ImageTools¶

class ImageTools¶

Bases: pybind11_object

Various image tools; sub-image extraction, modification of the look up table, binarisation…

Methods

`__init__`
`binarise`	Overloaded function.
`changeLUT`	Change the look up table (LUT) of an image.
`columnMean`	Compute the column-wise mean intensities.
`crop`	Overloaded function.
`extract`	Overloaded function.
`flip`	Overloaded function.
`imageAdd`	Compute the image addition: \(Ires = I1 + I2\) .
`imageDifference`	Overloaded function.
`imageDifferenceAbsolute`	Overloaded function.
`imageSubtract`	Compute the image addition: \(Ires = I1 - I2\) .
`inMask`	Overloaded function.
`initUndistortMap`	Compute the undistortion transformation map.
`integralImage`	Compute the integral images:
`interpolate`
`normalize`	Normalize the image intensities.
`normalizedCorrelation`	Compute a correlation between 2 images.
`remap`	Overloaded function.
`resize`	Overloaded function.
`templateMatching`	Match a template image into another image using zero-mean normalized cross-correlation:
`undistort`	Overloaded function.
`warpImage`	Overloaded function.

Inherited Methods

Operators

`__doc__`
`__init__`
`__module__`

Attributes

`INTERPOLATION_AREA`
`INTERPOLATION_CUBIC`
`INTERPOLATION_LINEAR`
`INTERPOLATION_NEAREST`
`__annotations__`

class ImageInterpolationType(self, value: int)¶

Bases: pybind11_object

Values:

INTERPOLATION_NEAREST: Nearest neighbor interpolation.
INTERPOLATION_LINEAR: Bi-linear interpolation (optimized by SIMD lib if enabled).
INTERPOLATION_CUBIC: Bi-cubic interpolation.
INTERPOLATION_AREA: Area interpolation (optimized by SIMD lib if enabled).

__and__(self, other: object) → object¶

__eq__(self, other: object) → bool¶

__ge__(self, other: object) → bool¶

__getstate__(self) → int¶

__gt__(self, other: object) → bool¶

__hash__(self) → int¶

__index__(self) → int¶

__init__(self, value: int)¶

__int__(self) → int¶

__invert__(self) → object¶

__le__(self, other: object) → bool¶

__lt__(self, other: object) → bool¶

__ne__(self, other: object) → bool¶

__or__(self, other: object) → object¶

__rand__(self, other: object) → object¶

__ror__(self, other: object) → object¶

__rxor__(self, other: object) → object¶

__setstate__(self, state: int) → None¶

__xor__(self, other: object) → object¶

property name : str¶

__init__(*args, **kwargs)¶

static binarise(*args, **kwargs)¶

Overloaded function.

binarise(I: visp._visp.core.ImageGray, threshold1: int, threshold2: int, value1: int, value2: int, value3: int, useLUT: bool = true) -> None

Binarise an image.

Pixels whose values are less than threshold1 are set to value1
Pixels whose values are greater then or equal to threshold1 and less then or equal to threshold2 are set to value2
Pixels whose values are greater than threshold2 are set to value3

binarise(I: visp._visp.core.ImageFloat, threshold1: float, threshold2: float, value1: float, value2: float, value3: float, useLUT: bool = true) -> None

Binarise an image.

Pixels whose values are less than threshold1 are set to value1
Pixels whose values are greater then or equal to threshold1 and less then or equal to threshold2 are set to value2
Pixels whose values are greater than threshold2 are set to value3

binarise(I: visp._visp.core.ImageDouble, threshold1: float, threshold2: float, value1: float, value2: float, value3: float, useLUT: bool = true) -> None

Binarise an image.

Pixels whose values are less than threshold1 are set to value1
Pixels whose values are greater then or equal to threshold1 and less then or equal to threshold2 are set to value2
Pixels whose values are greater than threshold2 are set to value3

binarise(I: visp._visp.core.ImageRGBa, threshold1: visp._visp.core.RGBa, threshold2: visp._visp.core.RGBa, value1: visp._visp.core.RGBa, value2: visp._visp.core.RGBa, value3: visp._visp.core.RGBa, useLUT: bool = true) -> None

Binarise an image.

Pixels whose values are less than threshold1 are set to value1
Pixels whose values are greater then or equal to threshold1 and less then or equal to threshold2 are set to value2
Pixels whose values are greater than threshold2 are set to value3

static changeLUT(I: visp.core.ImageGray, A: int, newA: int, B: int, newB: int) → None¶

Change the look up table (LUT) of an image. Considering pixel gray level values \(l\) in the range \([A, B]\) , this method allows to rescale these values in \([A^*, B^*]\) by linear interpolation:

\(\left\{ \begin{array}{ll} l \in ]-\infty, A] \mbox{, } & l = A^* \\l \in [B, \infty[ \mbox{, } & l = B^* \\l \in ]A, B[ \mbox{, } & l = A^* + (l-A) * \frac{B^*-A^*}{B-A} \end{array} \right.\)

