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春季启动无法解析查看页面(Spring boot cannot resolve view page)

 我正在尝试使用Spring Boot运行简单的Web应用程序，但解析视图时出现问题。 当我去http：// localhost：8080 /它显示; 
 

There was an unexpected error (type=Not Found, status=404).

 

 有没有遗失的财产或图书馆？ 为什么它不能解决我的HTML页面？ 
 

 我的application.properties; 
 

spring.mvc.view.prefix: WEB-INF/html/
spring.mvc.view.suffix: .html

 

 在这里输入图像描述 
 

@SpringBootApplication
public class DemoApplication {

    public static void main(String[] args) {
        SpringApplication.run(DemoApplication.class, args);
    }
}



@Controller
public class InfoController {

    @RequestMapping("/")
    public String getServerInfo(Map<String, Object> model){

        //This method works without any problem.

        model.put("message", "server info");
        return "info";  

    }

}


I am trying to run a simple web application with using Spring Boot but there is a problem with resolving view. When I go to http://localhost:8080/ it shows;
 

There was an unexpected error (type=Not Found, status=404).

 

Is there any missing property or library? Why it cannot resolve my html page?
 

My application.properties;
 

spring.mvc.view.prefix: WEB-INF/html/
spring.mvc.view.suffix: .html

 

enter image description here
 

@SpringBootApplication
public class DemoApplication {

    public static void main(String[] args) {
        SpringApplication.run(DemoApplication.class, args);
    }
}



@Controller
public class InfoController {

    @RequestMapping("/")
    public String getServerInfo(Map<String, Object> model){

        //This method works without any problem.

        model.put("message", "server info");
        return "info";  

    }

}


原文：https://stackoverflow.com/questions/49364084
更新时间：2023-10-10 17:10

最满意答案

 避免在旋转图像时获得Jaggies效果的一种方法是使用另一种方法来采样像素，而不仅仅是调整像素，例如使用最近邻居插值来使边缘更平滑。 你可以看到matlab代码示例： 
 

im1 = imread('lena.jpg');imshow(im1);  
[m,n,p]=size(im1);
thet = rand(1);
mm = m*sqrt(2);
nn = n*sqrt(2);
for t=1:mm
   for s=1:nn
      i = uint16((t-mm/2)*cos(thet)+(s-nn/2)*sin(thet)+m/2);
      j = uint16(-(t-mm/2)*sin(thet)+(s-nn/2)*cos(thet)+n/2);
      if i>0 && j>0 && i<=m && j<=n           
         im2(t,s,:)=im1(i,j,:);
      end
   end
end
figure;
imshow(im2);

 

 取自（ 这里 ）。 基本上，这意味着当对原始图像中的像素进行采样时，我们会在像素附近采样并对它们进行插值以获得目标像素值。 通过这种方式，您可以完成您想要的安装任何附加软件包。 
 

 编辑 
 

 我发现了一些我曾经用Java编写过的旧代码，其中包含了几个取样算法的实现。 代码如下： 
 

 最近的邻居采样器： 
 

/**
 * @pre (this!=null) && (this.pixels!=null)
 * @post returns the sampled pixel of (x,y) by nearest neighbor sampling
 */
private Pixel sampleNearestNeighbor(double x, double y) {
    int X = (int) Math.round(x);
    int Y = (int) Math.round(y);
    if (X >= 0 && Y >= 0 && X < this.pixels.length
            && Y < this.pixels[0].length)
        // (X,Y) is within this.pixels' borders
        return new Pixel(pixels[X][Y].getRGB());
    else
        return new Pixel(255, 255, 255);
    // sample color will be default white
}

 

 双线采样器： 
 

/**
 * @pre (this!=null) && (this.pixels!=null)
 * @post returns the sampled pixel of (x,y) by bilinear interpolation
 */
private Pixel sampleBilinear(double x, double y) {
    int x1, y1, x2, y2;
    x1 = (int) Math.floor(x);
    y1 = (int) Math.floor(y);
    double weightX = x - x1;
    double weightY = y - y1;
    if (x1 >= 0 && y1 >= 0 && x1 + 1 < this.pixels.length
            && y1 + 1 < this.pixels[0].length) {
        x2 = x1 + 1;
        y2 = y1 + 1;

        double redAX = (weightX * this.pixels[x2][y1].getRed())
                + (1 - weightX) * this.pixels[x1][y1].getRed();
        double greenAX = (weightX * this.pixels[x2][y1].getGreen())
                + (1 - weightX) * this.pixels[x1][y1].getGreen();
        double blueAX = (weightX * this.pixels[x2][y1].getBlue())
                + (1 - weightX) * this.pixels[x1][y1].getBlue();
        // bilinear interpolation of A point

