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https://github.com/opencv/opencv.git
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Merge branch 4.x
This commit is contained in:
Alexander Smorkalov
@@ -0,0 +1,91 @@
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Handling Animated Image Files {#tutorial_animations}
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===========================
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@tableofcontents
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| | |
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| -: | :- |
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| Original author | Suleyman Turkmen (with help of ChatGPT) |
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| Compatibility | OpenCV >= 4.11 |
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Goal
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----
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In this tutorial, you will learn how to:
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- Use `cv::imreadanimation` to load frames from animated image files.
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- Understand the structure and parameters of the `cv::Animation` structure.
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- Display individual frames from an animation.
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- Use `cv::imwriteanimation` to write `cv::Animation` to a file.
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Source Code
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-----------
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@add_toggle_cpp
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- **Downloadable code**: Click
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[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/imgcodecs/animations.cpp)
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- **Code at a glance:**
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@include samples/cpp/tutorial_code/imgcodecs/animations.cpp
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@end_toggle
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@add_toggle_python
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- **Downloadable code**: Click
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[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/imgcodecs/animations.py)
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- **Code at a glance:**
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@include samples/python/tutorial_code/imgcodecs/animations.py
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@end_toggle
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Explanation
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-----------
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## Initializing the Animation Structure
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Initialize a `cv::Animation` structure to hold the frames from the animated image file.
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@add_toggle_cpp
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@snippet cpp/tutorial_code/imgcodecs/animations.cpp init_animation
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@end_toggle
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@add_toggle_python
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@snippet python/tutorial_code/imgcodecs/animations.py init_animation
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@end_toggle
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## Loading Frames
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Use `cv::imreadanimation` to load frames from the specified file. Here, we load all frames from an animated WebP image.
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@add_toggle_cpp
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@snippet cpp/tutorial_code/imgcodecs/animations.cpp read_animation
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@end_toggle
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@add_toggle_python
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@snippet python/tutorial_code/imgcodecs/animations.py read_animation
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@end_toggle
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## Displaying Frames
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Each frame in the `animation.frames` vector can be displayed as a standalone image. This loop iterates through each frame, displaying it in a window with a short delay to simulate the animation.
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@add_toggle_cpp
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@snippet cpp/tutorial_code/imgcodecs/animations.cpp show_animation
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@end_toggle
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@add_toggle_python
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@snippet python/tutorial_code/imgcodecs/animations.py show_animation
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@end_toggle
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## Saving Animation
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@add_toggle_cpp
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@snippet cpp/tutorial_code/imgcodecs/animations.cpp write_animation
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@end_toggle
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@add_toggle_python
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@snippet python/tutorial_code/imgcodecs/animations.py write_animation
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@end_toggle
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## Summary
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The `cv::imreadanimation` and `cv::imwriteanimation` functions make it easy to work with animated image files by loading frames into a `cv::Animation` structure, allowing frame-by-frame processing.
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With these functions, you can load, process, and save frames from animated image files like GIF, AVIF, APNG, and WebP.
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@@ -10,3 +10,4 @@ Application utils (highgui, imgcodecs, videoio modules) {#tutorial_table_of_cont
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- @subpage tutorial_orbbec_uvc
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- @subpage tutorial_intelperc
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- @subpage tutorial_wayland_ubuntu
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- @subpage tutorial_animations
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@@ -83,7 +83,7 @@ Arranging the terms: \f$r = x \cos \theta + y \sin \theta\f$
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### Standard and Probabilistic Hough Line Transform
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OpenCV implements two kind of Hough Line Transforms:
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OpenCV implements three kind of Hough Line Transforms:
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a. **The Standard Hough Transform**
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@@ -97,6 +97,12 @@ b. **The Probabilistic Hough Line Transform**
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of the detected lines \f$(x_{0}, y_{0}, x_{1}, y_{1})\f$
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- In OpenCV it is implemented with the function **HoughLinesP()**
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c. **The Weighted Hough Transform**
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- Uses edge intensity instead binary 0 or 1 values in standard Hough transform.
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- In OpenCV it is implemented with the function **HoughLines()** with use_edgeval=true.
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- See the example in samples/cpp/tutorial_code/ImgTrans/HoughLines_Demo.cpp.
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### What does this program do?
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- Loads an image
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- Applies a *Standard Hough Line Transform* and a *Probabilistic Line Transform*.
