mesh_prediction_scheme_constrained_multi_parallelogram_decoder.h

Go to the documentation of this file.

// 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_CONSTRAINED_MULTI_PARALLELOGRAM_DECODER_H_
#define DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_CONSTRAINED_MULTI_PARALLELOGRAM_DECODER_H_
 
#include <algorithm>
#include <cmath>
 
#include "draco/compression/attributes/prediction_schemes/mesh_prediction_scheme_constrained_multi_parallelogram_shared.h"
#include "draco/compression/attributes/prediction_schemes/mesh_prediction_scheme_decoder.h"
#include "draco/compression/attributes/prediction_schemes/mesh_prediction_scheme_parallelogram_shared.h"
#include "draco/compression/bit_coders/rans_bit_decoder.h"
#include "draco/core/math_utils.h"
#include "draco/core/varint_decoding.h"
#include "draco/draco_features.h"
 
namespace draco {
 
// Decoder for predictions encoded with the constrained multi-parallelogram
// encoder. See the corresponding encoder for more details about the prediction
// method.
template <typename DataTypeT, class TransformT, class MeshDataT>
class MeshPredictionSchemeConstrainedMultiParallelogramDecoder
    : public MeshPredictionSchemeDecoder<DataTypeT, TransformT, MeshDataT> {
 public:
  using CorrType =
      typename PredictionSchemeDecoder<DataTypeT, TransformT>::CorrType;
  using CornerTable = typename MeshDataT::CornerTable;
 
  explicit MeshPredictionSchemeConstrainedMultiParallelogramDecoder(
      const PointAttribute *attribute)
      : MeshPredictionSchemeDecoder<DataTypeT, TransformT, MeshDataT>(
            attribute),
        selected_mode_(Mode::OPTIMAL_MULTI_PARALLELOGRAM) {}
  MeshPredictionSchemeConstrainedMultiParallelogramDecoder(
      const PointAttribute *attribute, const TransformT &transform,
      const MeshDataT &mesh_data)
      : MeshPredictionSchemeDecoder<DataTypeT, TransformT, MeshDataT>(
            attribute, transform, mesh_data),
        selected_mode_(Mode::OPTIMAL_MULTI_PARALLELOGRAM) {}
 
  bool ComputeOriginalValues(const CorrType *in_corr, DataTypeT *out_data,
                             int size, int num_components,
                             const PointIndex *entry_to_point_id_map) override;
 
  bool DecodePredictionData(DecoderBuffer *buffer) override;
 
  PredictionSchemeMethod GetPredictionMethod() const override {
    return MESH_PREDICTION_CONSTRAINED_MULTI_PARALLELOGRAM;
  }
 
  bool IsInitialized() const override {
    return this->mesh_data().IsInitialized();
  }
 
 private:
  typedef constrained_multi_parallelogram::Mode Mode;
  static constexpr int kMaxNumParallelograms =
      constrained_multi_parallelogram::kMaxNumParallelograms;
  // Crease edges are used to store whether any given edge should be used for
  // parallelogram prediction or not. New values are added in the order in which
  // the edges are processed. For better compression, the flags are stored in
  // in separate contexts based on the number of available parallelograms at a
  // given vertex.
  std::vector<bool> is_crease_edge_[kMaxNumParallelograms];
  Mode selected_mode_;
};
 
template <typename DataTypeT, class TransformT, class MeshDataT>
bool MeshPredictionSchemeConstrainedMultiParallelogramDecoder<
    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);
 
  // Predicted values for all simple parallelograms encountered at any given
  // vertex.
  std::vector<DataTypeT> pred_vals[kMaxNumParallelograms];
  for (int i = 0; i < kMaxNumParallelograms; ++i) {
    pred_vals[i].resize(num_components, 0);
  }
  this->transform().ComputeOriginalValue(pred_vals[0].data(), in_corr,
                                         out_data);
 
  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();
 
  // Current position in the |is_crease_edge_| array for each context.
  std::vector<int> is_crease_edge_pos(kMaxNumParallelograms, 0);
 
  // Used to store predicted value for multi-parallelogram prediction.
  std::vector<DataTypeT> multi_pred_vals(num_components);
 
  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 start_corner_id =
        this->mesh_data().data_to_corner_map()->at(p);
 
