ubuntu22.04@laptop OpenCV Get Started: 005_rotate_and_translate_image
- [1. 源由](#1. 源由)
- [2. translate/rotate应用Demo](#2. translate/rotate应用Demo)
- [3 translate_image](#3 translate_image)
-
- [3.1 C++应用Demo](#3.1 C++应用Demo)
- [3.2 Python应用Demo](#3.2 Python应用Demo)
- [3.3 平移图像过程](#3.3 平移图像过程)
- [4. rotate_image](#4. rotate_image)
-
- [4.1 C++应用Demo](#4.1 C++应用Demo)
- [4.2 Python应用Demo](#4.2 Python应用Demo)
- [4.3 旋转图像过程](#4.3 旋转图像过程)
- [5. 总结](#5. 总结)
- [6. 参考资料](#6. 参考资料)
1. 源由
图像的平移和旋转是图像编辑中最基本的操作之一。两者都属于广义仿射变换的范畴。
因此，在研究更复杂的变换之前，首先学习使用OpenCV中提供的函数旋转和平移图像。
2. translate/rotate应用Demo
005_rotate_and_translate_image是OpenCV平移和旋转的示例程序。
确认OpenCV安装路径：
$ find /home/daniel/ -name "OpenCVConfig.cmake"
/home/daniel/OpenCV/installation/opencv-4.9.0/lib/cmake/opencv4/
/home/daniel/OpenCV/opencv/build/OpenCVConfig.cmake
/home/daniel/OpenCV/opencv/build/unix-install/OpenCVConfig.cmake
$ export OpenCV_DIR=/home/daniel/OpenCV/installation/opencv-4.9.0/lib/cmake/opencv4/
3 translate_image
3.1 C++应用Demo
C++应用Demo工程结构：
005_rotate_and_translate_image/CPP$ tree .
.
└── translate_image
├── CMakeLists.txt
├── image.jpg
└── translate_image.cpp
2 directories, 6 files
C++应用Demo工程编译执行：
$ cd translate_image
$ mkdir build
$ cd build
$ cmake ..
$ cmake --build . --config Release
$ cd ..
$ ./build/translate_image
3.2 Python应用Demo
Python应用Demo工程结构：
005_rotate_and_translate_image/Python$ tree .
.
├── image.jpg
├── image_translation.py
├── requirements.txt
└── rotate_image.py
0 directories, 4 files
Python应用Demo工程执行：
$ workoncv-4.9.0
$ python image_translation.py
3.3 平移图像过程
引入平移矩阵对图像进行移动：
- t x t_x tx: X方向，正数向右移动；反之向左移动。
- t y t_y ty: Y方向，正数向下移动；反之向上移动。
C++:
// get tx and ty values for translation
float tx = float(width) / 4;
float ty = float(height) / 4;
// create the translation matrix using tx and ty
float warp_values[] = { 1.0, 0.0, tx, 0.0, 1.0, ty };
Mat translation_matrix = Mat(2, 3, CV_32F, warp_values);
// we will save the resulting image in translated_image matrix
Mat translated_image;
// apply affine transformation to the original image using translation matrix
warpAffine(image, translated_image, translation_matrix, image.size());
Python:
# get tx and ty values for translation
tx, ty = width / 4, height / 4 # you divide by value of your choice
# create the translation matrix using tx and ty, it is a NumPy array
translation_matrix = np.array([
[1, 0, tx],
[0, 1, ty]
], dtype=np.float32)
# apply the translation to the image
translated_image = cv2.warpAffine(
src=image, M=translation_matrix, dsize=(width, height)
)
4. rotate_image
4.1 C++应用Demo
C++应用Demo工程结构：
005_rotate_and_translate_image/CPP$ tree .
.
└── rotate_image
├── CMakeLists.txt
├── image.jpg
└── rotate_image.cpp
2 directories, 6 files
C++应用Demo工程编译执行：
$ cd rotate_image
$ mkdir build
$ cd build
$ cmake ..
$ cmake --build . --config Release
$ cd ..
$ ./build/rotate_image
4.2 Python应用Demo
Python应用Demo工程结构：
005_rotate_and_translate_image/Python$ tree .
.
├── image.jpg
├── image_translation.py
├── requirements.txt
└── rotate_image.py
0 directories, 4 files
Python应用Demo工程执行：
$ workoncv-4.9.0
$ python rotate_image.py
4.3 旋转图像过程
沿旋转中心点进行角度旋转，采用线性代数矩阵运算：
- 旋转中心点：采用了图片的重心
- 旋转角度：示例为45度
C++:
double angle = 45;
// get the center coordinates of the image to create the 2D rotation matrix
Point2f center((image.cols - 1) / 2.0, (image.rows - 1) / 2.0);
// create the rotation matrix using the image center
Mat rotation_matix = getRotationMatrix2D(center, angle, 1.0);
// we will save the resulting image in rotated_image matrix
Mat rotated_image;
// apply affine transformation to the original image using the 2D rotaiton matrix
warpAffine(image, rotated_image, rotation_matix, image.size());
Python:
# dividing height and width by 2 to get the center of the image
height, width = image.shape[:2]
center = (width/2, height/2)
# the above center is the center of rotation axis
# using cv2.getRotationMatrix2D() to get the rotation matrix
rotate_matrix = cv2.getRotationMatrix2D(center=center, angle=45, scale=1)
# rotate the image using cv2.warpAffine
rotated_image = cv2.warpAffine(src=image, M=rotate_matrix, dsize=(width, height))
5. 总结
通过对NumPy二维数组操作，对图像进行旋转和移动。
- center: 旋转中心点
- angle: 旋转角度
- scale: 缩放尺寸
- src: 源图像数组
- M: 转换矩阵
- dsize: 输出图像尺寸
- dst: 输出图像
- flags: 插值方法, INTER_LINEAR or INTER_NEAREST
- borderMode: 像素外推方法
- borderValue: 在恒定边界的情况下使用的值，默认值为0
6. 参考资料
【1】ubuntu22.04@laptop OpenCV Get Started