mesh_prediction_scheme_parallelogram_decoder.h

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// Copyright 2016 The Draco Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//      http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
#ifndef DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_PARALLELOGRAM_DECODER_H_
#define DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_PARALLELOGRAM_DECODER_H_
 
#include "draco/compression/attributes/prediction_schemes/mesh_prediction_scheme_decoder.h"
#include "draco/compression/attributes/prediction_schemes/mesh_prediction_scheme_parallelogram_shared.h"
 
namespace draco {
 
// Decoder for attribute values encoded with the standard parallelogram
// prediction. See the description of the corresponding encoder for more
// details.
template <typename DataTypeT, class TransformT, class MeshDataT>
class MeshPredictionSchemeParallelogramDecoder
    : public MeshPredictionSchemeDecoder<DataTypeT, TransformT, MeshDataT> {
 public:
  using CorrType =
      typename PredictionSchemeDecoder<DataTypeT, TransformT>::CorrType;
  using CornerTable = typename MeshDataT::CornerTable;
  explicit MeshPredictionSchemeParallelogramDecoder(
      const PointAttribute *attribute)
      : MeshPredictionSchemeDecoder<DataTypeT, TransformT, MeshDataT>(
            attribute) {}
  MeshPredictionSchemeParallelogramDecoder(const PointAttribute *attribute,
                                           const TransformT &transform,
                                           const MeshDataT &mesh_data)
      : MeshPredictionSchemeDecoder<DataTypeT, TransformT, MeshDataT>(
            attribute, transform, mesh_data) {}
 
  bool ComputeOriginalValues(const CorrType *in_corr, DataTypeT *out_data,
                             int size, int num_components,
                             const PointIndex *entry_to_point_id_map) override;
  PredictionSchemeMethod GetPredictionMethod() const override {
    return MESH_PREDICTION_PARALLELOGRAM;
  }
 
  bool IsInitialized() const override {
    return this->mesh_data().IsInitialized();
  }
};
 
template <typename DataTypeT, class TransformT, class MeshDataT>
bool MeshPredictionSchemeParallelogramDecoder<DataTypeT, TransformT,
                                              MeshDataT>::
    ComputeOriginalValues(const CorrType *in_corr, DataTypeT *out_data,
                          int /* size */, int num_components,
                          const PointIndex * /* entry_to_point_id_map */) {
  this->transform().Init(num_components);
 
  const CornerTable *const table = this->mesh_data().corner_table();
  const std::vector<int32_t> *const vertex_to_data_map =
      this->mesh_data().vertex_to_data_map();
 
  // For storage of prediction values (already initialized to zero).
  std::unique_ptr<DataTypeT[]> pred_vals(new DataTypeT[num_components]());
 
  // Restore the first value.
  this->transform().ComputeOriginalValue(pred_vals.get(), in_corr, out_data);
 
  const int corner_map_size =
      static_cast<int>(this->mesh_data().data_to_corner_map()->size());
  for (int p = 1; p < corner_map_size; ++p) {
    const CornerIndex corner_id = this->mesh_data().data_to_corner_map()->at(p);
    const int dst_offset = p * num_components;
    if (!ComputeParallelogramPrediction(p, corner_id, table,
                                        *vertex_to_data_map, out_data,
                                        num_components, pred_vals.get())) {
      // Parallelogram could not be computed, Possible because some of the
      // vertices are not valid (not encoded yet).
      // We use the last encoded point as a reference (delta coding).
      const int src_offset = (p - 1) * num_components;
      this->transform().ComputeOriginalValue(
          out_data + src_offset, in_corr + dst_offset, out_data + dst_offset);
    } else {
      // Apply the parallelogram prediction.
      this->transform().ComputeOriginalValue(
          pred_vals.get(), in_corr + dst_offset, out_data + dst_offset);
    }
  }
  return true;
}
 
}  // namespace draco
 
#endif  // DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_PARALLELOGRAM_DECODER_H_