lensfunpy
=========
lensfunpy is an easy-to-use Python wrapper for the lensfun_ library.
`API Documentation <https://letmaik.github.io/lensfunpy/api/>`_
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 <http://www.scipy.org>`_ instead of OpenCV.
The `lensfunpy.util <https://letmaik.github.io/lensfunpy/api/lensfunpy.util.html>`_ 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 = '3.7'
$env:PYTHON_ARCH = 'x86_64'
$env:NUMPY_VERSION = '1.14.*'
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/
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"description": "lensfunpy\n=========\n\nlensfunpy is an easy-to-use Python wrapper for the lensfun_ library.\n\n`API Documentation <https://letmaik.github.io/lensfunpy/api/>`_\n\nSample code\n-----------\n\nHow to find cameras and lenses\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n.. code-block:: python\n\n import lensfunpy\n\n cam_maker = 'NIKON CORPORATION'\n cam_model = 'NIKON D3S'\n lens_maker = 'Nikon'\n lens_model = 'Nikkor 28mm f/2.8D AF'\n\n db = lensfunpy.Database()\n cam = db.find_cameras(cam_maker, cam_model)[0]\n lens = db.find_lenses(cam, lens_maker, lens_model)[0]\n\n print(cam)\n # Camera(Maker: NIKON CORPORATION; Model: NIKON D3S; Variant: ; \n # Mount: Nikon F AF; Crop Factor: 1.0; Score: 0)\n\n print(lens)\n # Lens(Maker: Nikon; Model: Nikkor 28mm f/2.8D AF; Type: RECTILINEAR;\n # Focal: 28.0-28.0; Aperture: 2.79999995232-2.79999995232; \n # Crop factor: 1.0; Score: 110)\n\nHow to correct lens distortion\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n.. code-block:: python\n\n import cv2 # OpenCV library\n\n focal_length = 28.0\n aperture = 1.4\n distance = 10\n image_path = '/path/to/image.tiff'\n undistorted_image_path = '/path/to/image_undist.tiff'\n\n img = cv2.imread(image_path)\n height, width = img.shape[0], img.shape[1]\n\n mod = lensfunpy.Modifier(lens, cam.crop_factor, width, height)\n mod.initialize(focal_length, aperture, distance, pixel_format=img.dtype)\n\n undist_coords = mod.apply_geometry_distortion()\n img_undistorted = cv2.remap(img, undist_coords, None, cv2.INTER_LANCZOS4)\n cv2.imwrite(undistorted_image_path, img_undistorted)\n\nIt is also possible to apply the correction via `SciPy <http://www.scipy.org>`_ instead of OpenCV.\nThe `lensfunpy.util <https://letmaik.github.io/lensfunpy/api/lensfunpy.util.html>`_ module\ncontains convenience functions for RGB images which handle both OpenCV and SciPy.\n\nHow to correct lens vignetting\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nNote that the assumption is that the image is in a linear state, i.e., it is not\ngamma corrected.\n\n.. code-block:: python\n\n import lensfunpy\n import imageio\n\n db = lensfun.Database()\n cam = db.find_cameras('NIKON CORPORATION', 'NIKON D3S')[0]\n lens = db.find_lenses(cam, 'Nikon', 'Nikkor AF 20mm f/2.8D')[0]\n\n # The image is assumed to be in a linearly state.\n img = imageio.imread('/path/to/image.tiff')\n\n focal_length = 20\n aperture = 4\n distance = 10\n width = img.shape[1]\n height = img.shape[0]\n\n mod = lensfunpy.Modifier(lens, cam.crop_factor, width, height)\n mod.initialize(focal_length, aperture, distance, pixel_format=img.dtype)\n\n did_apply = mod.apply_color_modification(img)\n if did_apply:\n imageio.imwrite('/path/to/image_corrected.tiff', img)\n else:\n print('vignetting not corrected, calibration data missing?')\n\n\nHow to correct lens vignetting and TCA\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nNote that the assumption is that the image is in a linear state, i.e., it is not\ngamma corrected. Vignetting should always be corrected first before applying the\nTCA correction.