Android OpenCV基础API清晰度亮度识别检测

...
inline
Mat::Mat(int _rows, int _cols, int _type)
    : flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0),
      datalimit(0), allocator(0), u(0), size(&rows), step(0)
{
    create(_rows, _cols, _type);
}
inline
void Mat::create(int _rows, int _cols, int _type)
{
    _type &= TYPE_MASK;
    if( dims <= 2 && rows == _rows && cols == _cols && type() == _type && data )
        return;
    int sz[] = {_rows, _cols};
    create(2, sz, _type);
}
...

public static Mat imread(String filename, int flags) {
       return new Mat(imread_0(filename, flags));
}
// 调用例子
eg:
Mat bgr = Imgcodecs.imread(filePath, Imgcodecs.IMREAD_UNCHANGED);
Imgproc.cvtColor(bgr, srcMat, Imgproc.COLOR_BGR2RGB);
//Imgcodecs flags 常用参数含义
public static final int IMREAD_UNCHANGED = -1;  // 无改动
public static final int IMREAD_GRAYSCALE = 0;  // 单通道灰色
public static final int IMREAD_COLOR = 1;  //三通道BGR图像

Bitmap bitmap = BitmapFactory.decodeResource(res, R.drawable.icon);
Mat mat = Mat()
// bitmap : 支持ARGB_8888和RGB_565两种格式
// mat : 类型为CV_8UC4，通道顺序为RGBA
Utils.bitmapToMat(bitmap, mat);

File file = new File(Environment.getExternalStorageDirectory().getPath() + File.separator + "${System.currentTimeMillis()}.jpg");
 if (!file.exists()) {
        file.createNewFile();
 }
// 文件路径  ,  待输出mat对象
Imgcodecs.imwrite(file.getPath(), srcMat);

//亮度检测
private static float brightness(Mat grayImage) {
        float a = 0;
        int Hist[] = new int[256];
        for (int i = 0; i < 256; i++) {
            Hist[i] = 0;
        }
        for (int i = 0; i < grayImage.rows(); i++) {
            for (int j = 0; j < grayImage.cols(); j++) {
                //在计算过程中，考虑128为亮度均值点
                a += (float) (grayImage.get(i, j)[0] - 128);
                int x = (int) grayImage.get(i, j)[0];
                Hist[x]++;
            }
        }
        float da = a / (float) (grayImage.rows() * grayImage.cols());
        float D = Math.abs(da);
        float Ma = 0;
        for (int i = 0; i < 256; i++) {
            Ma += Math.abs(i - 128 - da) * Hist[i];
        }
        Ma /= (float) ((grayImage.rows() * grayImage.cols()));
        float M = Math.abs(Ma);
        float K = D / M;
        float cast = K;
        if (cast >= 1) {
            if (da > 0) {
                Log.e("ymc", "过亮");
            } else {
                Log.e("ymc", "过暗");
            }
        } else {
            Log.e("ymc", "亮度：正常");
        }
        return cast;
    }

//清晰度
private static double clarity(Mat grayImage) {
        Mat laplacianDstImage = new Mat();
        Imgproc.Laplacian(grayImage, laplacianDstImage, CvType.CV_64F);
        MatOfDouble median = new MatOfDouble();
        MatOfDouble std = new MatOfDouble();
        Core.meanStdDev(laplacianDstImage, median, std);
        double clarity = Math.pow(std.get(0, 0)[0], 2);
        //后续可根据业务设置阈值
        Log.e("ymc", "清晰度：" + clarity);
        laplacianDstImage.release();
        return clarity;
    }