tensorbay.sensor.intrinsics

CameraMatrix, DistortionCoefficients and CameraIntrinsics.

CameraMatrix represents camera matrix. It describes the mapping of a pinhole camera model from 3D points in the world to 2D points in an image.

DistortionCoefficients represents camera distortion coefficients. It is the deviation from rectilinear projection including radial distortion and tangential distortion.

CameraIntrinsics represents camera intrinsics including camera matrix and distortion coeffecients. It describes the mapping of the scene in front of the camera to the pixels in the final image.

CameraMatrix, DistortionCoefficients and CameraIntrinsics class can all be initialized by __init__() or loads() method.

class tensorbay.sensor.intrinsics.CameraMatrix(fx: Optional[float] = None, fy: Optional[float] = None, cx: Optional[float] = None, cy: Optional[float] = None, skew: float = 0, *, matrix: Optional[Union[Sequence[Sequence[float]], numpy.ndarray]] = 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 – The x axis focal length expressed in pixels.
fy – The y axis focal length expressed in pixels.
cx – The x coordinate of the so called principal point that should be in the center of the image.
cy – The y coordinate of the so called principal point that should be in the center of the image.
skew – It causes shear distortion in the projected image.
matrix – A 3x3 Sequence of camera matrix.

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.

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: Dict[str, float]) → tensorbay.sensor.intrinsics._T[source]

Loads CameraMatrix from a dict containing the information of the camera matrix.

Parameters: contents – A dict containing the information of the camera matrix.
Returns: A CameraMatrix instance contains the information from the contents dict.

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() → Dict[str, float][source]

Dumps the camera matrix into a dict.

Returns: A dict containing the information of the camera matrix.

Examples

>>> camera_matrix.dumps()
{'fx': 1, 'fy': 2, 'cx': 3, 'cy': 4, 'skew': 3}

as_matrix() → numpy.ndarray[source]

Return the camera matrix as a 3x3 numpy array.

Returns: A 3x3 numpy array representing the camera matrix.

Examples

>>> numpy_array = camera_matrix.as_matrix()
>>> numpy_array
array([[1., 3., 3.],
       [0., 4., 4.],
       [0., 0., 1.]])

project(point: Sequence[float]) → tensorbay.geometry.vector.Vector2D[source]

Project a point to the pixel coordinates.

Parameters: point – 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.

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: float)[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, …
Raises: TypeError – When tangential and radial distortion is not provided to initialize class.

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: Dict[str, float]) → tensorbay.sensor.intrinsics._T[source]

Loads DistortionCoefficients from a dict containing the information.

Parameters: contents – A dict containig distortion coefficients of a camera.
Returns: A DistortionCoefficients instance containing information from the contents dict.

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() → Dict[str, float][source]

Dumps the distortion coefficients into a dict.

Returns: A dict containing the information of distortion coefficients.

Examples

>>> distortion_coefficients.dumps()
{'p1': 1, 'p2': 2, 'k1': 3, 'k2': 4}

distort(point: Sequence[float], is_fisheye: bool = False) → tensorbay.geometry.vector.Vector2D[source]

Add distortion to a point.

Parameters

point – A Sequence containing the coordinates of the point to be distorted.
is_fisheye – 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.

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: Optional[float] = None, fy: Optional[float] = None, cx: Optional[float] = None, cy: Optional[float] = None, skew: float = 0, *, camera_matrix: Optional[Union[Sequence[Sequence[float]], numpy.ndarray]] = None, **kwargs: float)[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 – The x axis focal length expressed in pixels.
fy – The y axis focal length expressed in pixels.
cx – The x coordinate of the so called principal point that should be in the center of the image.
cy – The y coordinate of the so called principal point that should be in the center of the image.
skew – It causes shear distortion in the projected image.
camera_matrix – A 3x3 Sequence of the camera matrix.
**kwargs – Float values to initialize DistortionCoefficients.

camera_matrix

A 3x3 Sequence of the camera matrix.

Type: tensorbay.sensor.intrinsics.CameraMatrix

distortion_coefficients

It is the deviation from rectilinear projection. It includes

Type: tensorbay.sensor.intrinsics.DistortionCoefficients

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: Dict[str, Dict[str, float]]) → tensorbay.sensor.intrinsics._T[source]

Loads CameraIntrinsics from a dict containing the information.

Parameters: contents – A dict containig camera matrix and distortion coefficients.
Returns: A CameraIntrinsics instance containing information from the contents dict.

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() → Dict[str, Dict[str, float]][source]

Dumps the camera intrinsics into a dict.

Returns: A dict containing camera intrinsics.

Examples

>>> camera_intrinsics.dumps()
{'cameraMatrix': {'fx': 1, 'fy': 2, 'cx': 3, 'cy': 4, 'skew': 3},
'distortionCoefficients': {'p1': 5, 'k1': 6}}

set_camera_matrix(fx: Optional[float] = None, fy: Optional[float] = None, cx: Optional[float] = None, cy: Optional[float] = None, skew: float = 0, *, matrix: Optional[Union[Sequence[Sequence[float]], numpy.ndarray]] = None) → None[source]

Set camera matrix of the camera intrinsics.

Parameters

fx – The x axis focal length expressed in pixels.
fy – The y axis focal length expressed in pixels.
cx – The x coordinate of the so called principal point that should be in the center of the image.
cy – The y coordinate of the so called principal point that should be in the center of the image.
skew – It causes shear distortion in the projected image.
matrix – Camera matrix in 3x3 sequence.

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: float) → None[source]

Set distortion coefficients of the camera intrinsics.

Parameters: **kwargs – Contains p1, p2, …, k1, k2, …

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: Sequence[float], is_fisheye: bool = False) → tensorbay.geometry.vector.Vector2D[source]

Project a point to the pixel coordinates.

If distortion coefficients are provided, distort the point before projection.

Parameters

point – A Sequence containing coordinates of the point to be projected.
is_fisheye – Whether the sensor is fisheye camera, default is False.

Returns

The coordinates on the pixel plane where the point is projected to.

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)