Swift 2.2 - 在 UIImage 中计算黑色像素

Question

我需要计算UIImage 中的所有黑色像素。我找到了一个可以工作的代码，但是它是用 Objective-C 编写的。我试图快速转换它，但我得到很多错误，我找不到修复它们的方法。

使用 Swift 进行此操作的最佳方法是什么？

简单图片

目标-C：

/**
 * Structure to keep one pixel in RRRRRRRRGGGGGGGGBBBBBBBBAAAAAAAA format
 */

struct pixel {
    unsigned char r, g, b, a;
};

/**
 * Process the image and return the number of pure red pixels in it.
 */

- (NSUInteger) processImage: (UIImage*) image
{
    NSUInteger numberOfRedPixels = 0;

    // Allocate a buffer big enough to hold all the pixels

    struct pixel* pixels = (struct pixel*) calloc(1, image.size.width * image.size.height * sizeof(struct pixel));
    if (pixels != nil)
    {
        // Create a new bitmap

        CGContextRef context = CGBitmapContextCreate(
            (void*) pixels,
            image.size.width,
            image.size.height,
            8,
            image.size.width * 4,
            CGImageGetColorSpace(image.CGImage),
            kCGImageAlphaPremultipliedLast
        );

        if (context != NULL)
        {
            // Draw the image in the bitmap

            CGContextDrawImage(context, CGRectMake(0.0f, 0.0f, image.size.width, image.size.height), image.CGImage);

            // Now that we have the image drawn in our own buffer, we can loop over the pixels to
            // process it. This simple case simply counts all pixels that have a pure red component.

            // There are probably more efficient and interesting ways to do this. But the important
            // part is that the pixels buffer can be read directly.

            NSUInteger numberOfPixels = image.size.width * image.size.height;

            while (numberOfPixels > 0) {
                if (pixels->r == 255) {
                    numberOfRedPixels++;
                }
                pixels++;
                numberOfPixels--;
            }

            CGContextRelease(context);
        }

        free(pixels);
    }

    return numberOfRedPixels;
}

Answer 1

使用 Accelerate 的 vImageHistogramCalculation 获得图像中不同通道的直方图要快得多：

let img: CGImage = CIImage(image: image!)!.cgImage!

let imgProvider: CGDataProvider = img.dataProvider!
let imgBitmapData: CFData = imgProvider.data!
var imgBuffer = vImage_Buffer(data: UnsafeMutableRawPointer(mutating: CFDataGetBytePtr(imgBitmapData)), height: vImagePixelCount(img.height), width: vImagePixelCount(img.width), rowBytes: img.bytesPerRow)

let alpha = [UInt](repeating: 0, count: 256)
let red = [UInt](repeating: 0, count: 256)
let green = [UInt](repeating: 0, count: 256)
let blue = [UInt](repeating: 0, count: 256)

let alphaPtr = UnsafeMutablePointer<vImagePixelCount>(mutating: alpha) as UnsafeMutablePointer<vImagePixelCount>?
let redPtr = UnsafeMutablePointer<vImagePixelCount>(mutating: red) as UnsafeMutablePointer<vImagePixelCount>?
let greenPtr = UnsafeMutablePointer<vImagePixelCount>(mutating: green) as UnsafeMutablePointer<vImagePixelCount>?
let bluePtr = UnsafeMutablePointer<vImagePixelCount>(mutating: blue) as UnsafeMutablePointer<vImagePixelCount>?

let rgba = [redPtr, greenPtr, bluePtr, alphaPtr]

let histogram = UnsafeMutablePointer<UnsafeMutablePointer<vImagePixelCount>?>(mutating: rgba)
let error = vImageHistogramCalculation_ARGB8888(&imgBuffer, histogram, UInt32(kvImageNoFlags))

运行后，alpha、red、green 和 blue 现在是图像中颜色的直方图。如果red、green和blue都只有第0个位置，而alpha只有最后一个位置，你的图像是黑色的。

如果您甚至不想检查多个数组，可以使用vImageMatrixMultiply 组合您的不同通道：

let readableMatrix: [[Int16]] = [
    [3,     0,     0,    0]
    [0,     1,     1,    1],
    [0,     0,     0,    0],
    [0,     0,     0,    0]
]

var matrix: [Int16] = [Int16](repeating: 0, count: 16)

for i in 0...3 {
    for j in 0...3 {
        matrix[(3 - j) * 4 + (3 - i)] = readableMatrix[i][j]
    }
}
vImageMatrixMultiply_ARGB8888(&imgBuffer, &imgBuffer, matrix, 3, nil, nil, UInt32(kvImageNoFlags))

如果您在直方图之前将其插入，您的imgBuffer 将被修改为平均每个像素中的 RGB，并将平均值写入 B 通道。因此，您可以只检查blue 直方图而不是全部三个。

（顺便说一句，我在源代码中找到了对vImageMatrixMultiply 的最佳描述，例如https://github.com/phracker/MacOSX-SDKs/blob/2d31dd8bdd670293b59869335d9f1f80ca2075e0/MacOSX10.7.sdk/System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vImage.framework/Versions/A/Headers/Transform.h#L21）

Answer 2

我现在遇到了类似的问题，我需要确定图像是否为 100% 黑色。以下代码将返回它在图像中找到的纯黑色像素的数量。

但是，如果您想提高阈值，您可以更改比较值，并允许它容忍更广泛的可能颜色。

import UIKit

extension UIImage {
    var blackPixelCount: Int {
        var count = 0
        for x in 0..<Int(size.width) {
            for y in 0..<Int(size.height) {
                count = count + (isPixelBlack(CGPoint(x: CGFloat(x), y: CGFloat(y))) ? 1 : 0)
            }
        }

        return count
    }

    private func isPixelBlack(_ point: CGPoint) -> Bool {
        let pixelData = cgImage?.dataProvider?.data
        let pointerData: UnsafePointer<UInt8> = CFDataGetBytePtr(pixelData)

        let pixelInfo = Int(((size.width * point.y) + point.x)) * 4

        let maxValue: CGFloat = 255.0
        let compare: CGFloat = 0.01

        if (CGFloat(pointerData[pixelInfo]) / maxValue) > compare { return false }
        if (CGFloat(pointerData[pixelInfo + 1]) / maxValue) > compare { return false }
        if (CGFloat(pointerData[pixelInfo + 2]) / maxValue) > compare { return false }

        return true
    }
}

你可以这样称呼：

let count = image.blackPixelCount

需要注意的是，这是一个非常缓慢的过程，即使在小图像上也是如此。