As shown in the example below, this method can be used to binarize an image. For an unsigned char image (in the range 0-255), thresholding this image at level 127 can be done by:

#include <visp3/core/vpImage.h>
#include <visp3/core/vpImageTools.h>
#include <visp3/io/vpImageIo.h>

#ifdef ENABLE_VISP_NAMESPACE
using namespace VISP_NAMESPACE_NAME;
#endif

int main()
{
  vpImage<unsigned char> I;
#ifdef _WIN32
  std::string filename("C:/Temp/visp-images/Klimt/Klimt.ppm");
#else
  std::string filename("/local/soft/ViSP/ViSP-images/Klimt/Klimt.ppm");
#endif

  // Read an image from the disk
  vpImageIo::read(I, filename);

  // Binarize image I:
  // - gray level values less than or equal to 127 are set to 0,
  // - gray level values greater than 128 are set to 255
  vpImageTools::changeLUT(I, 127, 0, 128, 255);

  vpImageIo::write(I, "Klimt.pgm"); // Write the image in a PGM P5 image file format
}

Parameters:

I: visp.core.ImageGray¶: Image to process.
A: int¶: Low gray level value of the range to consider.
B: int¶: Height gray level value of the range to consider.

static columnMean(I: visp.core.ImageDouble, result: visp.core.RowVector) → None¶

Compute the column-wise mean intensities.

Parameters:

I: visp.core.ImageDouble¶: The image.

static crop(*args, **kwargs)¶

Overloaded function.

crop(I: visp._visp.core.ImageGray, roi_top: float, roi_left: float, roi_height: int, roi_width: int, crop: visp._visp.core.ImageGray, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Note

See crop(const vpImage<Type> &, const vpRect &, vpImage<Type> &)

Parameters:

I: Input image from which a sub image will be extracted.
roi_top: ROI vertical position of the upper/left corner in the input image.
roi_left: ROI horizontal position of the upper/left corner in the input image.
roi_height: Cropped image height corresponding to the ROI height.
roi_width: Cropped image width corresponding to the ROI height.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageUInt16, roi_top: float, roi_left: float, roi_height: int, roi_width: int, crop: visp._visp.core.ImageUInt16, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Note

See crop(const vpImage<Type> &, const vpRect &, vpImage<Type> &)

Parameters:

I: Input image from which a sub image will be extracted.
roi_top: ROI vertical position of the upper/left corner in the input image.
roi_left: ROI horizontal position of the upper/left corner in the input image.
roi_height: Cropped image height corresponding to the ROI height.
roi_width: Cropped image width corresponding to the ROI height.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageFloat, roi_top: float, roi_left: float, roi_height: int, roi_width: int, crop: visp._visp.core.ImageFloat, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Note

See crop(const vpImage<Type> &, const vpRect &, vpImage<Type> &)

Parameters:

I: Input image from which a sub image will be extracted.
roi_top: ROI vertical position of the upper/left corner in the input image.
roi_left: ROI horizontal position of the upper/left corner in the input image.
roi_height: Cropped image height corresponding to the ROI height.
roi_width: Cropped image width corresponding to the ROI height.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageDouble, roi_top: float, roi_left: float, roi_height: int, roi_width: int, crop: visp._visp.core.ImageDouble, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Note

See crop(const vpImage<Type> &, const vpRect &, vpImage<Type> &)

Parameters:

I: Input image from which a sub image will be extracted.
roi_top: ROI vertical position of the upper/left corner in the input image.
roi_left: ROI horizontal position of the upper/left corner in the input image.
roi_height: Cropped image height corresponding to the ROI height.
roi_width: Cropped image width corresponding to the ROI height.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: vpImage<bool>, roi_top: float, roi_left: float, roi_height: int, roi_width: int, crop: vpImage<bool>, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Note

See crop(const vpImage<Type> &, const vpRect &, vpImage<Type> &)

Parameters:

I: Input image from which a sub image will be extracted.
roi_top: ROI vertical position of the upper/left corner in the input image.
roi_left: ROI horizontal position of the upper/left corner in the input image.
roi_height: Cropped image height corresponding to the ROI height.
roi_width: Cropped image width corresponding to the ROI height.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageRGBa, roi_top: float, roi_left: float, roi_height: int, roi_width: int, crop: visp._visp.core.ImageRGBa, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Note

See crop(const vpImage<Type> &, const vpRect &, vpImage<Type> &)

Parameters:

I: Input image from which a sub image will be extracted.
roi_top: ROI vertical position of the upper/left corner in the input image.
roi_left: ROI horizontal position of the upper/left corner in the input image.
roi_height: Cropped image height corresponding to the ROI height.
roi_width: Cropped image width corresponding to the ROI height.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageRGBf, roi_top: float, roi_left: float, roi_height: int, roi_width: int, crop: visp._visp.core.ImageRGBf, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Note

See crop(const vpImage<Type> &, const vpRect &, vpImage<Type> &)

