//------------------变形方法和其辅助函数 End-----------------------------------------
// 三种变形的并行版本
// 变换思路和代码基本同前，只将为目标图每个格点赋像素值的步骤进行并行，即每个格点同时
// 计算其在原图中对应的坐标，并查找像素信息
// 故只将串行的两重for，转换为并行的循环
public static byte[,,] RotateTwistImgParallel(byte[,,] img, InterpolationFunc interpolationFunc,
double maxAngle, double radius,
double centerX, double centerY)
{
int height = img.GetLength(0);
int width = img.GetLength(1);
byte[,,] imgTwisted = new byte[height, width, img.GetLength(2)];
System.Threading.Tasks.Parallel.For(0, height * width, index => {
int i = index / width;
int j = index % width;
double distance = Math.Sqrt((i - centerX) * (i - centerX) + (j - centerY) * (j - centerY));
if (distance > radius)
{
for (int channel = 0; channel < 3; channel++)
{
imgTwisted[i, j, channel] = img[i, j, channel];
}
return;
}
double angle = maxAngle * (radius - distance) / radius;
double x = Math.Cos(angle) * (i - centerX) - Math.Sin(angle) * (j - centerY) + centerX;
double y = Math.Sin(angle) * (i - centerX) + Math.Cos(angle) * (j - centerY) + centerY;
for (int channel = 0; channel < 3; channel++)
{
imgTwisted[i, j, channel] = interpolationFunc(img, x, y, channel);
}
});
return(imgTwisted);
}
//------------------插值方法 End-----------------------------------------
// 变形方法 参数格式byte[,,]img, InterpolationFunc interpolationFunc, 其他变形相关参数 返回值byte[,,]
// maxAngle弧度制，在前端中，为了用户友好，规定写入角度值，并且由前端完成角度弧度转换这样的简单逻辑
public static byte[,,] RotateTwistImg(byte[,,] img, InterpolationFunc interpolationFunc,
double maxAngle, double radius,
double centerX, double centerY)
{
int height = img.GetLength(0);
int width = img.GetLength(1);
byte[,,] imgTwisted = new byte[height, width, img.GetLength(2)];
for (int i = 0; i < height; i++)
{
for (int j = 0; j < width; j++)
{
// 按照变化公式，计算目标图(i,j)应到原图哪个位置取像素信息
double distance = Math.Sqrt((i - centerX) * (i - centerX) + (j - centerY) * (j - centerY));
if (distance > radius)
{
for (int channel = 0; channel < 3; channel++)
{
imgTwisted[i, j, channel] = img[i, j, channel];
}
continue;
}
// 原始公式 angle = maxAngle * (radius - distance) / radius， 化简防止radius distance差距过大大数吃小数
double angle = maxAngle * (1 - distance / radius);
double x = Math.Cos(angle) * (i - centerX) - Math.Sin(angle) * (j - centerY) + centerX;
double y = Math.Sin(angle) * (i - centerX) + Math.Cos(angle) * (j - centerY) + centerY;
for (int channel = 0; channel < 3; channel++)
{
imgTwisted[i, j, channel] = interpolationFunc(img, x, y, channel);
}
}
}
return(imgTwisted);
}
public TransformBindable(Bindable <TValue> targetBindable, InterpolationFunc <TValue> interpolationFunc)
{
this.targetBindable = targetBindable;
this.interpolationFunc = interpolationFunc ?? Interpolation <TValue> .ValueAt;
TargetMember = $"{targetBindable.GetHashCode()}.Value";
}
static GenericInterpolation()
{
const string interpolation_method = nameof(GenericInterpolation <TEasing> .ValueAt);
var parameters = typeof(InterpolationFunc <TValue, TEasing>)
.GetMethod(nameof(InterpolationFunc <TValue, TEasing> .Invoke))
?.GetParameters().Select(p => p.ParameterType).ToArray();
MethodInfo valueAtMethod = typeof(GenericInterpolation <TEasing>).GetMethod(interpolation_method, parameters);
if (valueAtMethod != null)
{
FUNCTION = (InterpolationFunc <TValue, TEasing>)valueAtMethod.CreateDelegate(typeof(InterpolationFunc <TValue, TEasing>));
}
else
{
var typeRef = FormatterServices.GetSafeUninitializedObject(typeof(TValue)) as IInterpolable <TValue>;
if (typeRef == null)
{
throw new NotSupportedException($"Type {typeof(TValue)} has no interpolation function. Implement the interface {typeof(IInterpolable<TValue>)} interface on the object.");
}
FUNCTION = typeRef.ValueAt;
}
}
public TransformBindable(Bindable <TValue> targetBindable)
{
this.targetBindable = targetBindable;
interpolationFunc = Interpolation.ValueAt;
TargetMember = $"{targetBindable.GetHashCode()}.Value";
}
/// <summary>
/// Creates a new instance operating on a property or field of <typeparamref name="T"/>. The property or field is
/// denoted by its name, passed as <paramref name="propertyOrFieldName"/>.
