lensfunpy 1.15.0

How to find cameras and lenses

import lensfunpy

cam_maker = 'NIKON CORPORATION'
cam_model = 'NIKON D3S'
lens_maker = 'Nikon'
lens_model = 'Nikkor 28mm f/2.8D AF'

db = lensfunpy.Database()
cam = db.find_cameras(cam_maker, cam_model)[0]
lens = db.find_lenses(cam, lens_maker, lens_model)[0]

print(cam)
# Camera(Maker: NIKON CORPORATION; Model: NIKON D3S; Variant: ;
#        Mount: Nikon F AF; Crop Factor: 1.0; Score: 0)

print(lens)
# Lens(Maker: Nikon; Model: Nikkor 28mm f/2.8D AF; Type: RECTILINEAR;
#      Focal: 28.0-28.0; Aperture: 2.79999995232-2.79999995232;
#      Crop factor: 1.0; Score: 110)

How to correct lens distortion

import cv2 # OpenCV library

focal_length = 28.0
aperture = 1.4
distance = 10
image_path = '/path/to/image.tiff'
undistorted_image_path = '/path/to/image_undist.tiff'

img = cv2.imread(image_path)
height, width = img.shape[0], img.shape[1]

mod = lensfunpy.Modifier(lens, cam.crop_factor, width, height)
mod.initialize(focal_length, aperture, distance, pixel_format=img.dtype)

undist_coords = mod.apply_geometry_distortion()
img_undistorted = cv2.remap(img, undist_coords, None, cv2.INTER_LANCZOS4)
cv2.imwrite(undistorted_image_path, img_undistorted)

It is also possible to apply the correction via SciPy instead of OpenCV. The lensfunpy.util module contains convenience functions for RGB images which handle both OpenCV and SciPy.

How to correct lens vignetting

Note that the assumption is that the image is in a linear state, i.e., it is not gamma corrected.

import lensfunpy
import imageio

db = lensfun.Database()
cam = db.find_cameras('NIKON CORPORATION', 'NIKON D3S')[0]
lens = db.find_lenses(cam, 'Nikon', 'Nikkor AF 20mm f/2.8D')[0]

# The image is assumed to be in a linearly state.
img = imageio.imread('/path/to/image.tiff')

focal_length = 20
aperture = 4
distance = 10
width = img.shape[1]
height = img.shape[0]

mod = lensfunpy.Modifier(lens, cam.crop_factor, width, height)
mod.initialize(focal_length, aperture, distance, pixel_format=img.dtype)

did_apply = mod.apply_color_modification(img)
if did_apply:
    imageio.imwrite('/path/to/image_corrected.tiff', img)
else:
    print('vignetting not corrected, calibration data missing?')

How to correct lens vignetting and TCA

Note that the assumption is that the image is in a linear state, i.e., it is not gamma corrected. Vignetting should always be corrected first before applying the TCA correction.

import imageio
import cv2
import lensfunpy

db = lensfunpy.Database()
cam = db.find_cameras('Canon', 'Canon EOS 5D Mark IV')[0]
lens = db.find_lenses(cam, 'Sigma', 'Sigma 8mm f/3.5 EX DG circular fisheye')[0]

# The image is assumed to be in a linearly state.
img = imageio.imread('/path/to/image.tiff')

focal_length = 8.0
aperture = 11
distance = 10
width = img.shape[1]
height = img.shape[0]

mod = lensfunpy.Modifier(lens, cam.crop_factor, width, height)
mod.initialize(focal_length, aperture, distance, pixel_format=img.dtype, flags=lensfunpy.ModifyFlags.VIGNETTING | lensfunpy.ModifyFlags.TCA)

# Vignette Correction
mod.apply_color_modification(img)

# TCA Correction
undist_coords = mod.apply_subpixel_distortion()
img[..., 0] = cv2.remap(img[..., 0], undist_coords[..., 0, :], None, cv2.INTER_LANCZOS4)
img[..., 1] = cv2.remap(img[..., 1], undist_coords[..., 1, :], None, cv2.INTER_LANCZOS4)
img[..., 2] = cv2.remap(img[..., 2], undist_coords[..., 2, :], None, cv2.INTER_LANCZOS4)

imageio.imwrite('/path/to/image_corrected.tiff', img)