Parameters:

I: Input image from which a sub image will be extracted.
roi_top: ROI vertical position of the upper/left corner in the input image.
roi_left: ROI horizontal position of the upper/left corner in the input image.
roi_height: Cropped image height corresponding to the ROI height.
roi_width: Cropped image width corresponding to the ROI height.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageGray, topLeft: visp._visp.core.ImagePoint, roi_height: int, roi_width: int, crop: visp._visp.core.ImageGray, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Note

See crop(const vpImage<Type> &, const vpRect &, vpImage<Type> &)

Parameters:

I: Input image from which a sub image will be extracted.
topLeft: ROI position of the upper/left corner in the input image.
roi_height: Cropped image height corresponding to the ROI height.
roi_width: Cropped image width corresponding to the ROI height.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageUInt16, topLeft: visp._visp.core.ImagePoint, roi_height: int, roi_width: int, crop: visp._visp.core.ImageUInt16, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Note

See crop(const vpImage<Type> &, const vpRect &, vpImage<Type> &)

Parameters:

I: Input image from which a sub image will be extracted.
topLeft: ROI position of the upper/left corner in the input image.
roi_height: Cropped image height corresponding to the ROI height.
roi_width: Cropped image width corresponding to the ROI height.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageFloat, topLeft: visp._visp.core.ImagePoint, roi_height: int, roi_width: int, crop: visp._visp.core.ImageFloat, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Note

See crop(const vpImage<Type> &, const vpRect &, vpImage<Type> &)

Parameters:

I: Input image from which a sub image will be extracted.
topLeft: ROI position of the upper/left corner in the input image.
roi_height: Cropped image height corresponding to the ROI height.
roi_width: Cropped image width corresponding to the ROI height.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageDouble, topLeft: visp._visp.core.ImagePoint, roi_height: int, roi_width: int, crop: visp._visp.core.ImageDouble, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Note

See crop(const vpImage<Type> &, const vpRect &, vpImage<Type> &)

Parameters:

I: Input image from which a sub image will be extracted.
topLeft: ROI position of the upper/left corner in the input image.
roi_height: Cropped image height corresponding to the ROI height.
roi_width: Cropped image width corresponding to the ROI height.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: vpImage<bool>, topLeft: visp._visp.core.ImagePoint, roi_height: int, roi_width: int, crop: vpImage<bool>, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Note

See crop(const vpImage<Type> &, const vpRect &, vpImage<Type> &)

Parameters:

I: Input image from which a sub image will be extracted.
topLeft: ROI position of the upper/left corner in the input image.
roi_height: Cropped image height corresponding to the ROI height.
roi_width: Cropped image width corresponding to the ROI height.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageRGBa, topLeft: visp._visp.core.ImagePoint, roi_height: int, roi_width: int, crop: visp._visp.core.ImageRGBa, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Note

See crop(const vpImage<Type> &, const vpRect &, vpImage<Type> &)

Parameters:

I: Input image from which a sub image will be extracted.
topLeft: ROI position of the upper/left corner in the input image.
roi_height: Cropped image height corresponding to the ROI height.
roi_width: Cropped image width corresponding to the ROI height.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageRGBf, topLeft: visp._visp.core.ImagePoint, roi_height: int, roi_width: int, crop: visp._visp.core.ImageRGBf, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Note

See crop(const vpImage<Type> &, const vpRect &, vpImage<Type> &)

Parameters:

I: Input image from which a sub image will be extracted.
topLeft: ROI position of the upper/left corner in the input image.
roi_height: Cropped image height corresponding to the ROI height.
roi_width: Cropped image width corresponding to the ROI height.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageGray, roi: visp._visp.core.Rect, crop: visp._visp.core.ImageGray, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Parameters:

I: Input image from which a sub image will be extracted.
roi: Region of interest in image I corresponding to the cropped part of the image.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageUInt16, roi: visp._visp.core.Rect, crop: visp._visp.core.ImageUInt16, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Parameters:

I: Input image from which a sub image will be extracted.
roi: Region of interest in image I corresponding to the cropped part of the image.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageFloat, roi: visp._visp.core.Rect, crop: visp._visp.core.ImageFloat, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Parameters:

I: Input image from which a sub image will be extracted.
roi: Region of interest in image I corresponding to the cropped part of the image.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageDouble, roi: visp._visp.core.Rect, crop: visp._visp.core.ImageDouble, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Parameters:

I: Input image from which a sub image will be extracted.
roi: Region of interest in image I corresponding to the cropped part of the image.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: vpImage<bool>, roi: visp._visp.core.Rect, crop: vpImage<bool>, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Parameters:

I: Input image from which a sub image will be extracted.
roi: Region of interest in image I corresponding to the cropped part of the image.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageRGBa, roi: visp._visp.core.Rect, crop: visp._visp.core.ImageRGBa, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Parameters:

I: Input image from which a sub image will be extracted.
roi: Region of interest in image I corresponding to the cropped part of the image.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

crop(I: visp._visp.core.ImageRGBf, roi: visp._visp.core.Rect, crop: visp._visp.core.ImageRGBf, v_scale: int = 1, h_scale: int = 1) -> None

Crop a region of interest (ROI) in an image. The ROI coordinates and dimension are defined in the original image.

