NAME
Panotools::Script::Line::Image - Panotools input image
SYNOPSIS
A single input image is described by an 'i' line
DESCRIPTION
Basically the same format as an 'o' line.
w1000
h500 nona requires the width and height of input images wheras PTStitcher/mender don't
f0 projection format,
0 - rectilinear (normal lenses)
1 - Panoramic (Scanning cameras like Noblex)
2 - Circular fisheye
3 - full-frame fisheye
4 - PSphere, equirectangular
7 - Mirror (a spherical mirror)
8 - Orthographic fisheye
10 - Stereographic fisheye
21 - Equisolid fisheye
v82 horizontal field of view of image (required)
y0 yaw angle (required)
p43 pitch angle (required)
r0 roll angle (required)
a,b,c lens correction coefficients (optional)
(see http://www.fh-furtwangen.de/~dersch/barrel/barrel.html)
d,e initial lens offset in pixels(defaults d0 e0, optional).
Used to correct for offset from center of image
d - horizontal offset,
e - vertical offset
g,t initial lens shear. Use to remove slight misalignment
of the line scanner relative to the film transport
g - horizontal shear
t - vertical shear
j stack number
Eev exposure of image in EV (exposure values)
Er white balance factor for red channel
Eb white balance factor for blue channel
Ra EMoR response model from the Computer Vision Lab at Columbia University
Rb This models the camera response curve
Rc
Rd
Re
TiX,TiY,TiZ Tilt on x axis, y axis, z axis
TiS Scaling of field of view in the tilt transformation
TrX,TrY,TrZ Translation on x axis, y axis, z axis
Tpy,Tpp yaw and pitch of remapping plane for translation
Te0,Te1,Te2,Te3 Test parameters
Vm vignetting correction mode (default 0):
0: no vignetting correction
1: radial vignetting correction (see j,k,l,o options)
2: flatfield vignetting correction (see p option)
4: proportional correction: i_new = i / corr.
This mode is recommended for use with linear data.
If the input data is gamma corrected, try adding g2.2
to the m line.
default is additive correction: i_new = i + corr
Both radial and flatfield correction can be combined with the
proportional correction by adding 4.
Examples: i1 - radial polynomial correction by addition.
The coefficients j,k,l,o must be specified.
i5 - radial polynomial correction by division.
The coefficients j,k,l,o must be specified.
i6 - flatfield correction by division.
The flatfield image should be specified with the p option
Va,Vb,Vc,Vd vignetting correction coefficients. (defaults: 0,0,0,0)
( 0, 2, 4, 6 order polynomial coefficients):
corr = ( i + j*r^2 + k*r^4 + l*r^6), where r is the distance from the image center
The corrected pixel value is calculated with: i_new = i_old + corr
if additive correction is used (default)
for proportional correction (h5): i_new = i_old / corr;
Vx,Vy radial vignetting correction offset in pixels (defaults q0 w0, optional).
Used to correct for offset from center of image
Vx - horizontal offset
Vy - vertical offset
S100,600,100,800 Selection(l,r,t,b), Only pixels inside the rectangle will be used for conversion.
Original image size is used for all image parameters
(e.g. field-of-view) refer to the original image.
Selection can be outside image dimension.
The selection will be circular for circular fisheye images, and
rectangular for all other projection formats
nName file name of the input image.
i f2 r0 p0 y0 v183 a0 b-0.1 c0 S100,600,100,800 n"photo1.jpg"
i f2 r0 p0 y180 v183 a0 b-0.1 c0 S100,600,100,800 n"photo1.jpg"
Rotate transform the image, angles in degrees:
$i->Transform ($roll, $pitch, $yaw);
Each image attribute (v, a, b, c etc...) can be read like so:
$fov = $i->v;
Note that this will return either the value (56.7) or a reference to another image (=0). If you supply a Panotools::Script object as a parameter then the reference will be resolved and you will always get the value:
$fov = $i->v ($pto);
Get the absolute path to the image file
$i->Path ('/path/to/project.pto');
If a .pto project isn't specified then paths are assumed to be relatve to cwd
For any given coordinate in this image (top left is 0,0), calculate an x,y,z cartesian coordinate, accounting for lens distortion, projection and rotation.
$coor = $i->To_Cartesian ($pto, [23,45]);
($x, $y, $z) = @{$coor};
Query distance (radius) to photo in pixels:
$pix_radius = $i->Radius ($pto);