/// By default, an interpolation method "ValueAt" from <see cref="Interpolation"/> with suitable signature is
/// picked for interpolating between <see cref="Transform{TValue}.StartValue"/> and
/// <see cref="Transform{TValue}.EndValue"/> according to <see cref="Transform.StartTime"/>,
/// <see cref="Transform.EndTime"/>, and a current time.
/// </summary>
/// <param name="propertyOrFieldName">The property or field name to be operated upon.</param>
public TransformCustom(string propertyOrFieldName)
{
TargetMember = propertyOrFieldName;
accessor = getAccessor(propertyOrFieldName);
Trace.Assert(accessor.Read != null && accessor.Write != null, $"Failed to populate {nameof(accessor)}.");
interpolationFunc = Interpolation.ValueAt;
}
static TransformCustom()
{
interpolation_func =
(InterpolationFunc<TValue>)typeof(Interpolation).GetMethod(
nameof(Interpolation.ValueAt),
typeof(InterpolationFunc<TValue>)
.GetMethod(nameof(InterpolationFunc<TValue>.Invoke))
.GetParameters().Select(p => p.ParameterType).ToArray()
)?.CreateDelegate(typeof(InterpolationFunc<TValue>));
}
public TransformBindable(Bindable <TValue> targetBindable)
{
this.targetBindable = targetBindable;
// Lambda expression is used so that the delegate is cached (see: https://github.com/dotnet/roslyn/issues/5835)
interpolationFunc = (double d, TValue value, TValue tValue, double time, double endTime, in TEasing type)
=> Interpolation.ValueAt(d, value, tValue, time, endTime, in type);
TargetMember = $"{targetBindable.GetHashCode()}.Value";
}
/// <summary>
/// Creates a new instance operating on a property or field of <typeparamref name="T"/>. The property or field is
/// denoted by its name, passed as <paramref name="propertyOrFieldName"/>.
/// By default, an interpolation method "ValueAt" from <see cref="Interpolation"/> with suitable signature is
/// picked for interpolating between <see cref="Transform{TValue}.StartValue"/> and
/// <see cref="Transform{TValue}.EndValue"/> according to <see cref="Transform.StartTime"/>,
/// <see cref="Transform.EndTime"/>, and a current time.
/// </summary>
/// <param name="propertyOrFieldName">The property or field name to be operated upon.</param>
public TransformCustom(string propertyOrFieldName)
{
TargetMember = propertyOrFieldName;
accessor = getAccessor(propertyOrFieldName);
Trace.Assert(accessor.Read != null && accessor.Write != null, $"Failed to populate {nameof(accessor)}.");
// Lambda expression is used so that the delegate is cached (see: https://github.com/dotnet/roslyn/issues/5835)
interpolationFunc = (double d, TValue value, TValue tValue, double time, double endTime, in TEasing type)
=> Interpolation.ValueAt(d, value, tValue, time, endTime, in type);
}
/// <summary>
/// Creates a new instance operating on a property or field of <see cref="T"/>. The property or field is
/// denoted by its name, passed as <paramref name="propertyOrFieldName"/>.