Setting v_scale and h_scale to values different from 1 allows also to subsample the cropped image.

Parameters:

I: Input image from which a sub image will be extracted.
roi: Region of interest in image I corresponding to the cropped part of the image.
crop: Cropped image.
v_scale: [in] : Vertical subsampling factor applied to the ROI.
h_scale: [in] : Horizontal subsampling factor applied to the ROI.

static extract(*args, **kwargs)¶

Overloaded function.

extract(src: visp._visp.core.ImageGray, dst: visp._visp.core.ImageGray, r: visp._visp.core.RectOriented) -> None

Extract a rectangular region from an image.

Parameters:

src: The source image.
dst: The resulting image.
r: The rectangle area.

extract(src: visp._visp.core.ImageGray, dst: visp._visp.core.ImageDouble, r: visp._visp.core.RectOriented) -> None

Extract a rectangular region from an image.

Parameters:

src: The source image.
dst: The resulting image.
r: The rectangle area.

static flip(*args, **kwargs)¶

Overloaded function.

flip(I: visp._visp.core.ImageGray, newI: visp._visp.core.ImageGray) -> None

Flip vertically the input image and give the result in the output image.

Parameters:

I: Input image to flip.
newI: Output image which is the flipped input image.

flip(I: visp._visp.core.ImageUInt16, newI: visp._visp.core.ImageUInt16) -> None

Flip vertically the input image and give the result in the output image.

Parameters:

I: Input image to flip.
newI: Output image which is the flipped input image.

flip(I: visp._visp.core.ImageFloat, newI: visp._visp.core.ImageFloat) -> None

Flip vertically the input image and give the result in the output image.

Parameters:

I: Input image to flip.
newI: Output image which is the flipped input image.

flip(I: visp._visp.core.ImageDouble, newI: visp._visp.core.ImageDouble) -> None

Flip vertically the input image and give the result in the output image.

Parameters:

I: Input image to flip.
newI: Output image which is the flipped input image.

flip(I: vpImage<bool>, newI: vpImage<bool>) -> None

Flip vertically the input image and give the result in the output image.

Parameters:

I: Input image to flip.
newI: Output image which is the flipped input image.

flip(I: visp._visp.core.ImageRGBa, newI: visp._visp.core.ImageRGBa) -> None

Flip vertically the input image and give the result in the output image.

Parameters:

I: Input image to flip.
newI: Output image which is the flipped input image.

flip(I: visp._visp.core.ImageRGBf, newI: visp._visp.core.ImageRGBf) -> None

Flip vertically the input image and give the result in the output image.

Parameters:

I: Input image to flip.
newI: Output image which is the flipped input image.

flip(I: visp._visp.core.ImageGray) -> None

Flip vertically the input image.

The following example shows how to use this function:

#include <visp3/core/vpImage.h>
#include <visp3/core/vpImageTools.h>
#include <visp3/io/vpImageIo.h>

#ifdef ENABLE_VISP_NAMESPACE
using namespace VISP_NAMESPACE_NAME;
#endif

int main()
{
  vpImage<vpRGBa> I;
#ifdef _WIN32
  std::string filename("C:/Temp/visp-images/Klimt/Klimt.ppm");
#else
  std::string filename("/local/soft/ViSP/ViSP-images/Klimt/Klimt.ppm");
#endif

  // Read an image from the disk
  vpImageIo::read(I, filename);

  // Flip the image
  vpImageTools::flip(I);

  // Write the image in a PGM P5 image file format
  vpImageIo::write(I, "Klimt-flip.ppm");
}

Parameters:

I: Input image which is flipped and modified in output.

flip(I: visp._visp.core.ImageUInt16) -> None

Flip vertically the input image.

The following example shows how to use this function:

#include <visp3/core/vpImage.h>
#include <visp3/core/vpImageTools.h>
#include <visp3/io/vpImageIo.h>

#ifdef ENABLE_VISP_NAMESPACE
using namespace VISP_NAMESPACE_NAME;
#endif

int main()
{
  vpImage<vpRGBa> I;
#ifdef _WIN32
  std::string filename("C:/Temp/visp-images/Klimt/Klimt.ppm");
#else
  std::string filename("/local/soft/ViSP/ViSP-images/Klimt/Klimt.ppm");
#endif

  // Read an image from the disk
  vpImageIo::read(I, filename);

  // Flip the image
  vpImageTools::flip(I);

  // Write the image in a PGM P5 image file format
  vpImageIo::write(I, "Klimt-flip.ppm");
}

Parameters:

I: Input image which is flipped and modified in output.

flip(I: visp._visp.core.ImageFloat) -> None

Flip vertically the input image.