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@@ -217,7 +217,7 @@ Following options can be used to produce special builds with instrumentation or
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| `ENABLE_BUILD_HARDENING` | GCC, Clang, MSVC | Enable compiler options which reduce possibility of code exploitation. |
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| `ENABLE_LTO` | GCC, Clang, MSVC | Enable Link Time Optimization (LTO). |
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| `ENABLE_THIN_LTO` | Clang | Enable thin LTO which incorporates intermediate bitcode to binaries allowing consumers optimize their applications later. |
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| `OPENCV_ALGO_HINT_DEFAULT` | Any | Set default OpenCV implementation hint value: `ALGO_HINT_ACCURATE` or `ALGO_HINT_APROX`. Dangerous! The option changes behaviour globally and may affect accuracy of many algorithms. |
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| `OPENCV_ALGO_HINT_DEFAULT` | Any | Set default OpenCV implementation hint value: `ALGO_HINT_ACCURATE` or `ALGO_HINT_APPROX`. Dangerous! The option changes behaviour globally and may affect accuracy of many algorithms. |
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@see [GCC instrumentation](https://gcc.gnu.org/onlinedocs/gcc/Instrumentation-Options.html)
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@see [Build hardening](https://en.wikipedia.org/wiki/Hardening_(computing))
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@@ -310,11 +310,12 @@ Following formats can be read by OpenCV without help of any third-party library:
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| [JPEG2000 with OpenJPEG](https://en.wikipedia.org/wiki/OpenJPEG) | `WITH_OPENJPEG` | _ON_ | `BUILD_OPENJPEG` |
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| [JPEG2000 with JasPer](https://en.wikipedia.org/wiki/JasPer) | `WITH_JASPER` | _ON_ (see note) | `BUILD_JASPER` |
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| [EXR](https://en.wikipedia.org/wiki/OpenEXR) | `WITH_OPENEXR` | _ON_ | `BUILD_OPENEXR` |
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| [JPEG XL](https://en.wikipedia.org/wiki/JPEG_XL) | `WITH_JPEGXL` | _ON_ | Not supported. (see note) |
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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.
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@note OpenJPEG have higher priority than JasPer which is deprecated. In order to use JasPer, OpenJPEG must be disabled.
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@note (JPEG XL) OpenCV doesn't contain libjxl source code, so `BUILD_JPEGXL` is not supported.
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### GDAL integration
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@@ -9,41 +9,49 @@ Installation in MacOS {#tutorial_macos_install}
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| Original author | `@sajarindider` |
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| Compatibility | OpenCV >= 3.4 |
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The following steps have been tested for MacOSX (Mavericks) but should work with other versions as well.
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The following steps have been tested for macOS (Mavericks) but should work with other versions as well.
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Required Packages
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-----------------
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- CMake 3.9 or higher
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- Git
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- Python 2.7 or later and Numpy 1.5 or later
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- Python 3.x and NumPy 1.5 or later
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This tutorial will assume you have [Python](https://docs.python.org/3/using/mac.html),
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[Numpy](https://docs.scipy.org/doc/numpy-1.10.1/user/install.html) and
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[Git](https://www.atlassian.com/git/tutorials/install-git) installed on your machine.
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[NumPy](https://numpy.org/install/) and
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[Git](https://git-scm.com/downloads/mac) installed on your machine.
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@note
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OSX comes with Python 2.7 by default, you will need to install Python 3.8 if you want to use it specifically.
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- macOS up to 12.2 (Monterey): Comes with Python 2.7 pre-installed.
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- macOS 12.3 and later: Python 2.7 has been removed, and no version of Python is included by default.
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It is recommended to install the latest version of Python 3.x (at least Python 3.8) for compatibility with the latest OpenCV Python bindings.
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@note
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If you XCode and XCode Command Line-Tools installed, you already have git installed on your machine.
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If you have Xcode and Xcode Command Line Tools installed, Git is already available on your machine.
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Installing CMake
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----------------
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-# Find the version for your system and download CMake from their release's [page](https://cmake.org/download/)
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-# Install the dmg package and launch it from Applications. That will give you the UI app of CMake
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-# Install the `.dmg` package and launch it from Applications. That will give you the UI app of CMake
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-# From the CMake app window, choose menu Tools --> How to Install For Command Line Use. Then, follow the instructions from the pop-up there.
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-# Install folder will be /usr/bin/ by default, submit it by choosing Install command line links.
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-# The install folder will be `/usr/local/bin/` by default. Complete the installation by choosing Install command line links.
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-# Test that CMake is installed correctly by running:
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-# Test that it works by running
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@code{.bash}
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cmake --version
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@endcode
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@note You can use [Homebrew](https://brew.sh/) to install CMake with @code{.bash} brew install cmake @endcode
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@note You can use [Homebrew](https://brew.sh/) to install CMake with:
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@code{.bash}
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brew install cmake
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@endcode
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Getting OpenCV Source Code
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--------------------------
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@@ -53,20 +61,22 @@ You can use the latest stable OpenCV version or you can grab the latest snapshot
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### Getting the Latest Stable OpenCV Version
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- Go to our [downloads page](https://opencv.org/releases).
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- Download the source archive and unpack it.
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- Go to our [OpenCV releases page](https://opencv.org/releases).
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- Download the source archive of the latest version (e.g., OpenCV 4.x) and unpack it.
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### Getting the Cutting-edge OpenCV from the Git Repository
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Launch Git client and clone [OpenCV repository](http://github.com/opencv/opencv).
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If you need modules from [OpenCV contrib repository](http://github.com/opencv/opencv_contrib) then clone it as well.
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Launch Git client and clone [OpenCV repository](https://github.com/opencv/opencv).