    CornerIndex corner_id(start_corner_id);
    int num_parallelograms = 0;
    bool first_pass = true;
    while (corner_id != kInvalidCornerIndex) {
      if (ComputeParallelogramPrediction(
              p, corner_id, table, *vertex_to_data_map, out_data,
              num_components, &(pred_vals[num_parallelograms][0]))) {
        // Parallelogram prediction applied and stored in
        // |pred_vals[num_parallelograms]|
        ++num_parallelograms;
        // Stop processing when we reach the maximum number of allowed
        // parallelograms.
        if (num_parallelograms == kMaxNumParallelograms) {
          break;
        }
      }
 
      // Proceed to the next corner attached to the vertex. First swing left
      // and if we reach a boundary, swing right from the start corner.
      if (first_pass) {
        corner_id = table->SwingLeft(corner_id);
      } else {
        corner_id = table->SwingRight(corner_id);
      }
      if (corner_id == start_corner_id) {
        break;
      }
      if (corner_id == kInvalidCornerIndex && first_pass) {
        first_pass = false;
        corner_id = table->SwingRight(start_corner_id);
      }
    }
 
    // Check which of the available parallelograms are actually used and compute
    // the final predicted value.
    int num_used_parallelograms = 0;
    if (num_parallelograms > 0) {
      for (int i = 0; i < num_components; ++i) {
        multi_pred_vals[i] = 0;
      }
      // Check which parallelograms are actually used.
      for (int i = 0; i < num_parallelograms; ++i) {
        const int context = num_parallelograms - 1;
        const int pos = is_crease_edge_pos[context]++;
        if (is_crease_edge_[context].size() <= pos) {
          return false;
        }
        const bool is_crease = is_crease_edge_[context][pos];
        if (!is_crease) {
          ++num_used_parallelograms;
          for (int j = 0; j < num_components; ++j) {
            multi_pred_vals[j] =
                AddAsUnsigned(multi_pred_vals[j], pred_vals[i][j]);
          }
        }
      }
    }
    const int dst_offset = p * num_components;
    if (num_used_parallelograms == 0) {
      // No parallelogram was valid.
      // We use the last decoded point as a reference.
      const int src_offset = (p - 1) * num_components;
      this->transform().ComputeOriginalValue(
          out_data + src_offset, in_corr + dst_offset, out_data + dst_offset);
    } else {
      // Compute the correction from the predicted value.
      for (int c = 0; c < num_components; ++c) {
        multi_pred_vals[c] /= num_used_parallelograms;
      }
      this->transform().ComputeOriginalValue(
          multi_pred_vals.data(), in_corr + dst_offset, out_data + dst_offset);
    }
  }
  return true;
}
 
template <typename DataTypeT, class TransformT, class MeshDataT>
bool MeshPredictionSchemeConstrainedMultiParallelogramDecoder<
    DataTypeT, TransformT, MeshDataT>::DecodePredictionData(DecoderBuffer
                                                                *buffer) {
#ifdef DRACO_BACKWARDS_COMPATIBILITY_SUPPORTED
  if (buffer->bitstream_version() < DRACO_BITSTREAM_VERSION(2, 2)) {
    // Decode prediction mode.
    uint8_t mode;
    if (!buffer->Decode(&mode)) {
      return false;
    }
 
    if (mode != Mode::OPTIMAL_MULTI_PARALLELOGRAM) {
      // Unsupported mode.
      return false;
    }
  }
#endif
 
  // Encode selected edges using separate rans bit coder for each context.
  for (int i = 0; i < kMaxNumParallelograms; ++i) {
    uint32_t num_flags;
    if (!DecodeVarint<uint32_t>(&num_flags, buffer)) {
      return false;
    }
    if (num_flags > this->mesh_data().corner_table()->num_corners()) {
      return false;
    }
    if (num_flags > 0) {
      is_crease_edge_[i].resize(num_flags);
      RAnsBitDecoder decoder;
      if (!decoder.StartDecoding(buffer)) {
        return false;
      }
      for (uint32_t j = 0; j < num_flags; ++j) {
        is_crease_edge_[i][j] = decoder.DecodeNextBit();
      }
      decoder.EndDecoding();
    }
  }
  return MeshPredictionSchemeDecoder<DataTypeT, TransformT,
                                     MeshDataT>::DecodePredictionData(buffer);
}
 
}  // namespace draco
 
#endif  // DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_CONSTRAINED_MULTI_PARALLELOGRAM_DECODER_H_