The following example shows how to use this function:

#include <visp3/core/vpImage.h>
#include <visp3/core/vpImageTools.h>
#include <visp3/io/vpImageIo.h>

#ifdef ENABLE_VISP_NAMESPACE
using namespace VISP_NAMESPACE_NAME;
#endif

int main()
{
  vpImage<vpRGBa> I;
#ifdef _WIN32
  std::string filename("C:/Temp/visp-images/Klimt/Klimt.ppm");
#else
  std::string filename("/local/soft/ViSP/ViSP-images/Klimt/Klimt.ppm");
#endif

  // Read an image from the disk
  vpImageIo::read(I, filename);

  // Flip the image
  vpImageTools::flip(I);

  // Write the image in a PGM P5 image file format
  vpImageIo::write(I, "Klimt-flip.ppm");
}

Parameters:

I: Input image which is flipped and modified in output.

flip(I: visp._visp.core.ImageDouble) -> None

Flip vertically the input image.

The following example shows how to use this function:

#include <visp3/core/vpImage.h>
#include <visp3/core/vpImageTools.h>
#include <visp3/io/vpImageIo.h>

#ifdef ENABLE_VISP_NAMESPACE
using namespace VISP_NAMESPACE_NAME;
#endif

int main()
{
  vpImage<vpRGBa> I;
#ifdef _WIN32
  std::string filename("C:/Temp/visp-images/Klimt/Klimt.ppm");
#else
  std::string filename("/local/soft/ViSP/ViSP-images/Klimt/Klimt.ppm");
#endif

  // Read an image from the disk
  vpImageIo::read(I, filename);

  // Flip the image
  vpImageTools::flip(I);

  // Write the image in a PGM P5 image file format
  vpImageIo::write(I, "Klimt-flip.ppm");
}

Parameters:

I: Input image which is flipped and modified in output.

flip(I: vpImage<bool>) -> None

Flip vertically the input image.

The following example shows how to use this function:

#include <visp3/core/vpImage.h>
#include <visp3/core/vpImageTools.h>
#include <visp3/io/vpImageIo.h>

#ifdef ENABLE_VISP_NAMESPACE
using namespace VISP_NAMESPACE_NAME;
#endif

int main()
{
  vpImage<vpRGBa> I;
#ifdef _WIN32
  std::string filename("C:/Temp/visp-images/Klimt/Klimt.ppm");
#else
  std::string filename("/local/soft/ViSP/ViSP-images/Klimt/Klimt.ppm");
#endif

  // Read an image from the disk
  vpImageIo::read(I, filename);

  // Flip the image
  vpImageTools::flip(I);

  // Write the image in a PGM P5 image file format
  vpImageIo::write(I, "Klimt-flip.ppm");
}

Parameters:

I: Input image which is flipped and modified in output.

flip(I: visp._visp.core.ImageRGBa) -> None

Flip vertically the input image.

The following example shows how to use this function:

#include <visp3/core/vpImage.h>
#include <visp3/core/vpImageTools.h>
#include <visp3/io/vpImageIo.h>

#ifdef ENABLE_VISP_NAMESPACE
using namespace VISP_NAMESPACE_NAME;
#endif

int main()
{
  vpImage<vpRGBa> I;
#ifdef _WIN32
  std::string filename("C:/Temp/visp-images/Klimt/Klimt.ppm");
#else
  std::string filename("/local/soft/ViSP/ViSP-images/Klimt/Klimt.ppm");
#endif

  // Read an image from the disk
  vpImageIo::read(I, filename);

  // Flip the image
  vpImageTools::flip(I);

  // Write the image in a PGM P5 image file format
  vpImageIo::write(I, "Klimt-flip.ppm");
}

Parameters:

I: Input image which is flipped and modified in output.

flip(I: visp._visp.core.ImageRGBf) -> None

Flip vertically the input image.

The following example shows how to use this function:

#include <visp3/core/vpImage.h>
#include <visp3/core/vpImageTools.h>
#include <visp3/io/vpImageIo.h>

#ifdef ENABLE_VISP_NAMESPACE
using namespace VISP_NAMESPACE_NAME;
#endif

int main()
{
  vpImage<vpRGBa> I;
#ifdef _WIN32
  std::string filename("C:/Temp/visp-images/Klimt/Klimt.ppm");
#else
  std::string filename("/local/soft/ViSP/ViSP-images/Klimt/Klimt.ppm");
#endif

  // Read an image from the disk
  vpImageIo::read(I, filename);

  // Flip the image
  vpImageTools::flip(I);

  // Write the image in a PGM P5 image file format
  vpImageIo::write(I, "Klimt-flip.ppm");
}

Parameters:

I: Input image which is flipped and modified in output.

static imageAdd(I1: visp.core.ImageGray, I2: visp.core.ImageGray, Ires: visp.core.ImageGray, saturate: bool = false) → None¶

Compute the image addition: \(Ires = I1 + I2\) .

Note

The simd lib is used to accelerate processing on x86 and ARM architecture.

