// Copyright (c) the JPEG XL Project Authors. All rights reserved. // // Use of this source code is governed by a BSD-style // license that can be found in the LICENSE file. #ifndef LIB_JXL_SPLINES_H_ #define LIB_JXL_SPLINES_H_ #include #include #include #include #include "lib/jxl/ans_params.h" #include "lib/jxl/aux_out.h" #include "lib/jxl/aux_out_fwd.h" #include "lib/jxl/base/status.h" #include "lib/jxl/chroma_from_luma.h" #include "lib/jxl/dec_ans.h" #include "lib/jxl/dec_bit_reader.h" #include "lib/jxl/entropy_coder.h" #include "lib/jxl/image.h" namespace jxl { static constexpr float kDesiredRenderingDistance = 1.f; enum SplineEntropyContexts : size_t { kQuantizationAdjustmentContext = 0, kStartingPositionContext, kNumSplinesContext, kNumControlPointsContext, kControlPointsContext, kDCTContext, kNumSplineContexts }; struct Spline { struct Point { Point() : x(0.0f), y(0.0f) {} Point(float x, float y) : x(x), y(y) {} float x, y; bool operator==(const Point& other) const { return std::fabs(x - other.x) < 1e-3f && std::fabs(y - other.y) < 1e-3f; } }; std::vector control_points; // X, Y, B. float color_dct[3][32]; // Splines are draws by normalized Gaussian splatting. This controls the // Gaussian's parameter along the spline. float sigma_dct[32]; }; class QuantizedSplineEncoder; class QuantizedSpline { public: QuantizedSpline() = default; explicit QuantizedSpline(const Spline& original, int32_t quantization_adjustment, float y_to_x, float y_to_b); Status Dequantize(const Spline::Point& starting_point, int32_t quantization_adjustment, float y_to_x, float y_to_b, Spline& result) const; Status Decode(const std::vector& context_map, ANSSymbolReader* decoder, BitReader* br, size_t max_control_points, size_t* total_num_control_points); private: friend class QuantizedSplineEncoder; std::vector> control_points_; // Double delta-encoded. int color_dct_[3][32] = {}; int sigma_dct_[32] = {}; }; // A single "drawable unit" of a spline, i.e. a line of the region in which we // render each Gaussian. The structure doesn't actually depend on the exact // row, which allows reuse for different y values (which are tracked // separately). struct SplineSegment { float center_x, center_y; float maximum_distance; float inv_sigma; float sigma_over_4_times_intensity; float color[3]; }; class Splines { public: Splines() = default; explicit Splines(const int32_t quantization_adjustment, std::vector splines, std::vector starting_points) : quantization_adjustment_(quantization_adjustment), splines_(std::move(splines)), starting_points_(std::move(starting_points)) {} bool HasAny() const { return !splines_.empty(); } void Clear(); Status Decode(BitReader* br, size_t num_pixels); void AddTo(Image3F* opsin, const Rect& opsin_rect, const Rect& image_rect) const; void AddToRow(float* JXL_RESTRICT row_x, float* JXL_RESTRICT row_y, float* JXL_RESTRICT row_b, const Rect& image_row) const; void SubtractFrom(Image3F* opsin) const; const std::vector& QuantizedSplines() const { return splines_; } const std::vector& StartingPoints() const { return starting_points_; } int32_t GetQuantizationAdjustment() const { return quantization_adjustment_; } Status InitializeDrawCache(size_t image_xsize, size_t image_ysize, const ColorCorrelationMap& cmap); private: template void ApplyToRow(float* JXL_RESTRICT row_x, float* JXL_RESTRICT row_y, float* JXL_RESTRICT row_b, const Rect& image_row) const; template void Apply(Image3F* opsin, const Rect& opsin_rect, const Rect& image_rect) const; // If positive, quantization weights are multiplied by 1 + this/8, which // increases precision. If negative, they are divided by 1 - this/8. If 0, // they are unchanged. int32_t quantization_adjustment_ = 0; std::vector splines_; std::vector starting_points_; std::vector segments_; std::vector segment_indices_; std::vector segment_y_start_; }; } // namespace jxl #endif // LIB_JXL_SPLINES_H_