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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.
//
#ifdef DRACO_BACKWARDS_COMPATIBILITY_SUPPORTED
#ifndef DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_MULTI_PARALLELOGRAM_DECODER_H_
#define DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_MULTI_PARALLELOGRAM_DECODER_H_
#include "draco/draco_features.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 predictions encoded by multi-parallelogram encoding scheme.
// See the corresponding encoder for method description.
template <typename DataTypeT, class TransformT, class MeshDataT>
class MeshPredictionSchemeMultiParallelogramDecoder
: public MeshPredictionSchemeDecoder<DataTypeT, TransformT, MeshDataT> {
public:
using CorrType =
typename PredictionSchemeDecoder<DataTypeT, TransformT>::CorrType;
using CornerTable = typename MeshDataT::CornerTable;
explicit MeshPredictionSchemeMultiParallelogramDecoder(
const PointAttribute *attribute)
: MeshPredictionSchemeDecoder<DataTypeT, TransformT, MeshDataT>(
attribute) {}
MeshPredictionSchemeMultiParallelogramDecoder(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_MULTI_PARALLELOGRAM;
}
bool IsInitialized() const override {
return this->mesh_data().IsInitialized();
}
};
template <typename DataTypeT, class TransformT, class MeshDataT>
bool MeshPredictionSchemeMultiParallelogramDecoder<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);
// For storage of prediction values (already initialized to zero).
std::unique_ptr<DataTypeT[]> pred_vals(new DataTypeT[num_components]());
std::unique_ptr<DataTypeT[]> parallelogram_pred_vals(
new DataTypeT[num_components]());
this->transform().ComputeOriginalValue(pred_vals.get(), 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();
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;
for (int i = 0; i < num_components; ++i) {
pred_vals[i] = static_cast<DataTypeT>(0);
}
while (corner_id != kInvalidCornerIndex) {
if (ComputeParallelogramPrediction(
p, corner_id, table, *vertex_to_data_map, out_data,
num_components, parallelogram_pred_vals.get())) {
for (int c = 0; c < num_components; ++c) {
pred_vals[c] += parallelogram_pred_vals[c];
}
++num_parallelograms;
}
// Proceed to the next corner attached to the vertex.
corner_id = table->SwingRight(corner_id);
if (corner_id == start_corner_id) {
corner_id = kInvalidCornerIndex;
}
}
const int dst_offset = p * num_components;
if (num_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) {
pred_vals[c] /= num_parallelograms;
}
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_MULTI_PARALLELOGRAM_DECODER_H_
#endif
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