/// By default, an interpolation method "ValueAt" from <see cref="Interpolation"/> with suitable signature is
/// picked for interpolating between <see cref="Transform{TValue}.StartValue"/> and
/// <see cref="Transform{TValue}.EndValue"/> according to <see cref="Transform.StartTime"/>,
/// <see cref="Transform.EndTime"/>, and a current time.
/// Optionally, or when no suitable "ValueAt" from <see cref="Interpolation"/> exists, a custom function can be supplied
/// via <paramref name="interpolationFunc"/>.
/// </summary>
/// <param name="propertyOrFieldName">The property or field name to be operated upon.</param>
/// <param name="interpolationFunc">
/// The function to be used for interpolating between <see cref="Transform{TValue}.StartValue"/> and
/// <see cref="Transform{TValue}.EndValue"/> according to <see cref="Transform.StartTime"/>,
/// <see cref="Transform.EndTime"/>, and a current time.
/// If null, an interpolation method "ValueAt" from <see cref="Interpolation"/> with a suitable signature is picked.
/// If none exists, then this parameter must not be null.
/// </param>
public TransformCustom(string propertyOrFieldName, InterpolationFunc<TValue> interpolationFunc = null)
{
TargetMember = propertyOrFieldName;
accessor = getAccessor(propertyOrFieldName);
Trace.Assert(accessor.Read != null && accessor.Write != null, $"Failed to populate {nameof(accessor)}.");
this.interpolationFunc = interpolationFunc ?? interpolation_func;
if (this.interpolationFunc == null)
throw new InvalidOperationException(
$"Need to pass a custom {nameof(interpolationFunc)} since no default {nameof(Interpolation)}.{nameof(Interpolation.ValueAt)} exists.");
}
public static void DrawCatmullPath(List<Transform> points, InterpolationFunc sampler, int samples)
{
if (!PreDrawPath(points, 4))
return;
float sampleInterval = 1.0f / (float)samples;
int p0, p1, p2, p3;
for (int i = 0; i < points.Count; ++i)
{
p1 = i;
p0 = p1 - 1;
if (p0 < 0)
p0 = points.Count - 1;
p2 = p1 + 1;
if (p2 >= points.Count)
p2 = 0;
p3 = p2 + 1;
if (p3 >= points.Count)
p3 = 0;
Vector3 sample, prevSample;
prevSample = points[p1].position;
for (int j = 1; j <= samples; ++j)
{
float t = j * sampleInterval;
sample = sampler(points[p0].position,
points[p1].position,
points[p2].position,
points[p3].position, t);
Handles.DrawLine(prevSample, sample);
prevSample = sample;
}
}
}
public static byte[,,] TPSImgParallel(byte[,,] img, InterpolationFunc interpolationFunc,
double[,] pointPair)
{
// 置矩阵，高斯消元解系数同串行版本
if (pointPair.GetLength(1) != 4)
{
return(null); // Error pointPair
}
int pointNumber = pointPair.GetLength(0);
double[,] Y = new double[pointNumber + 3, 2];
for (var i = 0; i < pointNumber; i++)
{
Y[i, 0] = pointPair[i, 2];
Y[i, 1] = pointPair[i, 3];
}
double[,] L = new double[pointNumber + 3, pointNumber + 3];
for (var j = 0; j < pointNumber; j++)
{
L[pointNumber, j] = 1;
L[j, pointNumber] = 1;
}
for (var i = pointNumber + 1; i < pointNumber + 3; i++)
{
for (var j = 0; j < pointNumber; j++)
{
