View Source Evision.Stitcher (Evision v0.1.15)
Link to this section Summary
Types
Type that represents an Evision.Stitcher
struct.
Functions
These functions try to compose the given images (or images stored internally from the other function calls) into the final pano under the assumption that the image transformations were estimated before.
These functions try to compose the given images (or images stored internally from the other function calls) into the final pano under the assumption that the image transformations were estimated before.
Return
- retval:
double
Python prototype (for reference):
Creates a Stitcher configured in one of the stitching modes.
Creates a Stitcher configured in one of the stitching modes.
These functions try to match the given images and to estimate rotations of each camera.
These functions try to match the given images and to estimate rotations of each camera.
Return
- retval:
InterpolationFlags
Python prototype (for reference):
Return
- retval:
double
Python prototype (for reference):
Return
- retval:
double
Python prototype (for reference):
Return
- retval:
double
Python prototype (for reference):
Positional Arguments
- resol_mpx:
double
Python prototype (for reference):
Positional Arguments
- interp_flags:
InterpolationFlags
Python prototype (for reference):
Positional Arguments
- conf_thresh:
double
Python prototype (for reference):
Positional Arguments
- resol_mpx:
double
Python prototype (for reference):
Positional Arguments
- resol_mpx:
double
Python prototype (for reference):
Positional Arguments
- flag:
bool
Python prototype (for reference):
Positional Arguments
- images:
[Evision.Mat]
Return
- retval:
Status
- pano:
Evision.Mat
.
Has overloading in C++
Variant 1:
These functions try to stitch the given images.
These functions try to stitch the given images.
Return
- retval:
bool
Python prototype (for reference):
Return
- retval:
double
Python prototype (for reference):
Link to this section Types
@type t() :: %Evision.Stitcher{ref: reference()}
Type that represents an Evision.Stitcher
struct.
ref.
reference()
The underlying erlang resource variable.
Link to this section Functions
@spec composePanorama(t()) :: {integer(), Evision.Mat.t()} | {:error, String.t()}
Return
- retval:
Status
- pano:
Evision.Mat
.
Has overloading in C++
Python prototype (for reference):
composePanorama([, pano]) -> retval, pano
@spec composePanorama(t(), [Evision.Mat.maybe_mat_in()]) :: {integer(), Evision.Mat.t()} | {:error, String.t()}
These functions try to compose the given images (or images stored internally from the other function calls) into the final pano under the assumption that the image transformations were estimated before.
Positional Arguments
images:
[Evision.Mat]
.Input images.
Return
retval:
Status
pano:
Evision.Mat
.Final pano.
Note: Use the functions only if you're aware of the stitching pipeline, otherwise use Stitcher::stitch. @return Status code.
Python prototype (for reference):
composePanorama(images[, pano]) -> retval, pano
@spec composePanorama( t(), [Evision.Mat.maybe_mat_in()], [{atom(), term()}, ...] | nil ) :: {integer(), Evision.Mat.t()} | {:error, String.t()}
These functions try to compose the given images (or images stored internally from the other function calls) into the final pano under the assumption that the image transformations were estimated before.
Positional Arguments
images:
[Evision.Mat]
.Input images.
Return
retval:
Status
pano:
Evision.Mat
.Final pano.
Note: Use the functions only if you're aware of the stitching pipeline, otherwise use Stitcher::stitch. @return Status code.
Python prototype (for reference):
composePanorama(images[, pano]) -> retval, pano
Return
- retval:
double
Python prototype (for reference):
compositingResol() -> retval
Creates a Stitcher configured in one of the stitching modes.
Keyword Arguments
mode:
Mode
.Scenario for stitcher operation. This is usually determined by source of images to stitch and their transformation. Default parameters will be chosen for operation in given scenario.
Return
- retval:
Evision.Stitcher
@return Stitcher class instance.
Python prototype (for reference):
create([, mode]) -> retval
Creates a Stitcher configured in one of the stitching modes.
Keyword Arguments
mode:
Mode
.Scenario for stitcher operation. This is usually determined by source of images to stitch and their transformation. Default parameters will be chosen for operation in given scenario.
Return
- retval:
Evision.Stitcher
@return Stitcher class instance.
Python prototype (for reference):
create([, mode]) -> retval
@spec estimateTransform(t(), [Evision.Mat.maybe_mat_in()]) :: integer() | {:error, String.t()}
These functions try to match the given images and to estimate rotations of each camera.
