tensorbay.sensor.intrinsics#
Basic concepts of camera intrinsics.
- class tensorbay.sensor.intrinsics.CameraMatrix(fx=None, fy=None, cx=None, cy=None, skew=0, *, matrix=None)[source]#
Bases:
tensorbay.utility.repr.ReprMixin
,tensorbay.utility.attr.AttrsMixin
CameraMatrix represents camera matrix.
Camera matrix describes the mapping of a pinhole camera model from 3D points in the world to 2D points in an image.
- Parameters
fx (float) – The x axis focal length expressed in pixels.
fy (float) – The y axis focal length expressed in pixels.
cx (float) – The x coordinate of the so called principal point that should be in the center of the image.
cy (float) – The y coordinate of the so called principal point that should be in the center of the image.
skew (float) – It causes shear distortion in the projected image.
matrix (Optional[Union[Sequence[Sequence[float]], numpy.ndarray]]) – A 3x3 Sequence of camera matrix.
- Return type
None
- fx#
The x axis focal length expressed in pixels.
- Type
float
- fy#
The y axis focal length expressed in pixels.
- Type
float
- cx#
The x coordinate of the so called principal point that should be in the center of the image.
- Type
float
- cy#
The y coordinate of the so called principal point that should be in the center of the image.
- Type
float
- skew#
It causes shear distortion in the projected image.
- Type
float
- Raises
TypeError – When only keyword arguments with incorrect keys are provided, or when no arguments are provided.
- Parameters
fx (float) –
fy (float) –
cx (float) –
cy (float) –
skew (float) –
matrix (Optional[Union[Sequence[Sequence[float]], numpy.ndarray]]) –
- Return type
None
Examples
>>> matrix = [[1, 3, 3], ... [0, 2, 4], ... [0, 0, 1]]
Initialazation Method 1: Init from 3x3 sequence array.
>>> camera_matrix = CameraMatrix(matrix=matrix) >>> camera_matrix CameraMatrix( (fx): 1, (fy): 2, (cx): 3, (cy): 4, (skew): 3 )
Initialazation Method 2: Init from camera calibration parameters, skew is optional.
>>> camera_matrix = CameraMatrix(fx=1, fy=2, cx=3, cy=4, skew=3) >>> camera_matrix CameraMatrix( (fx): 1, (fy): 2, (cx): 3, (cy): 4, (skew): 3 )
- classmethod loads(contents)[source]#
Loads CameraMatrix from a dict containing the information of the camera matrix.
- Parameters
contents (Mapping[str, float]) – A dict containing the information of the camera matrix.
- Returns
A
CameraMatrix
instance contains the information from the contents dict.- Return type
tensorbay.sensor.intrinsics._T
Examples
>>> contents = { ... "fx": 2, ... "fy": 6, ... "cx": 4, ... "cy": 7, ... "skew": 3 ... } >>> camera_matrix = CameraMatrix.loads(contents) >>> camera_matrix CameraMatrix( (fx): 2, (fy): 6, (cx): 4, (cy): 7, (skew): 3 )
- dumps()[source]#
Dumps the camera matrix into a dict.
- Returns
A dict containing the information of the camera matrix.
- Return type
Dict[str, float]
Examples
>>> camera_matrix.dumps() {'fx': 1, 'fy': 2, 'cx': 3, 'cy': 4, 'skew': 3}
- as_matrix()[source]#
Return the camera matrix as a 3x3 numpy array.
- Returns
A 3x3 numpy array representing the camera matrix.
- Return type
numpy.ndarray
Examples
>>> numpy_array = camera_matrix.as_matrix() >>> numpy_array array([[1., 3., 3.], [0., 4., 4.], [0., 0., 1.]])
- project(point)[source]#
Project a point to the pixel coordinates.
- Parameters
point (Sequence[float]) – A Sequence containing the coordinates of the point to be projected.
- Returns
The pixel coordinates.
- Raises
TypeError – When the dimension of the input point is neither two nor three.
- Return type
Examples
Project a point in 2 dimensions
>>> camera_matrix.project([1, 2]) Vector2D(12, 19)
Project a point in 3 dimensions
>>> camera_matrix.project([1, 2, 4]) Vector2D(6.0, 10.0)
- class tensorbay.sensor.intrinsics.DistortionCoefficients(**kwargs)[source]#
Bases:
tensorbay.utility.repr.ReprMixin
,tensorbay.utility.attr.AttrsMixin
DistortionCoefficients represents camera distortion coefficients.