L[i, j] = pointPair[j, i - pointNumber - 1];
L[j, i] = L[i, j];
}
}
for (var i = 0; i < pointNumber; i++)
{
for (var j = 0; j <= i; j++)
{
if (j == i)
{
L[i, j] = 0;
break;
}
L[i, j] = RadialbasisByPoint(pointPair[i, 0], pointPair[i, 1], pointPair[j, 0], pointPair[j, 1]);
L[j, i] = L[i, j];
}
}
// 传入高斯消元函数的为引用，会被函数体修改矩阵值，原本应使用
// double[,] coe = GaussianElimination(L.Clone(), Y.Clone());
// 但LY不再使用，故为节约耗时，不clone
double[,] coe = GaussianElimination(L, Y);
if (coe == null)
{
return(null);
}
// 以下开始并行
int height = img.GetLength(0);
int width = img.GetLength(1);
byte[,,] imgTPSed = new byte[height, width, 3];
System.Threading.Tasks.Parallel.For(0, height * width, index => {
double x;
double y;
int i = index / width;
int j = index % width;
x = coe[pointNumber, 0] + coe[pointNumber + 1, 0] * i + coe[pointNumber + 2, 0] * j;
y = coe[pointNumber, 1] + coe[pointNumber + 1, 1] * i + coe[pointNumber + 2, 1] * j;
double[,] weightedUArray = new double[pointNumber, 4]; // 分正负相消累计，防止大数吃小数
double u;
double weightedUX;
double weightedUY;
int posUXcount = 0;
int negUXcount = 0;
int posUYcount = 0;
int negUYcount = 0;
for (var wCount = 0; wCount < pointNumber; wCount++)
{
u = RadialbasisByPoint(i, j, pointPair[wCount, 0], pointPair[wCount, 1]);
weightedUX = u * coe[wCount, 0];
weightedUY = u * coe[wCount, 1];
if (weightedUX > 0)
{
weightedUArray[posUXcount, 0] = weightedUX;
posUXcount++;
}
else
{
weightedUArray[negUXcount, 1] = weightedUX;
negUXcount++;
}
if (weightedUY > 0)
{
weightedUArray[posUYcount, 2] = weightedUY;
posUYcount++;
}
else
{
weightedUArray[negUYcount, 3] = weightedUY;
negUYcount++;
}
}
posUXcount--; posUYcount--; negUXcount--; negUYcount--;
while (posUXcount >= 0 && negUXcount >= 0)
{
if (x > 0)
{
x += weightedUArray[negUXcount, 1];
negUXcount--;
}
else
{
x += weightedUArray[posUXcount, 0];
posUXcount--;
}
}
while (posUXcount >= 0)
{
x += weightedUArray[posUXcount, 0];
posUXcount--;
}
while (negUXcount >= 0)
{
x += weightedUArray[negUXcount, 1];
negUXcount--;
}
while (posUYcount >= 0 && negUYcount >= 0)
{
if (y > 0)
{
y += weightedUArray[negUYcount, 3];
negUYcount--;
}
else
{
y += weightedUArray[posUYcount, 2];
posUYcount--;
}
}
while (posUYcount >= 0)
{
y += weightedUArray[posUYcount, 2];
posUYcount--;
}
while (negUYcount >= 0)
{
y += weightedUArray[negUYcount, 3];
negUYcount--;
}
if (x < 0 || x >= height || y < 0 || y > width)
{
return;
}
for (var channel = 0; channel < 3; channel++)
{
imgTPSed[i, j, channel] = interpolationFunc(img, x, y, channel);
}
});
return(imgTPSed);
}
public static byte[,,] DistortImgParallel(byte[,,] img, InterpolationFunc interpolationFunc,
double radius,
double centerX, double centerY,
bool isAdjustPillowDistort)
{
int height = img.GetLength(0);
int width = img.GetLength(1);
byte[,,] imgDistorted = new byte[height, width, img.GetLength(2)];
if (isAdjustPillowDistort) // 校正枕形畸变，即对图像做桶形畸变
{
System.Threading.Tasks.Parallel.For(0, height * width, index => {
int i = index / width;
int j = index % width;
