mirror of
https://github.com/hyperion-project/hyperion.ng.git
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239 lines
7.1 KiB
C++
239 lines
7.1 KiB
C++
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#pragma once
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// STL includes
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#include <cassert>
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#include <sstream>
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// hyperion-utils includes
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#include <utils/Image.h>
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#include <utils/Logger.h>
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// hyperion includes
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#include <hyperion/LedString.h>
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namespace hyperion
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{
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///
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/// The ImageToLedsMap holds a mapping of indices into an image to leds. It can be used to
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/// calculate the average (or mean) color per led for a specific region.
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///
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class ImageToLedsMap
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{
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public:
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///
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/// Constructs an mapping from the absolute indices in an image to each led based on the border
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/// definition given in the list of leds. The map holds absolute indices to any given image,
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/// provided that it is row-oriented.
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/// The mapping is created purely on size (width and height). The given borders are excluded
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/// from indexing.
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///
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/// @param[in] width The width of the indexed image
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/// @param[in] height The width of the indexed image
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/// @param[in] horizontalBorder The size of the horizontal border (0=no border)
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/// @param[in] verticalBorder The size of the vertical border (0=no border)
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/// @param[in] leds The list with led specifications
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///
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ImageToLedsMap(
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const unsigned width,
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const unsigned height,
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const unsigned horizontalBorder,
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const unsigned verticalBorder,
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const std::vector<Led> & leds);
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///
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/// Returns the width of the indexed image
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///
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/// @return The width of the indexed image [pixels]
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///
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unsigned width() const;
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///
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/// Returns the height of the indexed image
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///
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/// @return The height of the indexed image [pixels]
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///
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unsigned height() const;
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unsigned horizontalBorder() const { return _horizontalBorder; };
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unsigned verticalBorder() const { return _verticalBorder; };
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///
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/// Determines the mean color for each led using the mapping the image given
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/// at construction.
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///
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/// @param[in] image The image from which to extract the led colors
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///
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/// @return ledColors The vector containing the output
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///
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template <typename Pixel_T>
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std::vector<ColorRgb> getMeanLedColor(const Image<Pixel_T> & image) const
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{
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std::vector<ColorRgb> colors(_colorsMap.size(), ColorRgb{0,0,0});
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getMeanLedColor(image, colors);
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return colors;
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}
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///
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/// Determines the mean color for each led using the mapping the image given
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/// at construction.
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///
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/// @param[in] image The image from which to extract the led colors
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/// @param[out] ledColors The vector containing the output
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///
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template <typename Pixel_T>
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void getMeanLedColor(const Image<Pixel_T> & image, std::vector<ColorRgb> & ledColors) const
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{
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// Sanity check for the number of leds
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//assert(_colorsMap.size() == ledColors.size());
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if(_colorsMap.size() != ledColors.size())
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{
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Debug(Logger::getInstance("HYPERION"), "ImageToLedsMap: colorsMap.size != ledColors.size -> %d != %d", _colorsMap.size(), ledColors.size());
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return;
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}
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// Iterate each led and compute the mean
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auto led = ledColors.begin();
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for (auto colors = _colorsMap.begin(); colors != _colorsMap.end(); ++colors, ++led)
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{
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const ColorRgb color = calcMeanColor(image, *colors);
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*led = color;
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}
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}
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///
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/// Determines the uni color for each led using the mapping the image given
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/// at construction.
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///
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/// @param[in] image The image from which to extract the led colors
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///
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/// @return ledColors The vector containing the output
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///
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template <typename Pixel_T>
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std::vector<ColorRgb> getUniLedColor(const Image<Pixel_T> & image) const
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{
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std::vector<ColorRgb> colors(_colorsMap.size(), ColorRgb{0,0,0});
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getUniLedColor(image, colors);
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return colors;
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}
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///
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/// Determines the uni color for each led using the mapping the image given
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/// at construction.
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///
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/// @param[in] image The image from which to extract the led colors
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/// @param[out] ledColors The vector containing the output
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///
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template <typename Pixel_T>
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void getUniLedColor(const Image<Pixel_T> & image, std::vector<ColorRgb> & ledColors) const
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{
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// Sanity check for the number of leds
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// assert(_colorsMap.size() == ledColors.size());
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if(_colorsMap.size() != ledColors.size())
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{
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Debug(Logger::getInstance("HYPERION"), "ImageToLedsMap: colorsMap.size != ledColors.size -> %d != %d", _colorsMap.size(), ledColors.size());
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return;
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}
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// calculate uni color
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const ColorRgb color = calcMeanColor(image);
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std::fill(ledColors.begin(),ledColors.end(), color);
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}
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private:
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/// The width of the indexed image
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const unsigned _width;
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/// The height of the indexed image
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const unsigned _height;
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const unsigned _horizontalBorder;
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const unsigned _verticalBorder;
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/// The absolute indices into the image for each led
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std::vector<std::vector<unsigned>> _colorsMap;
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///
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/// Calculates the 'mean color' of the given list. This is the mean over each color-channel
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/// (red, green, blue)
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///
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/// @param[in] image The image a section from which an average color must be computed
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/// @param[in] colors The list with colors
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///
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/// @return The mean of the given list of colors (or black when empty)
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///
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template <typename Pixel_T>
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ColorRgb calcMeanColor(const Image<Pixel_T> & image, const std::vector<unsigned> & colors) const
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{
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const auto colorVecSize = colors.size();
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if (colorVecSize == 0)
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{
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return ColorRgb::BLACK;
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}
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// Accumulate the sum of each seperate color channel
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uint_fast32_t cummRed = 0;
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uint_fast32_t cummGreen = 0;
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uint_fast32_t cummBlue = 0;
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const auto& imgData = image.memptr();
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for (const unsigned colorOffset : colors)
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{
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const auto& pixel = imgData[colorOffset];
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cummRed += pixel.red;
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cummGreen += pixel.green;
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cummBlue += pixel.blue;
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}
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// Compute the average of each color channel
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const uint8_t avgRed = uint8_t(cummRed/colorVecSize);
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const uint8_t avgGreen = uint8_t(cummGreen/colorVecSize);
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const uint8_t avgBlue = uint8_t(cummBlue/colorVecSize);
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// Return the computed color
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return {avgRed, avgGreen, avgBlue};
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}
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///
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/// Calculates the 'mean color' over the given image. This is the mean over each color-channel
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/// (red, green, blue)
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///
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/// @param[in] image The image a section from which an average color must be computed
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///
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/// @return The mean of the given list of colors (or black when empty)
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///
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template <typename Pixel_T>
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ColorRgb calcMeanColor(const Image<Pixel_T> & image) const
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{
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// Accumulate the sum of each seperate color channel
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uint_fast32_t cummRed = 0;
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uint_fast32_t cummGreen = 0;
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uint_fast32_t cummBlue = 0;
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const unsigned imageSize = image.width() * image.height();
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const auto& imgData = image.memptr();
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for (unsigned idx=0; idx<imageSize; idx++)
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{
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const auto& pixel = imgData[idx];
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cummRed += pixel.red;
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cummGreen += pixel.green;
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cummBlue += pixel.blue;
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}
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// Compute the average of each color channel
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const uint8_t avgRed = uint8_t(cummRed/imageSize);
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const uint8_t avgGreen = uint8_t(cummGreen/imageSize);
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const uint8_t avgBlue = uint8_t(cummBlue/imageSize);
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// Return the computed color
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return {avgRed, avgGreen, avgBlue};
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}
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};
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} // end namespace hyperion
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