Distortion is the deviation from rectilinear projection including radial distortion and tangential distortion.
- Parameters
**kwargs – Float values with keys: k1, k2, … and p1, p2, …
kwargs (float) –
- Raises
TypeError – When tangential and radial distortion is not provided to initialize class.
- Return type
None
Examples
>>> distortion_coefficients = DistortionCoefficients(p1=1, p2=2, k1=3, k2=4) >>> distortion_coefficients DistortionCoefficients( (p1): 1, (p2): 2, (k1): 3, (k2): 4 )
- classmethod loads(contents)[source]#
Loads DistortionCoefficients from a dict containing the information.
- Parameters
contents (Mapping[str, float]) – A dict containig distortion coefficients of a camera.
- Returns
A
DistortionCoefficients
instance containing information from the contents dict.- Return type
tensorbay.sensor.intrinsics._T
Examples
>>> contents = { ... "p1": 1, ... "p2": 2, ... "k1": 3, ... "k2": 4 ... } >>> distortion_coefficients = DistortionCoefficients.loads(contents) >>> distortion_coefficients DistortionCoefficients( (p1): 1, (p2): 2, (k1): 3, (k2): 4 )
- dumps()[source]#
Dumps the distortion coefficients into a dict.
- Returns
A dict containing the information of distortion coefficients.
- Return type
Dict[str, float]
Examples
>>> distortion_coefficients.dumps() {'p1': 1, 'p2': 2, 'k1': 3, 'k2': 4}
- distort(point, is_fisheye=False)[source]#
Add distortion to a point.
- Parameters
point (Sequence[float]) – A Sequence containing the coordinates of the point to be distorted.
is_fisheye (bool) – Whether the sensor is fisheye camera, default is False.
- Raises
TypeError – When the dimension of the input point is neither two nor three.
- Returns
Distorted 2d point.
- Return type
Examples
Distort a point with 2 dimensions
>>> distortion_coefficients.distort((1.0, 2.0)) Vector2D(134.0, 253.0)
Distort a point with 3 dimensions
>>> distortion_coefficients.distort((1.0, 2.0, 3.0)) Vector2D(3.3004115226337447, 4.934156378600823)
Distort a point with 2 dimensions, fisheye is True
>>> distortion_coefficients.distort((1.0, 2.0), is_fisheye=True) Vector2D(6.158401093771876, 12.316802187543752)
- class tensorbay.sensor.intrinsics.CameraIntrinsics(fx=None, fy=None, cx=None, cy=None, skew=0, *, camera_matrix=None, **kwargs)[source]#
Bases:
tensorbay.utility.repr.ReprMixin
,tensorbay.utility.attr.AttrsMixin
CameraIntrinsics represents camera intrinsics.
Camera intrinsic parameters including camera matrix and distortion coeffecients. They describe the mapping of the scene in front of the camera to the pixels in the final image.
- Parameters
fx (Optional[float]) – The x axis focal length expressed in pixels.
fy (Optional[float]) – The y axis focal length expressed in pixels.
cx (Optional[float]) – The x coordinate of the so called principal point that should be in the center of the image.
cy (Optional[float]) – The y coordinate of the so called principal point that should be in the center of the image.
skew (float) – It causes shear distortion in the projected image.
camera_matrix (tensorbay.sensor.intrinsics.CameraMatrix) – A 3x3 Sequence of the camera matrix.
**kwargs – Float values to initialize
DistortionCoefficients
.kwargs (float) –
- Return type
None
- camera_matrix#
A 3x3 Sequence of the camera matrix.
- distortion_coefficients#
It is the deviation from rectilinear projection. It includes
- radial distortion and tangential distortion.
Examples
>>> matrix = [[1, 3, 3], ... [0, 2, 4], ... [0, 0, 1]]
Initialization Method 1: Init from 3x3 sequence array.
>>> camera_intrinsics = CameraIntrinsics(camera_matrix=matrix, p1=5, k1=6) >>> camera_intrinsics CameraIntrinsics( (camera_matrix): CameraMatrix( (fx): 1, (fy): 2, (cx): 3, (cy): 4, (skew): 3 ), (distortion_coefficients): DistortionCoefficients( (p1): 5, (k1): 6 ) )
Initialization Method 2: Init from camera calibration parameters, skew is optional.