double distance = Math.Sqrt((i - centerX) * (i - centerX) + (j - centerY) * (j - centerY));
if (distance > radius)
{
return; // 投影球外的点，置为黑 0,0,0，即默认值
}
double k;
if (distance / radius < 0.001)
{
k = 1; // k 极小时
}
else
{
k = radius / distance * Math.Asin(distance / radius);
}
// 为了精确快速调整计算顺序，把原始公式在注释给出
double x = k * i + (1 - k) * centerX; // 原始公式 k * (i - centerX) + centerX
double y = k * j + (1 - k) * centerY; // 原始公式 k * (i - centerX) + centerX
if (x >= height || x < 0 || y >= width || y < 0)
{
return;
}
for (int channel = 0; channel < 3; channel++)
{
imgDistorted[i, j, channel] = interpolationFunc(img, x, y, channel);
}
});
}
else // 校正桶形畸变，即对图像做枕形畸变
{
System.Threading.Tasks.Parallel.For(0, height * width, index => {
int i = index / width;
int j = index % width;
double distance = Math.Sqrt((i - centerX) * (i - centerX) + (j - centerY) * (j - centerY));
if (distance > Math.PI / 2 * radius)
{
return; // 投影球外的点，置为黑 0,0,0，即默认值
}
double k;
if (distance / radius < 0.001)
{
k = 1; // k 极小时
}
else
{
k = Math.Sin(distance / radius) * radius / distance;
}
// 为了精确快速调整计算顺序，把原始公式在注释给出
double x = k * i + (1 - k) * centerX; // 原始公式 k * (i - centerX) + centerX
double y = k * j + (1 - k) * centerY; // 原始公式 k * (i - centerX) + centerX
if (x >= height || x < 0 || y >= width || y < 0)
{
return;
}
for (int channel = 0; channel < 3; channel++)
{
imgDistorted[i, j, channel] = interpolationFunc(img, x, y, channel);
}
});
}
return(imgDistorted);
}
// pointPair[i,0] ~ [i,3] 分别为 控制点x1 控制点y1 目标点x2 目标点y2，控制点：想变成的参考样貌；目标点：待变形图上的坐标
public static byte[,,] TPSImg(byte[,,] img, InterpolationFunc interpolationFunc,
double[,] pointPair)
{
if (pointPair.GetLength(1) != 4)
{
return(null); // Error pointPair
}
int pointNumber = pointPair.GetLength(0);
// 构造矩阵Y
double[,] Y = new double[pointNumber + 3, 2];
for (var i = 0; i < pointNumber; i++)
{
Y[i, 0] = pointPair[i, 2];
Y[i, 1] = pointPair[i, 3];
}
// 构造矩阵L，注意到L为对称阵，赋值时，循环体可以在第二重循环时减半循环量
double[,] L = new double[pointNumber + 3, pointNumber + 3];
for (var j = 0; j < pointNumber; j++)
{
L[pointNumber, j] = 1;
L[j, pointNumber] = 1;
}
for (var i = pointNumber + 1; i < pointNumber + 3; i++)
{
for (var j = 0; j < pointNumber; j++)
{
L[i, j] = pointPair[j, i - pointNumber - 1];
L[j, i] = L[i, j];
}
}
for (var i = 0; i < pointNumber; i++)
{
for (var j = 0; j <= i; j++)
{
if (j == i)
{
L[i, j] = 0;
break;
}
L[i, j] = RadialbasisByPoint(pointPair[i, 0], pointPair[i, 1], pointPair[j, 0], pointPair[j, 1]);
L[j, i] = L[i, j];
}
}
// 传入高斯消元函数的为引用，会被函数体修改矩阵值，原本应使用
// double[,] coe = GaussianElimination(L.Clone(), Y.Clone());
// 但LY不再使用，故为节约耗时，不clone
double[,] coe = GaussianElimination(L, Y);
if (coe == null)
{
return(null); // 方程无解，返回空图
}
int height = img.GetLength(0);
int width = img.GetLength(1);
byte[,,] imgTPSed = new byte[height, width, 3];
double x;
double y;
for (var i = 0; i < height; i++)
{
for (var j = 0; j < width; j++)
{
// 先计算 wU之外的项目
x = coe[pointNumber, 0] + coe[pointNumber + 1, 0] * i + coe[pointNumber + 2, 0] * j;
y = coe[pointNumber, 1] + coe[pointNumber + 1, 1] * i + coe[pointNumber + 2, 1] * j;