        double redBX = (weightX * this.pixels[x2][y2].getRed())
                + (1 - weightX) * this.pixels[x1][y2].getRed();
        double greenBX = (weightX * this.pixels[x2][y2].getGreen())
                + (1 - weightX) * this.pixels[x1][y2].getGreen();
        double blueBX = (weightX * this.pixels[x2][y2].getBlue())
                + (1 - weightX) * this.pixels[x1][y2].getBlue();
        // bilinear interpolation of B point

        int red = (int) (weightY * redBX + (1 - weightY) * redAX);
        int green = (int) (weightY * greenBX + (1 - weightY) * greenAX);
        int blue = (int) (weightY * blueBX + (1 - weightY) * blueAX);
        // bilinear interpolation of A and B
        return new Pixel(red, green, blue);

    } else if (x1 >= 0
            && y1 >= 0 // last row or column
            && (x1 == this.pixels.length - 1 || y1 == this.pixels[0].length - 1)) {
        return new Pixel(this.pixels[x1][y1].getRed(), this.pixels[x1][y1]
                .getGreen(), this.pixels[x1][y1].getBlue());
    } else
        return new Pixel(255, 255, 255);
    // sample color will be default white
}

 

 高斯采样器： 
 

/**
 * @pre (this!=null) && (this.pixels!=null)
 * @post returns the sampled pixel of (x,y) by gaussian function
 */
private Pixel sampleGaussian(double u, double v) {
    double w = 3; // sampling distance
    double sqrSigma = Math.pow(w / 3.0, 2); // sigma^2
    double normal = 0;
    double red = 0, green = 0, blue = 0;
    double minIX = Math.round(u - w);
    double maxIX = Math.round(u + w);
    double minIY = Math.round(v - w);
    double maxIY = Math.round(v + w);

    for (int ix = (int) minIX; ix <= maxIX; ix++) {
        for (int iy = (int) minIY; iy <= maxIY; iy++) {
            double sqrD = Math.pow(ix - u, 2) + Math.pow(iy - v, 2);
            // squared distance between (ix,iy) and (u,v)
            if (sqrD < Math.pow(w, 2) && ix >= 0 && iy >= 0
                    && ix < pixels.length && iy < pixels[0].length) {
                // gaussian function
                double gaussianWeight = Math.pow(2, -1 * (sqrD / sqrSigma));
                normal += gaussianWeight;
                red += gaussianWeight * pixels[ix][iy].getRed();
                green += gaussianWeight * pixels[ix][iy].getGreen();
                blue += gaussianWeight * pixels[ix][iy].getBlue();
            }
        }
    }
    red /= normal;
    green /= normal;
    blue /= normal;
    return new Pixel(red, green, blue);
}

 

 实际旋转： 
 

     /**
 * @pre (this!=null) && (this.pixels!=null) && (1 <= samplingMethod <= 3)
 * @post creates a new rotated-by-degrees Image and returns it
 */
public myImage rotate(double degrees, int samplingMethod) {
    myImage outputImg = null;

    int t = 0;
    for (; degrees < 0 || degrees >= 180; degrees += (degrees < 0) ? 180
            : -180)
        t++;

    int w = this.pixels.length;
    int h = this.pixels[0].length;
    double cosinus = Math.cos(Math.toRadians(degrees));
    double sinus = Math.sin(Math.toRadians(degrees));

    int width = Math.round((float) (w * Math.abs(cosinus) + h * sinus));
    int height = Math.round((float) (h * Math.abs(cosinus) + w * sinus));

    w--;
    h--; // move from (1,..,k) to (0,..,1-k)

    Pixel[][] pixelsArray = new Pixel[width][height];
    double x = 0; // x coordinate in the source image
    double y = 0; // y coordinate in the source image

    if (degrees >= 90) { // // 270 or 90 degrees turn
        double temp = cosinus;
        cosinus = sinus;
        sinus = -temp;
    }

    for (int i = 0; i < width; i++) {
        for (int j = 0; j < height; j++) {

            double x0 = i;
            double y0 = j;
            if (degrees >= 90) {
                if ((t % 2 == 1)) { // 270 degrees turn
                    x0 = j;
                    y0 = width - i - 1;
                } else { // 90 degrees turn
                    x0 = height - j - 1;
                    y0 = i;
                }
            } else if (t % 2 == 1) { // 180 degrees turn
                x0 = width - x0 - 1;
                y0 = height - y0 - 1;
            }

