Blur.cpp

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// Copyright (c) 2008-2019 OpenShot Studios, LLC
//
// SPDX-License-Identifier: LGPL-3.0-or-later
 
#include "Blur.h"
#include "Exceptions.h"
 
using namespace openshot;
 
Blur::Blur() : horizontal_radius(6.0), vertical_radius(6.0), sigma(3.0), iterations(3.0),
    mask_mode(BLUR_MASK_POST_BLEND) {
    // Init effect properties
    init_effect_details();
}
 
// Default constructor
Blur::Blur(Keyframe new_horizontal_radius, Keyframe new_vertical_radius, Keyframe new_sigma, Keyframe new_iterations) :
        horizontal_radius(new_horizontal_radius), vertical_radius(new_vertical_radius),
        sigma(new_sigma), iterations(new_iterations), mask_mode(BLUR_MASK_POST_BLEND)
{
    // Init effect properties
    init_effect_details();
}
 
// Init effect settings
void Blur::init_effect_details()
{
    InitEffectInfo();
 
    info.class_name = "Blur";
    info.name = "Blur";
    info.description = "Adjust the blur of the frame's image.";
    info.has_audio = false;
    info.has_video = true;
}
 
// This method is required for all derived classes of EffectBase, and returns a
// modified openshot::Frame object
std::shared_ptr<openshot::Frame> Blur::GetFrame(std::shared_ptr<openshot::Frame> frame, int64_t frame_number)
{
    // Get the frame's image
    std::shared_ptr<QImage> frame_image = frame->GetImage();
 
    // Get the current blur radius
    int horizontal_radius_value = horizontal_radius.GetValue(frame_number);
    int vertical_radius_value = vertical_radius.GetValue(frame_number);
    float sigma_value = sigma.GetValue(frame_number);
    int iteration_value = iterations.GetInt(frame_number);
    (void) sigma_value;
 
    int w = frame_image->width();
    int h = frame_image->height();
 
    // Grab two copies of the image pixel data
    QImage image_copy = frame_image->copy();
    std::shared_ptr<QImage> frame_image_2 = std::make_shared<QImage>(image_copy);
 
    // Loop through each iteration
    for (int iteration = 0; iteration < iteration_value; ++iteration)
    {
        // HORIZONTAL BLUR (if any)
        if (horizontal_radius_value > 0.0) {
            // Apply horizontal blur to target RGBA channels
            boxBlurH(frame_image->bits(), frame_image_2->bits(), w, h, horizontal_radius_value);
 
            // Swap output image back to input
            frame_image.swap(frame_image_2);
        }
 
        // VERTICAL BLUR (if any)
        if (vertical_radius_value > 0.0) {
            // Apply vertical blur to target RGBA channels
            boxBlurT(frame_image->bits(), frame_image_2->bits(), w, h, vertical_radius_value);
 
            // Swap output image back to input
            frame_image.swap(frame_image_2);
        }
    }
 
    // return the modified frame
    return frame;
}
 
bool Blur::UseCustomMaskBlend(int64_t frame_number) const {
    (void) frame_number;
    return mask_mode == BLUR_MASK_DRIVE_AMOUNT;
}
 
void Blur::ApplyCustomMaskBlend(std::shared_ptr<QImage> original_image, std::shared_ptr<QImage> effected_image,
                                std::shared_ptr<QImage> mask_image, int64_t frame_number) const {
    (void) frame_number;
    if (!original_image || !effected_image || !mask_image)
        return;
    if (original_image->size() != effected_image->size() || effected_image->size() != mask_image->size())
        return;
 
    unsigned char* original_pixels = reinterpret_cast<unsigned char*>(original_image->bits());
    unsigned char* effected_pixels = reinterpret_cast<unsigned char*>(effected_image->bits());
    unsigned char* mask_pixels = reinterpret_cast<unsigned char*>(mask_image->bits());
    const int pixel_count = effected_image->width() * effected_image->height();
 