\n\n.. code-block:: python\n\n import imageio\n import cv2\n import lensfunpy\n\n db = lensfunpy.Database()\n cam = db.find_cameras('Canon', 'Canon EOS 5D Mark IV')[0]\n lens = db.find_lenses(cam, 'Sigma', 'Sigma 8mm f/3.5 EX DG circular fisheye')[0]\n\n # The image is assumed to be in a linearly state.\n img = imageio.imread('/path/to/image.tiff')\n\n focal_length = 8.0\n aperture = 11\n distance = 10\n width = img.shape[1]\n height = img.shape[0]\n\n mod = lensfunpy.Modifier(lens, cam.crop_factor, width, height)\n mod.initialize(focal_length, aperture, distance, pixel_format=img.dtype, flags=lensfunpy.ModifyFlags.VIGNETTING | lensfunpy.ModifyFlags.TCA)\n\n # Vignette Correction\n mod.apply_color_modification(img)\n\n # TCA Correction\n undist_coords = mod.apply_subpixel_distortion()\n img[..., 0] = cv2.remap(img[..., 0], undist_coords[..., 0, :], None, cv2.INTER_LANCZOS4)\n img[..., 1] = cv2.remap(img[..., 1], undist_coords[..., 1, :], None, cv2.INTER_LANCZOS4)\n img[..., 2] = cv2.remap(img[..., 2], undist_coords[..., 2, :], None, cv2.INTER_LANCZOS4)\n\n imageio.imwrite('/path/to/image_corrected.tiff', img)\n\nInstallation\n------------\n\nInstall lensfunpy by running:\n\n.. code-block:: sh\n\n pip install lensfunpy\n\n64-bit binary wheels are provided for Linux, macOS, and Windows.\n\nInstallation from source on Linux/macOS\n---------------------------------------\n\nIf you have the need to use a specific lensfun version or you can't use the provided binary wheels\nthen follow the steps in this section to build lensfunpy from source.\n\nFirst, install the lensfun_ library on your system.\n\nOn Ubuntu, you can get (an outdated) version with:\n\n.. code-block:: sh\n\n sudo apt-get install liblensfun-dev\n \nOr install the latest developer version from the Git repository:\n\n.. code-block:: sh\n\n git clone https://github.com/lensfun/lensfun\n cd lensfun\n cmake .\n sudo make install\n \nAfter that, install lensfunpy using:\n\n.. code-block:: sh\n\n git clone https://github.com/letmaik/lensfunpy\n cd lensfunpy\n pip install numpy cython\n pip install .\n \nOn Linux, if you get the error \"ImportError: liblensfun.so.0: cannot open shared object file: No such file or directory\"\nwhen trying to use lensfunpy, then do the following:\n\n.. code-block:: sh\n\n echo \"/usr/local/lib\" | sudo tee /etc/ld.so.conf.d/99local.conf\n sudo ldconfig\n\nThe lensfun library is installed in ``/usr/local/lib`` when compiled from source, and apparently this folder is not searched\nfor libraries by default in some Linux distributions.\nNote that on some systems the installation path may be slightly different, such as ``/usr/local/lib/x86_64-linux-gnu``\nor ``/usr/local/lib64``.\n\nInstallation from source on Windows\n-----------------------------------\n\nThese instructions are experimental and support is not provided for them.\nTypically, there should be no need to build manually since wheels are hosted on PyPI.\n\nYou need to have Visual Studio installed to build lensfunpy.\n\nIn a PowerShell window:\n\n.. code-block:: sh\n\n $env:USE_CONDA = '1'\n $env:PYTHON_VERSION = '3.7'\n $env:PYTHON_ARCH = 'x86_64'\n $env:NUMPY_VERSION = '1.14.*'\n git clone https://github.com/letmaik/lensfunpy\n cd lensfunpy\n .github/scripts/build-windows.ps1\n\nThe above will download all build dependencies (including a Python installation)\nand is fully configured through the four environment variables.\nSet ``USE_CONDA = '0'`` to build within an existing Python environment.\n\n\n.. _lensfun: https://lensfun.github.io/\n",
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