Positional Arguments
images:
[Evision.Mat]
.Input images.
Keyword Arguments
masks:
[Evision.Mat]
.Masks for each input image specifying where to look for keypoints (optional).
Return
- retval:
Status
Note: Use the functions only if you're aware of the stitching pipeline, otherwise use Stitcher::stitch. @return Status code.
Python prototype (for reference):
estimateTransform(images[, masks]) -> retval
@spec estimateTransform( t(), [Evision.Mat.maybe_mat_in()], [{atom(), term()}, ...] | nil ) :: integer() | {:error, String.t()}
These functions try to match the given images and to estimate rotations of each camera.
Positional Arguments
images:
[Evision.Mat]
.Input images.
Keyword Arguments
masks:
[Evision.Mat]
.Masks for each input image specifying where to look for keypoints (optional).
Return
- retval:
Status
Note: Use the functions only if you're aware of the stitching pipeline, otherwise use Stitcher::stitch. @return Status code.
Python prototype (for reference):
estimateTransform(images[, masks]) -> retval
Return
- retval:
InterpolationFlags
Python prototype (for reference):
interpolationFlags() -> retval
Return
- retval:
double
Python prototype (for reference):
panoConfidenceThresh() -> retval
Return
- retval:
double
Python prototype (for reference):
registrationResol() -> retval
Return
- retval:
double
Python prototype (for reference):
seamEstimationResol() -> retval
Positional Arguments
- resol_mpx:
double
Python prototype (for reference):
setCompositingResol(resol_mpx) -> None
Positional Arguments
- interp_flags:
InterpolationFlags
Python prototype (for reference):
setInterpolationFlags(interp_flags) -> None
Positional Arguments
- conf_thresh:
double
Python prototype (for reference):
setPanoConfidenceThresh(conf_thresh) -> None
Positional Arguments
- resol_mpx:
double
Python prototype (for reference):
setRegistrationResol(resol_mpx) -> None
Positional Arguments
- resol_mpx:
double
Python prototype (for reference):
setSeamEstimationResol(resol_mpx) -> None
Positional Arguments
- flag:
bool
Python prototype (for reference):
setWaveCorrection(flag) -> None
@spec stitch(t(), [Evision.Mat.maybe_mat_in()]) :: {integer(), Evision.Mat.t()} | {:error, String.t()}
Positional Arguments
- images:
[Evision.Mat]
Return
- retval:
Status
- pano:
Evision.Mat
.
Has overloading in C++
Python prototype (for reference):
stitch(images[, pano]) -> retval, pano
@spec stitch(t(), [Evision.Mat.maybe_mat_in()], [{atom(), term()}, ...] | nil) :: {integer(), Evision.Mat.t()} | {:error, String.t()}
@spec stitch(t(), [Evision.Mat.maybe_mat_in()], [Evision.Mat.maybe_mat_in()]) :: {integer(), Evision.Mat.t()} | {:error, String.t()}
Variant 1:
These functions try to stitch the given images.
Positional Arguments
images:
[Evision.Mat]
.Input images.
masks:
[Evision.Mat]
.Masks for each input image specifying where to look for keypoints (optional).
Return
retval:
Status
pano:
Evision.Mat
.Final pano.
@return Status code.
Python prototype (for reference):
stitch(images, masks[, pano]) -> retval, pano
Variant 2:
Positional Arguments
- images:
[Evision.Mat]
Return
- retval:
Status
- pano:
Evision.Mat
.
Has overloading in C++
Python prototype (for reference):
stitch(images[, pano]) -> retval, pano
@spec stitch( t(), [Evision.Mat.maybe_mat_in()], [Evision.Mat.maybe_mat_in()], [{atom(), term()}, ...] | nil ) :: {integer(), Evision.Mat.t()} | {:error, String.t()}
These functions try to stitch the given images.
Positional Arguments
images:
[Evision.Mat]
.Input images.
masks:
[Evision.Mat]
.Masks for each input image specifying where to look for keypoints (optional).
Return
retval:
Status
pano:
Evision.Mat
.Final pano.
@return Status code.
Python prototype (for reference):
stitch(images, masks[, pano]) -> retval, pano
Return
- retval:
bool
Python prototype (for reference):
waveCorrection() -> retval
Return
- retval:
double
Python prototype (for reference):
workScale() -> retval