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https://github.com/letmaik/lensfunpy

📷 Lens distortion correction for Python, a wrapper for lensfun
https://github.com/letmaik/lensfunpy

camera-image distortion-correction image-processing lens python

Last synced: 13 days ago
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📷 Lens distortion correction for Python, a wrapper for lensfun

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README 

        
lensfunpy

=========



lensfunpy is an easy-to-use Python wrapper for the lensfun_ library.



`API Documentation `_



Sample code

-----------



How to find cameras and lenses

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~



.. code-block:: python



    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

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~



.. code-block:: python



    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.



.. code-block:: python



    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.



.. code-block:: python



    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)



Installation

------------



Install lensfunpy by running:



.. code-block:: sh



    pip install lensfunpy



64-bit binary wheels are provided for Linux, macOS, and Windows.



Installation from source on Linux/macOS

---------------------------------------



If you have the need to use a specific lensfun version or you can't use the provided binary wheels

then follow the steps in this section to build lensfunpy from source.



First, install the lensfun_ library on your system.



On Ubuntu, you can get (an outdated) version with:



.. code-block:: sh



    sudo apt-get install liblensfun-dev

    

Or install the latest developer version from the Git repository:



.. code-block:: sh



    git clone https://github.com/lensfun/lensfun

    cd lensfun

    cmake .

    sudo make install

    

After that, install lensfunpy using:



.. code-block:: sh



    git clone https://github.com/letmaik/lensfunpy

    cd lensfunpy

    pip install numpy cython

    pip install .

    

On Linux, if you get the error "ImportError: liblensfun.so.0: cannot open shared object file: No such file or directory"

when trying to use lensfunpy, then do the following:



.. code-block:: sh



    echo "/usr/local/lib" | sudo tee /etc/ld.so.conf.d/99local.conf

    sudo ldconfig



The lensfun library is installed in ``/usr/local/lib`` when compiled from source, and apparently this folder is not searched

for libraries by default in some Linux distributions.

Note that on some systems the installation path may be slightly different, such as ``/usr/local/lib/x86_64-linux-gnu``

or ``/usr/local/lib64``.



Installation from source on Windows

-----------------------------------



These instructions are experimental and support is not provided for them.

Typically, there should be no need to build manually since wheels are hosted on PyPI.



You need to have Visual Studio installed to build lensfunpy.



In a PowerShell window:



.. code-block:: sh



    $env:USE_CONDA = '1'

    $env:PYTHON_VERSION = '3.10'

    $env:PYTHON_ARCH = 'x86_64'

    $env:NUMPY_VERSION = '2.0.*'

    git clone https://github.com/letmaik/lensfunpy

    cd lensfunpy

    .github/scripts/build-windows.ps1



The above will download all build dependencies (including a Python installation)

and is fully configured through the four environment variables.

Set ``USE_CONDA = '0'`` to build within an existing Python environment.



.. _lensfun: https://lensfun.github.io/