Warning

This function does not work in-place (Ires object must be different from I1 and I2).

Parameters:

I1: visp.core.ImageGray¶: The first image.
I2: visp.core.ImageGray¶: The second image.
Ires: visp.core.ImageGray¶: math:Ires = I1 + I2
saturate: bool = false¶: If true, saturate the result to [0 ; 255] using vpMath::saturate , otherwise overflow may occur.

static imageDifference(*args, **kwargs)¶

Overloaded function.

imageDifference(I1: visp._visp.core.ImageGray, I2: visp._visp.core.ImageGray, Idiff: visp._visp.core.ImageGray) -> None

Compute the signed difference between the two images I1 and I2 for visualization purpose: Idiff = I1-I2

pixels with a null difference are set to 128.
A negative difference implies a pixel value < 128
A positive difference implies a pixel value > 128

Parameters:

I1: The first image.
I2: The second image.
Idiff: The result of the difference.

imageDifference(I1: visp._visp.core.ImageRGBa, I2: visp._visp.core.ImageRGBa, Idiff: visp._visp.core.ImageRGBa) -> None

Compute the signed difference between the two images I1 and I2 RGB components for visualization purpose: Idiff = I1-I2. The fourth component named A is not compared. It is set to 0 in the resulting difference image.

pixels with a null difference are set to R=128, G=128, B=128.
A negative difference implies a pixel R, G, B value < 128
A positive difference implies a pixel R, G, B value > 128

Parameters:

I1: The first image.
I2: The second image.
Idiff: The result of the difference between RGB components.

static imageDifferenceAbsolute(*args, **kwargs)¶

Overloaded function.

imageDifferenceAbsolute(I1: visp._visp.core.ImageGray, I2: visp._visp.core.ImageGray, Idiff: visp._visp.core.ImageGray) -> None

Compute the difference between the two images I1 and I2

Warning

: This is NOT for visualization If you want to visualize difference images during servo, please use vpImageTools::imageDifference (..,..,..) function.

Parameters:

I1: The first image.
I2: The second image.
Idiff: The result of the difference.

imageDifferenceAbsolute(I1: visp._visp.core.ImageDouble, I2: visp._visp.core.ImageDouble, Idiff: visp._visp.core.ImageDouble) -> None

Compute the difference between the two images I1 and I2.

Parameters:

I1: The first image.
I2: The second image.
Idiff: The result of the difference.

imageDifferenceAbsolute(I1: visp._visp.core.ImageRGBa, I2: visp._visp.core.ImageRGBa, Idiff: visp._visp.core.ImageRGBa) -> None

Compute the difference between the two images I1 and I2 RGB components. The fourth component named A is not compared. It is set to 0 in the resulting difference image.

Warning

: This is NOT for visualization. If you want to visualize difference images during servo, please use vpImageTools::imageDifference (..,..,..) function.

Parameters:

I1: The first image.
I2: The second image.
Idiff: The result of the difference between RGB components.

static imageSubtract(I1: visp.core.ImageGray, I2: visp.core.ImageGray, Ires: visp.core.ImageGray, saturate: bool = false) → None¶

Compute the image addition: \(Ires = I1 - I2\) .

Note

The simd lib is used to accelerate processing on x86 and ARM architecture.

Warning

This function does not work in-place (Ires object must be different from I1 and I2).

Parameters:

I1: visp.core.ImageGray¶: The first image.
I2: visp.core.ImageGray¶: The second image.
Ires: visp.core.ImageGray¶: math:Ires = I1 - I2
saturate: bool = false¶: If true, saturate the result to [0 ; 255] using vpMath::saturate , otherwise overflow may occur.

static inMask(*args, **kwargs)¶

Overloaded function.

inMask(I: visp._visp.core.ImageGray, mask: visp._visp.core.ImageGray, I_mask: visp._visp.core.ImageGray) -> int

Parameters:

I: Input image.
mask: Mask where pixels to consider have values that differ from 0.
I_mask: Resulting image where pixels that are in the mask are kept.

Returns:

The number of pixels that are in the mask.

inMask(I: visp._visp.core.ImageRGBa, mask: visp._visp.core.ImageGray, I_mask: visp._visp.core.ImageRGBa) -> int

Parameters:

I: Input image.
mask: Mask where pixels to consider have values that differ from 0.
I_mask: Resulting image where pixels that are in the mask are kept.

Returns:

The number of pixels that are in the mask.

static initUndistortMap(cam: visp._visp.core.CameraParameters, width: int, height: int, mapU: vpArray2D<int>, mapV: vpArray2D<int>, mapDu: vpArray2D<float>, mapDv: vpArray2D<float>) → None¶

Compute the undistortion transformation map.

