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87 lines
3.8 KiB
C++
87 lines
3.8 KiB
C++
// Copyright 2016 The Draco Authors.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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#ifndef DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_PREDICTION_SCHEME_DIFFERENCE_H_
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#define DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_PREDICTION_SCHEME_DIFFERENCE_H_
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#include "compression/attributes/prediction_schemes/prediction_scheme.h"
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namespace draco {
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// Basic prediction scheme based on computing backward differences between
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// stored attribute values (also known as delta-coding). Usually works better
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// than the reference point prediction scheme, because nearby values are often
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// encoded next to each other.
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template <typename DataTypeT,
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class Transform = PredictionSchemeTransform<DataTypeT, DataTypeT>>
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class PredictionSchemeDifference
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: public PredictionScheme<DataTypeT, Transform> {
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public:
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using CorrType = typename PredictionScheme<DataTypeT, Transform>::CorrType;
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// Initialized the prediction scheme.
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explicit PredictionSchemeDifference(const PointAttribute *attribute)
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: PredictionScheme<DataTypeT, Transform>(attribute) {}
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PredictionSchemeDifference(const PointAttribute *attribute,
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const Transform &transform)
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: PredictionScheme<DataTypeT, Transform>(attribute, transform) {}
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bool Encode(const DataTypeT *in_data, CorrType *out_corr, int size,
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int num_components,
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const PointIndex *entry_to_point_id_map) override;
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bool Decode(const CorrType *in_corr, DataTypeT *out_data, int size,
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int num_components,
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const PointIndex *entry_to_point_id_map) override;
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PredictionSchemeMethod GetPredictionMethod() const override {
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return PREDICTION_DIFFERENCE;
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}
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bool IsInitialized() const override { return true; }
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};
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template <typename DataTypeT, class Transform>
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bool PredictionSchemeDifference<DataTypeT, Transform>::Encode(
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const DataTypeT *in_data, CorrType *out_corr, int size, int num_components,
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const PointIndex *) {
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this->transform().InitializeEncoding(in_data, size, num_components);
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// Encode data from the back using D(i) = D(i) - D(i - 1).
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for (int i = size - num_components; i > 0; i -= num_components) {
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this->transform().ComputeCorrection(
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in_data + i, in_data + i - num_components, out_corr, i);
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}
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// Encode correction for the first element.
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std::unique_ptr<DataTypeT[]> zero_vals(new DataTypeT[num_components]());
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this->transform().ComputeCorrection(in_data, zero_vals.get(), out_corr, 0);
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return true;
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}
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template <typename DataTypeT, class Transform>
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bool PredictionSchemeDifference<DataTypeT, Transform>::Decode(
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const CorrType *in_corr, DataTypeT *out_data, int size, int num_components,
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const PointIndex *) {
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this->transform().InitializeDecoding(num_components);
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// Decode the original value for the first element.
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std::unique_ptr<DataTypeT[]> zero_vals(new DataTypeT[num_components]());
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this->transform().ComputeOriginalValue(zero_vals.get(), in_corr, out_data, 0);
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// Decode data from the front using D(i) = D(i) + D(i - 1).
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for (int i = num_components; i < size; i += num_components) {
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this->transform().ComputeOriginalValue(out_data + i - num_components,
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in_corr, out_data + i, i);
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}
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return true;
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}
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} // namespace draco
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#endif // DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_PREDICTION_SCHEME_DIFFERENCE_H_
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