., 1, 2] = params.cy
if tx_fx:
intrinsics[..., 0, 3] = tx_fx
return intrinsics.expand(batch_size, -1, -1)
@staticmethod
def _create_left_camera(batch_size, device, dtype):
return _SmokeTestData._create_rectified_camera(_TestParams, batch_size, device, dtype)
@staticmethod
def _create_right_camera(batch_size, device, dtype, tx_fx):
return _SmokeTestData._create_rectified_camera(_TestParams, batch_size, device, dtype, tx_fx=tx_fx)
@staticmethod
def _create_stereo_camera(batch_size, device, dtype, tx_fx):
left_rectified_camera = _SmokeTestData._create_left_camera(batch_size, device, dtype)
right_rectified_camera = _SmokeTestData._create_right_camera(batch_size, device, dtype, tx_fx)
return left_rectified_camera, right_rectified_camera
class TestStereoCamera:
"""Test class for :class:`~kornia.geometry.camera.stereo.StereoCamera`"""
@staticmethod
def _create_disparity_tensor(batch_size, height, width, max_disparity, device, dtype):
size = (batch_size, height, width, 1)
return torch.randint(size=size, low=0, high=max_disparity, device=device, dtype=dtype)
@staticmethod
def test_stereo_camera_attributes_smoke(batch_size, device, dtype):
"""Test proper setup of the class for smoke data."""
tx_fx = -10
left_rectified_camera, right_rectified_camera = _SmokeTestData._create_stereo_camera(
batch_size, device, dtype, tx_fx
)
stereo_camera = StereoCamera(left_rectified_camera, right_rectified_camera)
def _assert_all(x, y):
assert torch.all(torch.eq(x, y))
_assert_all(stereo_camera.fx, _TestParams.fx)
_assert_all(stereo_camera.fy, _TestParams.fy)
_assert_all(stereo_camera.cx_left, _TestParams.cx)
_assert_all(stereo_camera.cy, _TestParams.cy)
_assert_all(stereo_camera.tx, -tx_fx / _TestParams.fx)
assert stereo_camera.Q.shape == (batch_size, 4, 4)
assert stereo_camera.Q.dtype in (torch.float16, torch.float32, torch.float64)
@staticmethod
def test_stereo_camera_attributes_real(batch_size, device, dtype):
"""Test proper setup of the class for real data."""
left_rectified_camera, right_rectified_camera = _RealTestData._get_real_stereo_camera(batch_size, device, dtype)
stereo_camera = StereoCamera(left_rectified_camera, right_rectified_camera)
assert_allclose(stereo_camera.fx, left_rectified_camera[..., 0, 0])
assert_allclose(stereo_camera.fy, left_rectified_camera[..., 1, 1])
assert_allclose(stereo_camera.cx_left, left_rectified_camera[..., 0, 2])
assert_allclose(stereo_camera.cy, left_rectified_camera[..., 1, 2])
assert_allclose(stereo_camera.tx, -right_rectified_camera[..., 0, 3] / right_rectified_camera[..., 0, 0])
assert stereo_camera.Q.shape == (batch_size, 4, 4)
assert stereo_camera.Q.dtype in (torch.float16, torch.float32, torch.float64)
def test_reproject_disparity_to_3D_smoke(self, batch_size, device, dtype):
"""Test reprojecting of disparity to 3D for smoke data."""
tx_fx = -10
left_rectified_camera, right_rectified_camera = _SmokeTestData._create_stereo_camera(
batch_size, device, dtype, tx_fx
)
disparity_tensor = self._create_disparity_tensor(
batch_size, _TestParams.height, _TestParams.width, max_disparity=2, device=device, dtype=dtype
)
stereo_camera = StereoCamera(left_rectified_camera, right_rectified_camera)
xyz = stereo_camera.reproject_disparity_to_3D(disparity_tensor)
assert xyz.shape == (batch_size, _TestParams.height, _TestParams.width, 3)
assert xyz.dtype in (torch.float16, torch.float32, torch.float64)
assert xyz.device == device
@staticmethod
def test_reproject_disparity_to_3D_real(batch_size, device, dtype):
"""Test reprojecting of disparity to 3D for known outcome."""
disparity_tensor = _RealTestData._get_real_disparity(batch_size, device, dtype)
xyz_gt = _RealTestData._get_real_point_cloud(batch_size, device, dtype)
left_rectified_camera, right_rectified_camera = _RealTestData._get_real_stereo_camera(batch_size, device, dtype)
stereo_camera = StereoCamera(left_rectified_camera, right_rectified_camera)
xyz = stereo_camera.reproject_disparity_to_3D(disparity_tensor)
assert_allclose(xyz, xyz_gt)
def test_reproject_disparity_to_3D_simple(self, batch_size, device, dtype):
"""Test reprojecting of disparity to 3D for real data."""
height, width = _RealTestData().height, _RealTestData().width
max_disparity = 80
disparity_tensor = self._create_disparity_tensor(
batch_size, height, width, max_disparity=max_disparity, device=device, dtype=dtype
)
left_rectified_camera, right_rectified_camera = _RealTestData._get_real_stereo_camera(batch_size, device, dtype)
stereo_camera = StereoCamera(left_rectified_camera, right_rectified_camera)
xyz = stereo_camera.reproject_disparity_to_3D(disparity_tensor)
assert xyz.shape == (batch_size, height, width, 3)
assert xyz.dtype in (torch.float16, torch.float32, torch.float64)
assert xyz.dtype == dtype
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