// 分别计算各wU的结果，按正负号存入数组中，累加时，
// 保证xy和新作为加项的wU正负异号
// 则整体加法流程充分地让正负相消累计，每一步得到的数的绝对值较小，
// 防止double型在位数提高时新引入舍入误差
double[,] weightedUArray = new double[pointNumber, 4];
double u;
double weightedUX;
double weightedUY;
int posUXcount = 0;
int negUXcount = 0;
int posUYcount = 0;
int negUYcount = 0;
// 计算wU并按正负号存储
for (var wCount = 0; wCount < pointNumber; wCount++)
{
u = RadialbasisByPoint(i, j, pointPair[wCount, 0], pointPair[wCount, 1]);
weightedUX = u * coe[wCount, 0];
weightedUY = u * coe[wCount, 1];
if (weightedUX > 0)
{
weightedUArray[posUXcount, 0] = weightedUX;
posUXcount++;
}
else
{
weightedUArray[negUXcount, 1] = weightedUX;
negUXcount++;
}
if (weightedUY > 0)
{
weightedUArray[posUYcount, 2] = weightedUY;
posUYcount++;
}
else
{
weightedUArray[negUYcount, 3] = weightedUY;
negUYcount++;
}
}
posUXcount--; posUYcount--; negUXcount--; negUYcount--;
// 分正负，尽可能异号累加得到x
while (posUXcount >= 0 && negUXcount >= 0)
{
if (x > 0)
{
x += weightedUArray[negUXcount, 1];
negUXcount--;
}
else
{
x += weightedUArray[posUXcount, 0];
posUXcount--;
}
}
while (posUXcount >= 0)
{
x += weightedUArray[posUXcount, 0];
posUXcount--;
}
while (negUXcount >= 0)
{
x += weightedUArray[negUXcount, 1];
negUXcount--;
}
// 分正负，尽可能异号累加得到y
while (posUYcount >= 0 && negUYcount >= 0)
{
if (y > 0)
{
y += weightedUArray[negUYcount, 3];
negUYcount--;
}
else
{
y += weightedUArray[posUYcount, 2];
posUYcount--;
}
}
while (posUYcount >= 0)
{
y += weightedUArray[posUYcount, 2];
posUYcount--;
}
while (negUYcount >= 0)
{
y += weightedUArray[negUYcount, 3];
negUYcount--;
}
// 得到对应坐标点，到原图中查找像素信息
if (x < 0 || x >= height || y < 0 || y > width)
{
continue;
}
for (var channel = 0; channel < 3; channel++)
{
imgTPSed[i, j, channel] = interpolationFunc(img, x, y, channel);
}
}
}
return(imgTPSed);
}
/// <summary>
/// Smoothly adjusts the value of a <see cref="Bindable{TValue}"/> over time.
/// </summary>
/// <returns>A <see cref="TransformSequence{T}"/> to which further transforms can be added.</returns>
public static TransformSequence <T> TransformBindableTo <T, TValue>(this T drawable, [NotNull] Bindable <TValue> bindable, TValue newValue, double duration = 0, Easing easing = Easing.None,
InterpolationFunc <TValue> interpolationFunc = null)
where T : ITransformable =>
drawable.TransformTo(drawable.PopulateTransform(new TransformBindable <TValue, T>(bindable, interpolationFunc), newValue, duration, easing));
/// <summary>
/// Smoothly adjusts the value of a <see cref="Bindable{TValue}"/> over time.
/// </summary>
/// <returns>A <see cref="TransformSequence{T}"/> to which further transforms can be added.</returns>
public static TransformSequence <T> TransformBindableTo <T, TValue>(this TransformSequence <T> t, [NotNull] Bindable <TValue> bindable, TValue newValue, double duration = 0, Easing easing = Easing.None,
InterpolationFunc <TValue> interpolationFunc = null)
where T : ITransformable =>
t.Append(o => o.TransformBindableTo(bindable, newValue, duration, easing, interpolationFunc));