            // calculate new x/y coordinates and
            // adjust their locations to the middle of the picture
            x = x0 * cosinus - (y0 - sinus * w) * sinus;
            y = x0 * sinus + (y0 - sinus * w) * cosinus;

            if (x < -0.5 || x > w + 0.5 || y < -0.5 || y > h + 0.5)
                // the pixels that does not have a source will be painted in
                // default white
                pixelsArray[i][j] = new Pixel(255, 255, 255);
            else {
                if (samplingMethod == 1)
                    pixelsArray[i][j] = sampleNearestNeighbor(x, y);
                else if (samplingMethod == 2)
                    pixelsArray[i][j] = sampleBilinear(x, y);
                else if (samplingMethod == 3)
                    pixelsArray[i][j] = sampleGaussian(x, y);
            }
        }
        outputImg = new myImage(pixelsArray);
    }

    return outputImg;
}


One way to avoid from getting the Jaggies effect when rotating images is by using another way to sample the pixels than just taking the adjusted pixels, for example to use Nearest-neighbor interpolation to make the edges smoother. You can see matlab code example:
 

im1 = imread('lena.jpg');imshow(im1);  
[m,n,p]=size(im1);
thet = rand(1);
mm = m*sqrt(2);
nn = n*sqrt(2);
for t=1:mm
   for s=1:nn
      i = uint16((t-mm/2)*cos(thet)+(s-nn/2)*sin(thet)+m/2);
      j = uint16(-(t-mm/2)*sin(thet)+(s-nn/2)*cos(thet)+n/2);
      if i>0 && j>0 && i<=m && j<=n           
         im2(t,s,:)=im1(i,j,:);
      end
   end
end
figure;
imshow(im2);

 

taken from (here). Basically it means that when sampling the pixels in the original picture, we sample near pixels and interpolate them to get the target pixel value. This way you can achive waht you want withourt installing any additiional packages.
 

EDIT
 

I've found some old code I once wrote in Java, which contains implementations of a couple of sampling algorithems. Here is the code:
 

Nearest Neighbor sampler:
 

/**
 * @pre (this!=null) && (this.pixels!=null)
 * @post returns the sampled pixel of (x,y) by nearest neighbor sampling
 */
private Pixel sampleNearestNeighbor(double x, double y) {
    int X = (int) Math.round(x);
    int Y = (int) Math.round(y);
    if (X >= 0 && Y >= 0 && X < this.pixels.length
            && Y < this.pixels[0].length)
        // (X,Y) is within this.pixels' borders
        return new Pixel(pixels[X][Y].getRGB());
    else
        return new Pixel(255, 255, 255);
    // sample color will be default white
}

 

Bilinear sampler:
 

/**
 * @pre (this!=null) && (this.pixels!=null)
 * @post returns the sampled pixel of (x,y) by bilinear interpolation
 */
private Pixel sampleBilinear(double x, double y) {
    int x1, y1, x2, y2;
    x1 = (int) Math.floor(x);
    y1 = (int) Math.floor(y);
    double weightX = x - x1;
    double weightY = y - y1;
    if (x1 >= 0 && y1 >= 0 && x1 + 1 < this.pixels.length
            && y1 + 1 < this.pixels[0].length) {
        x2 = x1 + 1;
        y2 = y1 + 1;

        double redAX = (weightX * this.pixels[x2][y1].getRed())
                + (1 - weightX) * this.pixels[x1][y1].getRed();
        double greenAX = (weightX * this.pixels[x2][y1].getGreen())
                + (1 - weightX) * this.pixels[x1][y1].getGreen();
        double blueAX = (weightX * this.pixels[x2][y1].getBlue())
                + (1 - weightX) * this.pixels[x1][y1].getBlue();
        // bilinear interpolation of A point

        double redBX = (weightX * this.pixels[x2][y2].getRed())
                + (1 - weightX) * this.pixels[x1][y2].getRed();
        double greenBX = (weightX * this.pixels[x2][y2].getGreen())
                + (1 - weightX) * this.pixels[x1][y2].getGreen();
        double blueBX = (weightX * this.pixels[x2][y2].getBlue())
                + (1 - weightX) * this.pixels[x1][y2].getBlue();
        // bilinear interpolation of B point

        int red = (int) (weightY * redBX + (1 - weightY) * redAX);
        int green = (int) (weightY * greenBX + (1 - weightY) * greenAX);
        int blue = (int) (weightY * blueBX + (1 - weightY) * blueAX);
        // bilinear interpolation of A and B
        return new Pixel(red, green, blue);

