Merge "Tweak Kawase2 to use fewer passes and fewer samples." into main

void KawaseBlurDualFilter::blurInto(const sk_sp<SkSurface>& drawSurface, sk_sp<SkShader> input,

                                    const float inverseScale, const float radius,

                                    const float alpha) const {

    SkPaint paint;

    if (radius == 0) {

        paint.setShader(std::move(input));

        paint.setAlphaf(alpha);

    } else {

        SkRuntimeShaderBuilder blurBuilder(mBlurEffect);

        blurBuilder.child("child") = std::move(input);

    blurBuilder.uniform("in_inverseScale") = inverseScale;

        blurBuilder.uniform("in_blurOffset") = radius;

        blurBuilder.uniform("in_crossFade") = alpha;

    SkPaint paint;

        paint.setShader(blurBuilder.makeShader(nullptr));

    }

    paint.setBlendMode(alpha == 1.0f ? SkBlendMode::kSrc : SkBlendMode::kSrcOver);

    drawSurface->getCanvas()->drawPaint(paint);

}

    // Use a variable number of blur passes depending on the radius. The non-integer part of this

    // calculation is used to mix the final pass into the second-last with an alpha blend.

    constexpr int kMaxSurfaces = 4;

    const float filterDepth =

            std::min(kMaxSurfaces - 1.0f, 1.0f + std::max(0.0f, log2f(radius * kInputScale)));

    constexpr int kMaxSurfaces = 3;

    const float filterDepth = std::min(kMaxSurfaces - 1.0f, radius * kInputScale / 2.5f);

    const int filterPasses = std::min(kMaxSurfaces - 1, static_cast<int>(ceil(filterDepth)));

    // Render into surfaces downscaled by 1x, 1x, 2x, and 4x from the initial downscale.

    // Render into surfaces downscaled by 1x, 2x, and 4x from the initial downscale.

    sk_sp<SkSurface> surfaces[kMaxSurfaces] =

            {filterPasses >= 0 ? makeSurface(context, blurRect, 1 * kInverseInputScale) : nullptr,

             filterPasses >= 1 ? makeSurface(context, blurRect, 1 * kInverseInputScale) : nullptr,

             filterPasses >= 2 ? makeSurface(context, blurRect, 2 * kInverseInputScale) : nullptr,

             filterPasses >= 3 ? makeSurface(context, blurRect, 4 * kInverseInputScale) : nullptr};

    // These weights for scaling offsets per-pass are handpicked to look good at 1 <= radius <= 600.

    static const float kWeights[7] = {1.0f, 2.0f, 3.5f, 1.0f, 2.0f, 2.0f, 2.0f};

             filterPasses >= 1 ? makeSurface(context, blurRect, 2 * kInverseInputScale) : nullptr,

             filterPasses >= 2 ? makeSurface(context, blurRect, 4 * kInverseInputScale) : nullptr};

    // These weights for scaling offsets per-pass are handpicked to look good at 1 <= radius <= 250.

    static const float kWeights[5] = {

            1.0f, // 1st downsampling pass

            1.0f, // 2nd downsampling pass

            1.0f, // 3rd downsampling pass

            0.0f, // 1st upscaling pass. Set to zero to upscale without blurring for performance.

            1.0f, // 2nd upscaling pass

    };

    // Kawase is an approximation of Gaussian, but behaves differently because it is made up of many

    // simpler blurs. A transformation is required to approximate the same effect as Gaussian.

    float sumSquaredR = powf(kWeights[0] * powf(2.0f, 1), 2.0f);

    float sumSquaredR = powf(kWeights[0], 2.0f);

    for (int i = 0; i < filterPasses; i++) {

        const float alpha = std::min(1.0f, filterDepth - i);

        sumSquaredR += powf(powf(2.0f, i + 1) * alpha * kWeights[1 + i], 2.0f);

        sumSquaredR += powf(powf(2.0f, i + 1) * alpha * kWeights[6 - i], 2.0f);

        sumSquaredR += powf(powf(2.0f, i) * alpha * kWeights[1 + i] / kInputScale, 2.0f);

        sumSquaredR += powf(powf(2.0f, i + 1) * alpha * kWeights[4 - i] / kInputScale, 2.0f);

    }

    // Solve for R = sqrt(sum(r_i^2)). Divide R by hypot(1,1) to find some (x,y) offsets.

    const float step = M_SQRT1_2 *

            sqrtf(max(0.0f, (powf(radius, 2.0f) - powf(kInverseInputScale, 2.0f)) / sumSquaredR));

    // Solve for R = sqrt(sum(r_i^2)).

    const float step = radius * sqrt(1.0f / sumSquaredR);

    // Start by downscaling and doing the first blur pass.

    {

    }

    // Finally blur+upscale back to our original size.

    for (int i = filterPasses - 1; i >= 0; i--) {

        blurInto(surfaces[i], surfaces[i + 1]->makeImageSnapshot(), kWeights[6 - i] * step,

        blurInto(surfaces[i], surfaces[i + 1]->makeImageSnapshot(), kWeights[4 - i] * step,

                 std::min(1.0f, filterDepth - i));

    }

    return surfaces[0]->makeImageSnapshot();