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If you need modules from [OpenCV contrib repository](https://github.com/opencv/opencv_contrib) then clone it as well.
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For example:
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@code{.bash}
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cd ~/<your_working_directory>
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git clone https://github.com/opencv/opencv.git
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git clone https://github.com/opencv/opencv_contrib.git
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@endcode
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For example
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@code{.bash}
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cd ~/<my_working_directory>
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git clone https://github.com/opencv/opencv.git
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git clone https://github.com/opencv/opencv_contrib.git
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@endcode
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Building OpenCV from Source Using CMake
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---------------------------------------
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@@ -74,51 +84,96 @@ Building OpenCV from Source Using CMake
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the generated Makefiles, project files as well the object files and output binaries and enter
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there.
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For example
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For example:
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@code{.bash}
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mkdir build_opencv
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cd build_opencv
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@endcode
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@note It is good practice to keep clean your source code directories. Create build directory outside of source tree.
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@note It is good practice to keep your source code directories clean. Create the build directory outside of the source tree.
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-# Configuring. Run `cmake [<some optional parameters>] <path to the OpenCV source directory>`
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For example
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For example:
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@code{.bash}
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cmake -DCMAKE_BUILD_TYPE=Release -DBUILD_EXAMPLES=ON ../opencv
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@endcode
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or cmake-gui
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Alternatively, you can use the CMake GUI (`cmake-gui`):
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- set the OpenCV source code path to, e.g. `/home/user/opencv`
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- set the binary build path to your CMake build directory, e.g. `/home/user/build_opencv`
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- set the OpenCV source code path to, e.g. `/Users/your_username/opencv`
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- set the binary build path to your CMake build directory, e.g. `/Users/your_username/build_opencv`
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- set optional parameters
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- run: "Configure"
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- run: "Generate"
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-# Description of some parameters
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- build type: `CMAKE_BUILD_TYPE=Release` (or `Debug`)
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- to build with modules from opencv_contrib set `OPENCV_EXTRA_MODULES_PATH` to `<path to
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opencv_contrib>/modules`
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- set `BUILD_DOCS=ON` for building documents (doxygen is required)
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- set `BUILD_EXAMPLES=ON` to build all examples
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- build type: `-DCMAKE_BUILD_TYPE=Release` (or `Debug`).
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- include Extra Modules: If you cloned the `opencv_contrib` repository and want to include its modules, set:
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@code{.bash}
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-DOPENCV_EXTRA_MODULES_PATH=../opencv_contrib/modules
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@endcode
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- set `-DBUILD_DOCS=ON` for building documents (doxygen is required)
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- set `-DBUILD_EXAMPLES=ON` to build all examples
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-# [optional] Building python. Set the following python parameters:
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- `PYTHON3_EXECUTABLE = <path to python>`
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- `PYTHON3_INCLUDE_DIR = /usr/include/python<version>`
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- `PYTHON3_NUMPY_INCLUDE_DIRS =
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/usr/lib/python<version>/dist-packages/numpy/core/include/`
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- `-DPYTHON3_EXECUTABLE=$(which python3)`
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- `-DPYTHON3_INCLUDE_DIR=$(python3 -c "from sysconfig import get_paths as gp; print(gp()['include'])")`
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- `-DPYTHON3_NUMPY_INCLUDE_DIRS=$(python3 -c "import numpy; print(numpy.get_include())")`
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-# Build. From build directory execute *make*, it is recommended to do this in several threads
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For example
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For example:
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@code{.bash}
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make -j7 # runs 7 jobs in parallel
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make -j$(sysctl -n hw.ncpu) # runs the build using all available CPU cores
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@endcode
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-# To use OpenCV in your CMake-based projects through `find_package(OpenCV)` specify `OpenCV_DIR=<path_to_build_or_install_directory>` variable.
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-# After building, you can install OpenCV system-wide using:
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@code{.bash}
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sudo make install
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@endcode
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-# To use OpenCV in your CMake-based projects through `find_package(OpenCV)`, specify the `OpenCV_DIR` variable pointing to the build or install directory.
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For example:
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@code{.bash}
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cmake -DOpenCV_DIR=~/build_opencv ..
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@endcode
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### Verifying the OpenCV Installation
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After building (and optionally installing) OpenCV, you can verify the installation by checking the version using Python:
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@code{.bash}
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python3 -c "import cv2; print(cv2.__version__)"
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@endcode
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This command should output the version of OpenCV you have installed.
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@note
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You can also use a package manager like [Homebrew](https://brew.sh/)
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or [pip](https://pip.pypa.io/en/stable/) to install releases of OpenCV only (Not the cutting edge).
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- Installing via Homebrew:
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For example:
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@code{.bash}
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brew install opencv
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@endcode
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- Installing via pip:
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For example:
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@code{.bash}
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pip install opencv-python
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@endcode
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@note To access the extra modules from `opencv_contrib`, install the `opencv-contrib-python` package using `pip install opencv-contrib-python`.
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Reference in New Issue
Block a user