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Alexander Smorkalov
2026-02-19 17:10:14 +03:00
parent a9da03f6c8 a269a489b9
commit 6c995c768f
120 changed files with 650 additions and 465 deletions
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doc/tutorials/calib3d/camera_calibration/camera_calibration.markdown
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@@ -12,9 +12,9 @@ Camera calibration With OpenCV {#tutorial_camera_calibration}
| Compatibility | OpenCV >= 4.0 |
Cameras have been around for a long-long time. However, with the introduction of the cheap *pinhole*
Cameras have been around for a very long time. However, with the introduction of the cheap *pinhole*
cameras in the late 20th century, they became a common occurrence in our everyday life.
Unfortunately, this cheapness comes with its price: significant distortion. Luckily, these are
Unfortunately, this low cost comes with a trade-off: significant distortion. Luckily, these are
constants and with a calibration and some remapping we can correct this. Furthermore, with
calibration you may also determine the relation between the camera's natural units (pixels) and the
real world units (for example millimeters).
@@ -22,8 +22,10 @@ real world units (for example millimeters).
Theory
------
For the distortion OpenCV takes into account the radial and tangential factors. For the radial
factor one uses the following formula:
For distortion, OpenCV takes into account both radial and tangential factors. For the radial
factor one uses the following formulas:
\f[r^2 = x^2 + y^2\f]
\f[x_{distorted} = x( 1 + k_1 r^2 + k_2 r^4 + k_3 r^6) \\
y_{distorted} = y( 1 + k_1 r^2 + k_2 r^4 + k_3 r^6)\f]
@@ -64,10 +66,10 @@ objects. Currently OpenCV supports three types of objects for calibration:
- Symmetrical circle pattern
- Asymmetrical circle pattern
Basically, you need to take snapshots of these patterns with your camera and let OpenCV find them.
In practice, you need to capture multiple images of these patterns using your camera and let OpenCV find them.
Each found pattern results in a new equation. To solve the equation you need at least a
predetermined number of pattern snapshots to form a well-posed equation system. This number is
higher for the chessboard pattern and less for the circle ones. For example, in theory the
higher for the chessboard pattern and lower for circle-based patterns.For example, in theory the
chessboard pattern requires at least two snapshots. However, in practice we have a good amount of
noise present in our input images, so for good results you will probably need at least 10 good
snapshots of the input pattern in different positions.
@@ -148,8 +150,8 @@ Explanation
is defined in squares, but detection result is list of inner corners and that's why is smaller
by 1 in both dimensions.
Then again in case of cameras we only take camera images when an input delay time is passed.
This is done in order to allow user moving the chessboard around and getting different images.
In the case of live cameras, we only capture images when an input delay time is passed.
This is done to allow the user to move the chessboard around and getting different images.
Similar images result in similar equations, and similar equations at the calibration step will
form an ill-posed problem, so the calibration will fail. For square images the positions of the
corners are only approximate. We may improve this by calling the @ref cv::cornerSubPix function.
@@ -160,6 +162,7 @@ Explanation
visualization feedback purposes we will draw the found points on the input image using @ref
cv::findChessboardCorners function.
@snippet samples/cpp/tutorial_code/calib3d/camera_calibration/camera_calibration.cpp pattern_found
-# **Show state and result to the user, plus command line control of the application**
This part shows text output on the image.
@@ -170,6 +173,7 @@ Explanation
Then we show the image and wait for an input key and if this is *u* we toggle the distortion removal,
if it is *g* we start again the detection process, and finally for the *ESC* key we quit the application:
@snippet samples/cpp/tutorial_code/calib3d/camera_calibration/camera_calibration.cpp await_input
-# **Show the distortion removal for the images too**
When you work with an image list it is not
doc/tutorials/introduction/config_reference/config_reference.markdown
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@@ -317,7 +317,7 @@ Following formats can be read by OpenCV without help of any third-party library:
| [PFM](https://en.wikipedia.org/wiki/Netpbm#File_formats) | `WITH_IMGCODEC_PFM` | _ON_ |
| [GIF](https://en.wikipedia.org/wiki/GIF) | `WITH_IMGCODEC_GIF` | _ON_ |
### PNG, JPEG, TIFF, WEBP, JPEG 2000, EXR, JPEG XL support
### PNG, JPEG, TIFF, WEBP, JPEG 2000, EXR, JPEG XL, AVIF support
| Formats | Library | Option | Default | Force build own |
| --------| ------- | ------ | ------- | --------------- |
@@ -331,13 +331,18 @@ Following formats can be read by OpenCV without help of any third-party library:
|^| [JasPer](https://en.wikipedia.org/wiki/JasPer) | `WITH_JASPER` | _ON_ (see note) | `BUILD_JASPER` |
| [OpenEXR](https://en.wikipedia.org/wiki/OpenEXR) || `WITH_OPENEXR` | _ON_ | `BUILD_OPENEXR` |
| [JPEG XL](https://en.wikipedia.org/wiki/JPEG_XL) || `WITH_JPEGXL` | _ON_ | Not supported. (see note) |
| [AVIF](https://en.wikipedia.org/wiki/AVIF) || `WITH_AVIF` | _ON_ | Not supported. (see note) |
All libraries required to read images in these formats are included into OpenCV and will be built automatically if not found at the configuration stage. Corresponding `BUILD_*` options will force building and using own libraries, they are enabled by default on some platforms, e.g. Windows.
Most library source codes required to read/write images in these formats are bundled into OpenCV and will be built automatically if not found at the configuration stage
(except for some codecs that require external libraries, e.g. JPEG XL and AVIF).
Corresponding BUILD_* options will force building and using the bundled libraries; they are enabled by default on some platforms, e.g. Windows.
@note (All) Only one library for each image format can be enabled(e.g. In order to use JasPer for JPEG 2000 format, OpenJPEG must be disabled).
@note (JPEG 2000) OpenJPEG have higher priority than JasPer which is deprecated.
@note (JPEG XL) OpenCV doesn't contain libjxl source code, so `BUILD_JPEGXL` is not supported.
@note (EXR) OpenCV 5 doesn't contain OpenEXR source code, so `BUILD_OPENEXR` is not supported.
@note (JPEG XL) OpenCV doesn't contain libjxl source code, so `BUILD_JPEGXL` is not supported. Users must provide a system-wide installation of libjxl.
@note (AVIF) OpenCV doesn't contain libavif source code, so `BUILD_AVIF` is not supported. Users must provide a system-wide installation of libavif.
@warning OpenEXR ver 2.2 or earlier cannot be used in combination with C++17 or later. In this case, updating OpenEXR ver 2.3.0 or later is required.