Parameters:

cam: Camera intrinsic parameters with distortion coefficients.
width: Image width.
height: Image height.
mapU: 2D array that contains at each coordinate the u-coordinate in the distorted image.
mapV: 2D array that contains at each coordinate the v-coordinate in the distorted image.
mapDu: 2D array that contains at each coordinate the \(\Delta u\) for the interpolation.
mapDv: 2D array that contains at each coordinate the \(\Delta v\) for the interpolation.

static integralImage(I: visp.core.ImageGray, II: visp.core.ImageDouble, IIsq: visp.core.ImageDouble) → None¶

Compute the integral images:

\(II(u,v)=\sum_{u^{'}\leq u, v^{'}\leq v}I(u,v)\)

\(IIsq(u,v)=\sum_{u^{'}\leq u, v^{'}\leq v}I(u,v)^2\) .

Parameters:

I: visp.core.ImageGray¶: Input image.
II: visp.core.ImageDouble¶: Integral image II.
IIsq: visp.core.ImageDouble¶: Integral image IIsq.

static interpolate(I: visp.core.ImageGray, point: visp.core.ImagePoint, method: visp.core.ImageTools.ImageInterpolationType = INTERPOLATION_NEAREST) → float¶

static normalize(I: visp.core.ImageDouble) → None¶

Normalize the image intensities.

Parameters:

I: visp.core.ImageDouble¶: The image to normalize.

static normalizedCorrelation(I1: visp.core.ImageDouble, I2: visp.core.ImageDouble, useOptimized: bool = true) → float¶

Compute a correlation between 2 images.

Parameters:

I1: visp.core.ImageDouble¶: The first image.
I2: visp.core.ImageDouble¶: The second image.
useOptimized: bool = true¶: Use SSE if true and available.

static remap(*args, **kwargs)¶

Overloaded function.

remap(I: visp._visp.core.ImageGray, mapU: vpArray2D<int>, mapV: vpArray2D<int>, mapDu: vpArray2D<float>, mapDv: vpArray2D<float>, Iundist: visp._visp.core.ImageGray) -> None

Apply the transformation map to the image.

Parameters:

I: Input grayscale image.
mapU: Map that contains at each destination coordinate the u-coordinate in the source image.
mapV: Map that contains at each destination coordinate the v-coordinate in the source image.
mapDu: Map that contains at each destination coordinate the \(\Delta u\) for the interpolation.
mapDv: Map that contains at each destination coordinate the \(\Delta v\) for the interpolation.
Iundist: Output transformed grayscale image.

remap(I: visp._visp.core.ImageRGBa, mapU: vpArray2D<int>, mapV: vpArray2D<int>, mapDu: vpArray2D<float>, mapDv: vpArray2D<float>, Iundist: visp._visp.core.ImageRGBa) -> None

Apply the transformation map to the image.

Parameters:

I: Input color image.
mapU: Map that contains at each destination coordinate the u-coordinate in the source image.
mapV: Map that contains at each destination coordinate the v-coordinate in the source image.
mapDu: Map that contains at each destination coordinate the \(\Delta u\) for the interpolation.
mapDv: Map that contains at each destination coordinate the \(\Delta v\) for the interpolation.
Iundist: Output transformed color image.

static resize(*args, **kwargs)¶

Overloaded function.

resize(I: visp._visp.core.ImageGray, Ires: visp._visp.core.ImageGray, width: int, height: int, method: visp._visp.core.ImageTools.ImageInterpolationType = INTERPOLATION_NEAREST, nThreads: int = 0) -> None
resize(I: visp._visp.core.ImageUInt16, Ires: visp._visp.core.ImageUInt16, width: int, height: int, method: visp._visp.core.ImageTools.ImageInterpolationType = INTERPOLATION_NEAREST, nThreads: int = 0) -> None
resize(I: visp._visp.core.ImageFloat, Ires: visp._visp.core.ImageFloat, width: int, height: int, method: visp._visp.core.ImageTools.ImageInterpolationType = INTERPOLATION_NEAREST, nThreads: int = 0) -> None
resize(I: visp._visp.core.ImageGray, Ires: visp._visp.core.ImageGray, method: visp._visp.core.ImageTools.ImageInterpolationType = INTERPOLATION_NEAREST, nThreads: int = 0) -> None
resize(I: visp._visp.core.ImageUInt16, Ires: visp._visp.core.ImageUInt16, method: visp._visp.core.ImageTools.ImageInterpolationType = INTERPOLATION_NEAREST, nThreads: int = 0) -> None
resize(I: visp._visp.core.ImageFloat, Ires: visp._visp.core.ImageFloat, method: visp._visp.core.ImageTools.ImageInterpolationType = INTERPOLATION_NEAREST, nThreads: int = 0) -> None

static templateMatching(I: visp.core.ImageGray, I_tpl: visp.core.ImageGray, I_score: visp.core.ImageDouble, step_u: int, step_v: int, useOptimized: bool = true) → None¶

Match a template image into another image using zero-mean normalized cross-correlation:

