139 lines
3.8 KiB
C++
139 lines
3.8 KiB
C++
#include <hyperion/ImageToLedsMap.h>
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using namespace hyperion;
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ImageToLedsMap::ImageToLedsMap(
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Logger* log,
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int width,
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int height,
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int horizontalBorder,
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int verticalBorder,
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const std::vector<Led>& leds,
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int reducedPixelSetFactor,
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int accuracyLevel)
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: _log(log)
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, _width(width)
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, _height(height)
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, _horizontalBorder(horizontalBorder)
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, _verticalBorder(verticalBorder)
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, _nextPixelCount(reducedPixelSetFactor)
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, _clusterCount()
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, _colorsMap()
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{
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_nextPixelCount = reducedPixelSetFactor + 1;
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setAccuracyLevel(accuracyLevel);
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// Sanity check of the size of the borders (and width and height)
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Q_ASSERT(_width > 2*_verticalBorder);
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Q_ASSERT(_height > 2*_horizontalBorder);
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Q_ASSERT(_width < 10000);
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Q_ASSERT(_height < 10000);
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// Reserve enough space in the map for the leds
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_colorsMap.reserve(leds.size());
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const int xOffset = _verticalBorder;
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const int actualWidth = _width - 2 * _verticalBorder;
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const int yOffset = _horizontalBorder;
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const int actualHeight = _height - 2 * _horizontalBorder;
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size_t totalCount = 0;
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size_t totalCapacity = 0;
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int ledCounter = 0;
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for (const Led& led : leds)
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{
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// skip leds without area
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if ((led.maxX_frac-led.minX_frac) < 1e-6 || (led.maxY_frac-led.minY_frac) < 1e-6)
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{
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_colorsMap.emplace_back();
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continue;
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}
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// Compute the index boundaries for this led
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int minX_idx = xOffset + int32_t(qRound(actualWidth * led.minX_frac));
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int maxX_idx = xOffset + int32_t(qRound(actualWidth * led.maxX_frac));
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int minY_idx = yOffset + int32_t(qRound(actualHeight * led.minY_frac));
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int maxY_idx = yOffset + int32_t(qRound(actualHeight * led.maxY_frac));
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// make sure that the area is at least a single led large
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minX_idx = qMin(minX_idx, xOffset + actualWidth - 1);
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if (minX_idx == maxX_idx)
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{
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maxX_idx++;
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}
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minY_idx = qMin(minY_idx, yOffset + actualHeight - 1);
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if (minY_idx == maxY_idx)
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{
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maxY_idx++;
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}
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// Add all the indices in the above defined rectangle to the indices for this led
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const int maxYLedCount = qMin(maxY_idx, yOffset+actualHeight);
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const int maxXLedCount = qMin(maxX_idx, xOffset+actualWidth);
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const int realYLedCount = qAbs(maxYLedCount - minY_idx);
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const int realXLedCount = qAbs(maxXLedCount - minX_idx);
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bool skipPixelProcessing {false};
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if (_nextPixelCount > 1)
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{
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skipPixelProcessing = true;
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}
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size_t totalSize = static_cast<size_t>(realYLedCount * realXLedCount);
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if (!skipPixelProcessing && totalSize > 1600)
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{
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skipPixelProcessing = true;
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_nextPixelCount = 2;
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Warning(_log, "Mapping LED/light [%d]. The current mapping area contains %d pixels which is huge. Therefore every %d pixels will be skipped. You can enable reduced processing to hide that warning.", ledCounter, totalSize, _nextPixelCount);
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}
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std::vector<int> ledColors;
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ledColors.reserve(totalSize);
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for (int y = minY_idx; y < maxYLedCount; y += _nextPixelCount)
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{
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for (int x = minX_idx; x < maxXLedCount; x += _nextPixelCount)
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{
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ledColors.push_back( y * width + x);
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}
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}
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// Add the constructed vector to the map
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_colorsMap.push_back(ledColors);
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totalCount += ledColors.size();
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totalCapacity += ledColors.capacity();
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ledCounter++;
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}
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Debug(_log, "Total index number is: %d (memory: %d). Reduced pixel set factor: %d, Accuracy level: %d, Image size: %d x %d, LED areas: %d",
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totalCount, totalCapacity, reducedPixelSetFactor, accuracyLevel, width, height, leds.size());
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}
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int ImageToLedsMap::width() const
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{
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return _width;
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}
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int ImageToLedsMap::height() const
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{
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return _height;
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}
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void ImageToLedsMap::setAccuracyLevel (int accuracyLevel)
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{
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if (accuracyLevel > 4 )
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{
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Warning(_log, "Accuracy level %d is too high, it will be set to 4", accuracyLevel);
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accuracyLevel = 4;
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}
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//Set cluster number for dominant color advanced
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_clusterCount = accuracyLevel + 1;
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}
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