    #pragma omp parallel for schedule(static)
    for (int i = 0; i < pixel_count; ++i) {
        const int idx = i * 4;
        float factor = static_cast<float>(qGray(mask_pixels[idx], mask_pixels[idx + 1], mask_pixels[idx + 2])) / 255.0f;
        if (mask_invert)
            factor = 1.0f - factor;
        // Use a non-linear response curve for custom blur drive mode.
        factor = factor * factor;
        const float inverse = 1.0f - factor;
 
        // Drive blur amount with the grayscale mask while preserving source alpha.
        effected_pixels[idx] = static_cast<unsigned char>(
            (original_pixels[idx] * inverse) + (effected_pixels[idx] * factor));
        effected_pixels[idx + 1] = static_cast<unsigned char>(
            (original_pixels[idx + 1] * inverse) + (effected_pixels[idx + 1] * factor));
        effected_pixels[idx + 2] = static_cast<unsigned char>(
            (original_pixels[idx + 2] * inverse) + (effected_pixels[idx + 2] * factor));
        effected_pixels[idx + 3] = original_pixels[idx + 3];
    }
}
 
// Credit: http://blog.ivank.net/fastest-gaussian-blur.html (MIT License)
// Modified to process all four channels in a pixel array
void Blur::boxBlurH(unsigned char *scl, unsigned char *tcl, int w, int h, int r) {
    const float iarr = 1.0f / (r + r + 1);
 
    #pragma omp parallel for shared(scl, tcl)
    for (int i = 0; i < h; ++i) {
        const unsigned char* src = scl + i * w * 4;
        unsigned char* dst = tcl + i * w * 4;
 
        const unsigned char* first = src;
        const unsigned char* last  = src + (w - 1) * 4;
 
        int val[4];
        for (int c = 0; c < 4; ++c)
            val[c] = (r + 1) * first[c];
        for (int j = 0; j < r; ++j) {
            const unsigned char* p = src + j * 4;
            for (int c = 0; c < 4; ++c)
                val[c] += p[c];
        }
 
        int li = 0, ri = r;
        for (int j = 0; j <= r; ++j, ++ri) {
            const unsigned char* add = src + ri * 4;
            unsigned char* out = dst + j * 4;
            for (int c = 0; c < 4; ++c) {
                val[c] += add[c] - first[c];
                out[c] = (unsigned char)(val[c] * iarr + 0.5f);
            }
        }
        for (int j = r + 1; j < w - r; ++j, ++li, ++ri) {
            const unsigned char* add = src + ri * 4;
            const unsigned char* sub = src + li * 4;
            unsigned char* out = dst + j * 4;
            for (int c = 0; c < 4; ++c) {
                val[c] += add[c] - sub[c];
                out[c] = (unsigned char)(val[c] * iarr + 0.5f);
            }
        }
        for (int j = w - r; j < w; ++j, ++li) {
            const unsigned char* sub = src + li * 4;
            unsigned char* out = dst + j * 4;
            for (int c = 0; c < 4; ++c) {
                val[c] += last[c] - sub[c];
                out[c] = (unsigned char)(val[c] * iarr + 0.5f);
            }
        }
    }
}
 
void Blur::boxBlurT(unsigned char *scl, unsigned char *tcl, int w, int h, int r) {
    const float iarr = 1.0f / (r + r + 1);
    const int stride = w * 4;
 
    #pragma omp parallel for shared(scl, tcl)
    for (int i = 0; i < w; ++i) {
        const unsigned char* col_src = scl + i * 4;
        unsigned char* col_dst = tcl + i * 4;
 
        const unsigned char* first = col_src;
        const unsigned char* last  = col_src + (h - 1) * stride;
 
        int val[4];
        for (int c = 0; c < 4; ++c)
            val[c] = (r + 1) * first[c];
        for (int j = 0; j < r; ++j) {
            const unsigned char* p = col_src + j * stride;
            for (int c = 0; c < 4; ++c)
                val[c] += p[c];
        }
 