>>> camera_intrinsics = CameraIntrinsics( ... fx=1, ... fy=2, ... cx=3, ... cy=4, ... p1=5, ... k1=6, ... skew=3 ... ) >>> camera_intrinsics CameraIntrinsics( (camera_matrix): CameraMatrix( (fx): 1, (fy): 2, (cx): 3, (cy): 4, (skew): 3 ), (distortion_coefficients): DistortionCoefficients( (p1): 5, (k1): 6 ) )
- classmethod loads(contents)[source]#
Loads CameraIntrinsics from a dict containing the information.
- Parameters
contents (Mapping[str, Mapping[str, float]]) – A dict containig camera matrix and distortion coefficients.
- Returns
A
CameraIntrinsics
instance containing information from the contents dict.- Return type
tensorbay.sensor.intrinsics._T
Examples
>>> contents = { ... "cameraMatrix": { ... "fx": 1, ... "fy": 2, ... "cx": 3, ... "cy": 4, ... }, ... "distortionCoefficients": { ... "p1": 1, ... "p2": 2, ... "k1": 3, ... "k2": 4 ... }, ... } >>> camera_intrinsics = CameraIntrinsics.loads(contents) >>> camera_intrinsics CameraIntrinsics( (camera_matrix): CameraMatrix( (fx): 1, (fy): 2, (cx): 3, (cy): 4, (skew): 0 ), (distortion_coefficients): DistortionCoefficients( (p1): 1, (p2): 2, (k1): 3, (k2): 4 ) )
- dumps()[source]#
Dumps the camera intrinsics into a dict.
- Returns
A dict containing camera intrinsics.
- Return type
Dict[str, Dict[str, float]]
Examples
>>> camera_intrinsics.dumps() {'cameraMatrix': {'fx': 1, 'fy': 2, 'cx': 3, 'cy': 4, 'skew': 3}, 'distortionCoefficients': {'p1': 5, 'k1': 6}}
- set_camera_matrix(fx=None, fy=None, cx=None, cy=None, skew=0, *, matrix=None)[source]#
Set camera matrix of the camera intrinsics.
- Parameters
fx (Optional[float]) – The x axis focal length expressed in pixels.
fy (Optional[float]) – The y axis focal length expressed in pixels.
cx (Optional[float]) – The x coordinate of the so called principal point that should be in the center of the image.
cy (Optional[float]) – The y coordinate of the so called principal point that should be in the center of the image.
skew (float) – It causes shear distortion in the projected image.
matrix (Optional[Union[Sequence[Sequence[float]], numpy.ndarray]]) – Camera matrix in 3x3 sequence.
- Return type
None
Examples
>>> camera_intrinsics.set_camera_matrix(fx=11, fy=12, cx=13, cy=14, skew=15) >>> camera_intrinsics CameraIntrinsics( (camera_matrix): CameraMatrix( (fx): 11, (fy): 12, (cx): 13, (cy): 14, (skew): 15 ), (distortion_coefficients): DistortionCoefficients( (p1): 1, (p2): 2, (k1): 3, (k2): 4 ) )
- set_distortion_coefficients(**kwargs)[source]#
Set distortion coefficients of the camera intrinsics.
- Parameters
**kwargs – Contains p1, p2, …, k1, k2, …
kwargs (float) –
- Return type
None
Examples
>>> camera_intrinsics.set_distortion_coefficients(p1=11, p2=12, k1=13, k2=14) >>> camera_intrinsics CameraIntrinsics( (camera_matrix): CameraMatrix( (fx): 11, (fy): 12, (cx): 13, (cy): 14, (skew): 15 ), (distortion_coefficients): DistortionCoefficients( (p1): 11, (p2): 12, (k1): 13, (k2): 14 ) )
- project(point, is_fisheye=False)[source]#
Project a point to the pixel coordinates.
If distortion coefficients are provided, distort the point before projection.
- Parameters
point (Sequence[float]) – A Sequence containing coordinates of the point to be projected.
is_fisheye (bool) – Whether the sensor is fisheye camera, default is False.
- Returns
The coordinates on the pixel plane where the point is projected to.
- Return type
Examples
Project a point with 2 dimensions.
>>> camera_intrinsics.project((1, 2)) Vector2D(137.0, 510.0)
Project a point with 3 dimensions.
>>> camera_intrinsics.project((1, 2, 3)) Vector2D(6.300411522633745, 13.868312757201647)
Project a point with 2 dimensions, fisheye is True
>>> camera_intrinsics.project((1, 2), is_fisheye=True) Vector2D(9.158401093771875, 28.633604375087504)