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,但它是用Objective-C编写的。我试图在swift中转换它,但是我遇到了很多错误,我找不到修复它们的方法。
使用Swift做到这一点的最好方法是什么?
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;
}
答案 0 :(得分:6)
使用Accelerate的vImageHistogramCalculation
来获取图像中不同频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))
运行此选项后,alpha
,red
,green
和blue
现在是图片中颜色的直方图。如果red
,green
和blue
每个都只计算在第0个点,而alpha
只计算在最后一个点,则您的图像为黑色。
如果您不想检查多个阵列,可以使用vImageMatrixMultiply
组合不同的频道:
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))
如果你在直方图之前坚持这一点,你的imgBuffer
将被修改到位以平均每个像素中的RGB,将平均值写入B通道。因此,您只需检查blue
直方图,而不是全部三个。
(顺便说一句,我发现的vImageMatrixMultiply
的最佳描述位于源代码中,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)
答案 1 :(得分:0)
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数。
但是,如果要提高阈值,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
}
}
您可以这样称呼:
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。