\(\frac{\sum_{u^{'},v^{'}} (I(u+u^{'},v+v^{'})-\bar{I}_{u^{'},v^{'}}) (T(u^{'},v^{'})-\bar{T}_{u^{'},v^{'}})}{\sqrt{\sum_{u^{'},v^{'}} (I(u+u^{'},v+v^{'})-\bar{I}_{u^{'},v^{'}})^2 \sum_{u^{'},v^{'}}(T(u^{'},v^{'})-\bar{T}_{u^{'},v^{'}})^2}}\)

Parameters:

I: visp.core.ImageGray¶: Input image.
I_tpl: visp.core.ImageGray¶: Template image.
I_score: visp.core.ImageDouble¶: Output template matching score.
step_u: int¶: Step in u-direction to speed-up the computation.
step_v: int¶: Step in v-direction to speed-up the computation.
useOptimized: bool = true¶: Use optimized version (SSE, OpenMP, integral images, …) if true and available.

static undistort(*args, **kwargs)¶

Overloaded function.

undistort(I: visp._visp.core.ImageGray, cam: visp._visp.core.CameraParameters, newI: visp._visp.core.ImageGray, nThreads: int = 2) -> None

Undistort an image

Warning

This function works only with Types authorizing “+,-, multiplication by a scalar” operators.

Since this function is time consuming, if you want to undistort multiple images, you should rather call initUndistortMap() once and then remap() to undistort the images. This will be less time consuming.

Note

See initUndistortMap() , remap()

Parameters:

I: Input image to undistort.
cam: Parameters of the camera causing distortion.
nThreads: Number of threads to use if pthreads library is available.

undistort(I: visp._visp.core.ImageRGBa, cam: visp._visp.core.CameraParameters, newI: visp._visp.core.ImageRGBa, nThreads: int = 2) -> None

Undistort an image

Warning

This function works only with Types authorizing “+,-, multiplication by a scalar” operators.

Note

See initUndistortMap() , remap()

Parameters:

I: Input image to undistort.
cam: Parameters of the camera causing distortion.
nThreads: Number of threads to use if pthreads library is available.

undistort(I: visp._visp.core.ImageGray, mapU: vpArray2D<int>, mapV: vpArray2D<int>, mapDu: vpArray2D<float>, mapDv: vpArray2D<float>, newI: visp._visp.core.ImageGray) -> None

Undistort an image.

Note

To undistort a fisheye image, you have to first call initUndistortMap() function to calculate maps and then call undistort() with input maps.

Parameters:

I: Input image to undistort.
mapU: Map that contains at each destination coordinate the u-coordinate in the source image.
mapV: Map that contains at each destination coordinate the v-coordinate in the source image.
mapDu: Map that contains at each destination coordinate the \(\Delta u\) for the interpolation.
mapDv: Map that contains at each destination coordinate the \(\Delta v\) for the interpolation.
newI: Undistorted output image. The size of this image will be the same as the input image I .

undistort(I: visp._visp.core.ImageRGBa, mapU: vpArray2D<int>, mapV: vpArray2D<int>, mapDu: vpArray2D<float>, mapDv: vpArray2D<float>, newI: visp._visp.core.ImageRGBa) -> None

Undistort an image.

Note

To undistort a fisheye image, you have to first call initUndistortMap() function to calculate maps and then call undistort() with input maps.

Parameters:

I: Input image to undistort.
mapU: Map that contains at each destination coordinate the u-coordinate in the source image.
mapV: Map that contains at each destination coordinate the v-coordinate in the source image.
mapDu: Map that contains at each destination coordinate the \(\Delta u\) for the interpolation.
mapDv: Map that contains at each destination coordinate the \(\Delta v\) for the interpolation.
newI: Undistorted output image. The size of this image will be the same as the input image I .

static warpImage(*args, **kwargs)¶

Overloaded function.

warpImage(src: visp._visp.core.ImageGray, T: visp._visp.core.Matrix, dst: visp._visp.core.ImageGray, interpolation: visp._visp.core.ImageTools.ImageInterpolationType = INTERPOLATION_NEAREST, fixedPointArithmetic: bool = true, pixelCenter: bool = false) -> None
warpImage(src: visp._visp.core.ImageFloat, T: visp._visp.core.Matrix, dst: visp._visp.core.ImageFloat, interpolation: visp._visp.core.ImageTools.ImageInterpolationType = INTERPOLATION_NEAREST, fixedPointArithmetic: bool = true, pixelCenter: bool = false) -> None
warpImage(src: visp._visp.core.ImageDouble, T: visp._visp.core.Matrix, dst: visp._visp.core.ImageDouble, interpolation: visp._visp.core.ImageTools.ImageInterpolationType = INTERPOLATION_NEAREST, fixedPointArithmetic: bool = true, pixelCenter: bool = false) -> None
warpImage(src: visp._visp.core.ImageRGBa, T: visp._visp.core.Matrix, dst: visp._visp.core.ImageRGBa, interpolation: visp._visp.core.ImageTools.ImageInterpolationType = INTERPOLATION_NEAREST, fixedPointArithmetic: bool = true, pixelCenter: bool = false) -> None