本案例的目的是理解如何用Metal实现图像阀值素描滤镜，用于图像阀值素描，形成有噪点的素描；
Demo
HarbethDemo地址
实操代码
// 用于图像阀值素描，形成有噪点的素描
let filter = C7ThresholdSketch.init(edgeStrength: 2.5, threshold: 0.25)
// 方案1:
let dest = BoxxIO.init(element: originImage, filter: filter)
ImageView.image = try? dest.output()
dest.filters.forEach {
NSLog("%@", "\($0.parameterDescription)")
}
// 方案2:
ImageView.image = try? originImage.make(filter: filter)
// 方案3:
ImageView.image = originImage ->> filter
实现原理
过滤器
这款滤镜采用并行计算编码器设计.compute(kernel: "C7ThresholdSketch")，参数因子[edgeStrength, threshold]
对外开放参数
threshold: 任何高于这个阈值的边缘都是黑色的，低于白色的任何东西都是黑色的。edgeStrength: 调整滤波器的动态范围。更高的值会导致更强的边缘，但可以饱和强度的色彩空间。
public struct C7ThresholdSketch: C7FilterProtocol {
public static let range: ParameterRange
/// Any edge above this threshold will be black, and anything below white. Ranges from 0.0 to 1.0
@ZeroOneRange public var threshold: Float = range.value
/// Adjusts the dynamic range of the filter.
/// Higher values lead to stronger edges, but can saturate the intensity colorspace.
public var edgeStrength: Float = 1
public var modifier: Modifier {
return .compute(kernel: "C7ThresholdSketch")
}
public var factors: [Float] {
return [edgeStrength, threshold]
}
public init(edgeStrength: Float = 1, threshold: Float = range.value) {
self.edgeStrength = edgeStrength
self.threshold = threshold
}
}
着色器
取出周边1像素对应点的归一化坐标，获取到这些点对应的红色值； 水平方向取顶部和底部红色值做个整合处理，竖直方向取左边和右边做个整合处理，分别得到(h, v); length计算出范围值，step计算出阈值对应的颜色，最后得到黑色或白色像素颜色即可；
kernel void C7ThresholdSketch(texture2d
texture2d
constant float *edgeStrength [[buffer(0)]],
constant float *threshold [[buffer(1)]],
uint2 grid [[thread_position_in_grid]]) {
constexpr sampler quadSampler(mag_filter::linear, min_filter::linear);
const float x = float(grid.x);
const float y = float(grid.y);
const float width = float(inputTexture.get_width());
const float height = float(inputTexture.get_height());
const float2 leftCoordinate = float2((x - 1) / width, y / height);
const float2 rightCoordinate = float2((x + 1) / width, y / height);
const float2 topCoordinate = float2(x / width, (y - 1) / height);
const float2 bottomCoordinate = float2(x / width, (y + 1) / height);
const float2 topLeftCoordinate = float2((x - 1) / width, (y - 1) / height);
const float2 topRightCoordinate = float2((x + 1) / width, (y - 1) / height);
const float2 bottomLeftCoordinate = float2((x - 1) / width, (y + 1) / height);
const float2 bottomRightCoordinate = float2((x + 1) / width, (y + 1) / height);
const half leftIntensity = inputTexture.sample(quadSampler, leftCoordinate).r;
const half rightIntensity = inputTexture.sample(quadSampler, rightCoordinate).r;
const half topIntensity = inputTexture.sample(quadSampler, topCoordinate).r;
const half bottomIntensity = inputTexture.sample(quadSampler, bottomCoordinate).r;
const half topLeftIntensity = inputTexture.sample(quadSampler, topLeftCoordinate).r;
const half topRightIntensity = inputTexture.sample(quadSampler, topRightCoordinate).r;
const half bottomLeftIntensity = inputTexture.sample(quadSampler, bottomLeftCoordinate).r;
const half bottomRightIntensity = inputTexture.sample(quadSampler, bottomRightCoordinate).r;
half h = -topLeftIntensity - 2.0h * topIntensity - topRightIntensity + bottomLeftIntensity + 2.0h * bottomIntensity + bottomRightIntensity;
h = max(0.0h, h);
half v = -bottomLeftIntensity - 2.0h * leftIntensity - topLeftIntensity + bottomRightIntensity + 2.0h * rightIntensity + topRightIntensity;
v = max(0.0h, v);
half mag = length(half2(h, v)) * half(*edgeStrength);
mag = 1.0h - step(half(*threshold), mag);
const half4 outColor = half4(half3(mag), 1.0h);
outputTexture.write(outColor, grid);
}
Harbeth功能清单
支持ios系统和macOS系统支持运算符函数式操作支持多种模式数据源 UIImage, CIImage, CGImage, CMSampleBuffer, CVPixelBuffer.支持快速设计滤镜支持合并多种滤镜效果支持输出源的快速扩展支持相机采集特效支持视频添加滤镜特效支持矩阵卷积支持使用系统 MetalPerformanceShaders.支持兼容 CoreImage.滤镜部分大致分为以下几个模块：
Blend：图像融合技术 Blur：模糊效果 Pixel：图像的基本像素颜色处理 Effect：效果处理 Lookup：查找表过滤器 Matrix: 矩阵卷积滤波器 Shape：图像形状大小相关 Visual: 视觉动态特效 MPS: 系统 MetalPerformanceShaders.
最后
慢慢再补充其他相关滤镜，喜欢就给我点个星吧。滤镜Demo地址，目前包含100+种滤镜，同时也支持CoreImage混合使用。再附上一个开发加速库KJCategoriesDemo地址再附上一个网络基础库RxNetworksDemo地址喜欢的老板们可以点个星，谢谢各位老板！！！
✌️.
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