Opencv 仿射变换放大缩小|极客教程

仿射变换，又称仿射映射，是指在几何中，一个向量空间进行一次线性变换并接上一个平移，变换为另一个向量空间.
如何进行放大缩小？
1. 使用仿射变换，将图片在 $x$ 方向上放大 $1.3$ 倍，在 $y$ 方向上缩小至原来的 $\frac{4}{5}$ 。
2. 在上面的条件下，同时在 $x$ 方向上向右平移 $30$ （ $+30$ ），在 $y$ 方向上向上平移 $30$ （ $-30$ ）。

python实现：

import cv2
import numpy as np
import matplotlib.pyplot as plt


# Affine
def affine(img, a, b, c, d, tx, ty):
    H, W, C = img.shape

    # temporary image
    img = np.zeros((H+2, W+2, C), dtype=np.float32)
    img[1:H+1, 1:W+1] = _img

    # get new image shape
    H_new = np.round(H * d).astype(np.int)
    W_new = np.round(W * a).astype(np.int)
    out = np.zeros((H_new+1, W_new+1, C), dtype=np.float32)

    # get position of new image
    x_new = np.tile(np.arange(W_new), (H_new, 1))
    y_new = np.arange(H_new).repeat(W_new).reshape(H_new, -1)

    # get position of original image by affine
    adbc = a * d - b * c
    x = np.round((d * x_new  - b * y_new) / adbc).astype(np.int) - tx + 1
    y = np.round((-c * x_new + a * y_new) / adbc).astype(np.int) - ty + 1

    x = np.minimum(np.maximum(x, 0), W+1).astype(np.int)
    y = np.minimum(np.maximum(y, 0), H+1).astype(np.int)

    # assgin pixcel to new image
    out[y_new, x_new] = img[y, x]

    out = out[:H_new, :W_new]
    out = out.astype(np.uint8)

    return out


# Read image
_img = cv2.imread("imori.jpg").astype(np.float32)

# Affine
out = affine(img, a=1.3, b=0, c=0, d=0.8, tx=30, ty=-30)


# Save result
cv2.imshow("result", out)
cv2.waitKey(0)
cv2.imwrite("out.jpg", out)

c++实现：

#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <iostream>
#include <math.h>


// affine
cv::Mat affine(cv::Mat img, double a, double b, double c, double d, double tx, double ty){
  // get height and width
  int width = img.cols;
  int height = img.rows;
  int channel = img.channels();

  // get detriment
  double det = a * d - b * c;

  // Resize width and height
  int resized_width = (int)(width * a);
  int resized_height = (int)(height * d);

  // other parameters
  int x_before, y_before;
  double dx, dy, wx, wy, w_sum;
  double val;
  int _x, _y;

  // output
  cv::Mat out = cv::Mat::zeros(resized_height, resized_width, CV_8UC3);

  // Affine transformation
  for (int y = 0; y < resized_height; y++){    
    for (int x = 0; x < resized_width; x++){

      // get original position x
      x_before = (int)((d * x - b * y) / det - tx);

      if ((x_before < 0) || (x_before >= width)){
        continue;
      }

      // get original position y
      y_before = (int)((-c * x + a * y) / det - ty);

      if ((y_before < 0) || (y_before >= height)){
        continue;
      }

      // assign pixel to new position
      for (int c = 0; c < channel; c++){
        out.at<cv::Vec3b>(y, x)[c] = img.at<cv::Vec3b>(y_before, x_before)[c];
      }
    }
  }

  return out;
}


int main(int argc, const char* argv[]){
  // read image
  cv::Mat img = cv::imread("imori.jpg", cv::IMREAD_COLOR);

  // affine
  cv::Mat out = affine(img, 1.3, 0, 0, 0.8, 30, -30);

  //cv::imwrite("out.jpg", out);
  cv::imshow("answer", out);
  cv::waitKey(0);
  cv::destroyAllWindows();

  return 0;
}

输入：

Opencv 仿射变换