        int li = 0, ri = r;
        for (int j = 0; j <= r; ++j, ++ri) {
            const unsigned char* add = col_src + ri * stride;
            unsigned char* out = col_dst + j * stride;
            for (int c = 0; c < 4; ++c) {
                val[c] += add[c] - first[c];
                out[c] = (unsigned char)(val[c] * iarr + 0.5f);
            }
        }
        for (int j = r + 1; j < h - r; ++j, ++li, ++ri) {
            const unsigned char* add = col_src + ri * stride;
            const unsigned char* sub = col_src + li * stride;
            unsigned char* out = col_dst + j * stride;
            for (int c = 0; c < 4; ++c) {
                val[c] += add[c] - sub[c];
                out[c] = (unsigned char)(val[c] * iarr + 0.5f);
            }
        }
        for (int j = h - r; j < h; ++j, ++li) {
            const unsigned char* sub = col_src + li * stride;
            unsigned char* out = col_dst + j * stride;
            for (int c = 0; c < 4; ++c) {
                val[c] += last[c] - sub[c];
                out[c] = (unsigned char)(val[c] * iarr + 0.5f);
            }
        }
    }
}
 
// Generate JSON string of this object
std::string Blur::Json() const {
 
    // Return formatted string
    return JsonValue().toStyledString();
}
 
// Generate Json::Value for this object
Json::Value Blur::JsonValue() const {
 
    // Create root json object
    Json::Value root = EffectBase::JsonValue(); // get parent properties
    root["type"] = info.class_name;
    root["horizontal_radius"] = horizontal_radius.JsonValue();
    root["vertical_radius"] = vertical_radius.JsonValue();
    root["sigma"] = sigma.JsonValue();
    root["iterations"] = iterations.JsonValue();
    root["mask_mode"] = mask_mode;
 
    // return JsonValue
    return root;
}
 
// Load JSON string into this object
void Blur::SetJson(const std::string value) {
 
    // Parse JSON string into JSON objects
    try
    {
        const Json::Value root = openshot::stringToJson(value);
        // Set all values that match
        SetJsonValue(root);
    }
    catch (const std::exception& e)
    {
        // Error parsing JSON (or missing keys)
        throw InvalidJSON("JSON is invalid (missing keys or invalid data types)");
    }
}
 
// Load Json::Value into this object
void Blur::SetJsonValue(const Json::Value root) {
 
    // Set parent data
    EffectBase::SetJsonValue(root);
 
    // Set data from Json (if key is found)
    if (!root["horizontal_radius"].isNull())
        horizontal_radius.SetJsonValue(root["horizontal_radius"]);
    if (!root["vertical_radius"].isNull())
        vertical_radius.SetJsonValue(root["vertical_radius"]);
    if (!root["sigma"].isNull())
        sigma.SetJsonValue(root["sigma"]);
    if (!root["iterations"].isNull())
        iterations.SetJsonValue(root["iterations"]);
    if (!root["mask_mode"].isNull())
        mask_mode = root["mask_mode"].asInt();
}
 
// Get all properties for a specific frame
std::string Blur::PropertiesJSON(int64_t requested_frame) const {
 
    // Generate JSON properties list
    Json::Value root = BasePropertiesJSON(requested_frame);
 
    // Keyframes
    root["horizontal_radius"] = add_property_json("Horizontal Radius", horizontal_radius.GetValue(requested_frame), "float", "", &horizontal_radius, 0, 100, false, requested_frame);
    root["vertical_radius"] = add_property_json("Vertical Radius", vertical_radius.GetValue(requested_frame), "float", "", &vertical_radius, 0, 100, false, requested_frame);
    root["sigma"] = add_property_json("Sigma", sigma.GetValue(requested_frame), "float", "", &sigma, 0, 100, false, requested_frame);
    root["iterations"] = add_property_json("Iterations", iterations.GetValue(requested_frame), "float", "", &iterations, 0, 100, false, requested_frame);
    root["mask_mode"] = add_property_json("Mask Mode", mask_mode, "int", "", NULL, 0, 1, false, requested_frame);
    root["mask_mode"]["choices"].append(add_property_choice_json("Limit to Mask", BLUR_MASK_POST_BLEND, mask_mode));
    root["mask_mode"]["choices"].append(add_property_choice_json("Vary Strength", BLUR_MASK_DRIVE_AMOUNT, mask_mode));
 
    // Return formatted string
    return root.toStyledString();
}