    } else if (x1 >= 0
            && y1 >= 0 // last row or column
            && (x1 == this.pixels.length - 1 || y1 == this.pixels[0].length - 1)) {
        return new Pixel(this.pixels[x1][y1].getRed(), this.pixels[x1][y1]
                .getGreen(), this.pixels[x1][y1].getBlue());
    } else
        return new Pixel(255, 255, 255);
    // sample color will be default white
}

 

Gaussian sampler:
 

/**
 * @pre (this!=null) && (this.pixels!=null)
 * @post returns the sampled pixel of (x,y) by gaussian function
 */
private Pixel sampleGaussian(double u, double v) {
    double w = 3; // sampling distance
    double sqrSigma = Math.pow(w / 3.0, 2); // sigma^2
    double normal = 0;
    double red = 0, green = 0, blue = 0;
    double minIX = Math.round(u - w);
    double maxIX = Math.round(u + w);
    double minIY = Math.round(v - w);
    double maxIY = Math.round(v + w);

    for (int ix = (int) minIX; ix <= maxIX; ix++) {
        for (int iy = (int) minIY; iy <= maxIY; iy++) {
            double sqrD = Math.pow(ix - u, 2) + Math.pow(iy - v, 2);
            // squared distance between (ix,iy) and (u,v)
            if (sqrD < Math.pow(w, 2) && ix >= 0 && iy >= 0
                    && ix < pixels.length && iy < pixels[0].length) {
                // gaussian function
                double gaussianWeight = Math.pow(2, -1 * (sqrD / sqrSigma));
                normal += gaussianWeight;
                red += gaussianWeight * pixels[ix][iy].getRed();
                green += gaussianWeight * pixels[ix][iy].getGreen();
                blue += gaussianWeight * pixels[ix][iy].getBlue();
            }
        }
    }
    red /= normal;
    green /= normal;
    blue /= normal;
    return new Pixel(red, green, blue);
}

 

Actual rotate:
 

     /**
 * @pre (this!=null) && (this.pixels!=null) && (1 <= samplingMethod <= 3)
 * @post creates a new rotated-by-degrees Image and returns it
 */
public myImage rotate(double degrees, int samplingMethod) {
    myImage outputImg = null;

    int t = 0;
    for (; degrees < 0 || degrees >= 180; degrees += (degrees < 0) ? 180
            : -180)
        t++;

    int w = this.pixels.length;
    int h = this.pixels[0].length;
    double cosinus = Math.cos(Math.toRadians(degrees));
    double sinus = Math.sin(Math.toRadians(degrees));

    int width = Math.round((float) (w * Math.abs(cosinus) + h * sinus));
    int height = Math.round((float) (h * Math.abs(cosinus) + w * sinus));

    w--;
    h--; // move from (1,..,k) to (0,..,1-k)

    Pixel[][] pixelsArray = new Pixel[width][height];
    double x = 0; // x coordinate in the source image
    double y = 0; // y coordinate in the source image

    if (degrees >= 90) { // // 270 or 90 degrees turn
        double temp = cosinus;
        cosinus = sinus;
        sinus = -temp;
    }

    for (int i = 0; i < width; i++) {
        for (int j = 0; j < height; j++) {

            double x0 = i;
            double y0 = j;
            if (degrees >= 90) {
                if ((t % 2 == 1)) { // 270 degrees turn
                    x0 = j;
                    y0 = width - i - 1;
                } else { // 90 degrees turn
                    x0 = height - j - 1;
                    y0 = i;
                }
            } else if (t % 2 == 1) { // 180 degrees turn
                x0 = width - x0 - 1;
                y0 = height - y0 - 1;
            }

            // calculate new x/y coordinates and
            // adjust their locations to the middle of the picture
            x = x0 * cosinus - (y0 - sinus * w) * sinus;
            y = x0 * sinus + (y0 - sinus * w) * cosinus;

            if (x < -0.5 || x > w + 0.5 || y < -0.5 || y > h + 0.5)
                // the pixels that does not have a source will be painted in
                // default white
                pixelsArray[i][j] = new Pixel(255, 255, 255);
            else {
                if (samplingMethod == 1)
                    pixelsArray[i][j] = sampleNearestNeighbor(x, y);
                else if (samplingMethod == 2)
                    pixelsArray[i][j] = sampleBilinear(x, y);
                else if (samplingMethod == 3)
                    pixelsArray[i][j] = sampleGaussian(x, y);
            }
        }
        outputImg = new myImage(pixelsArray);
    }

    return outputImg;
}

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