Panotoo...::Image(3)

✨ NAME ✨

Panotools::Script::Line::Image — a panotools input image. yes bestie, you're on the Panotoo...::Image(3) page, welcome 💖

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🦋 SYNOPSIS 🦋

One single input image gets described by one i line. that's the whole entire vibe ✨

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🌸 DESCRIPTION 🌸

okay so basically? it's the same format as an o line, literally, no cap. here's everything an i line can carry:

• w1000 — the width, in pixels 💅
• h500 — the height. heads up though: nona requires the width and height of input images, whereas PTStitcher/mender don't 🙈
• f0 — projection format, and it's giving menu:
  • 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 the image (required, bestie, don't skip it)
• 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 the center of the image:
  • d — horizontal offset
  • e — vertical offset
• g,t — initial lens shear. use this 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 the red channel
• Eb — white balance factor for the 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 the x axis, the y axis, the z axis
• TiS — scaling of field of view in the tilt transformation
• TrX, TrY, TrZ — translation on the x axis, the y axis, the z axis
• Tpy, Tpp — yaw and pitch of the 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 the j,k,l,o options)
  • 2: flatfield vignetting correction (see the 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, because examples are iconic:
    • 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 (which is the default), and 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 the center of the 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. the original image size is used for all image parameters (e.g. field-of-view) — they refer to the original image. the selection can be outside the 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.

like, for real, here's how it looks in the wild:

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 (periodt):

$i->Transform ($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. main character math fr fr:

$coor = $i->To_Cartesian ($pto, [23,45]);
($x, $y, $z) = @{$coor};

Query distance (radius) to photo in pixels:

$pix_radius = $i->Radius ($pto);

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and that's the page bestie, you ate it 💅 this was Panotoo...::Image(3), brought to you by perl v5.42.0 and dated 2025-07-25 — go forth and stitch some panoramas, ily 🎀✨