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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.
//
// Shared functionality for different parallelogram prediction schemes.
#ifndef DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_PARALLELOGRAM_SHARED_H_
#define DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_PARALLELOGRAM_SHARED_H_
#include "draco/mesh/corner_table.h"
#include "draco/mesh/mesh.h"
namespace draco {
// TODO(draco-eng) consolidate Vertex/next/previous queries to one call
// (performance).
template <class CornerTableT>
inline void GetParallelogramEntries(
const CornerIndex ci, const CornerTableT *table,
const std::vector<int32_t> &vertex_to_data_map, int *opp_entry,
int *next_entry, int *prev_entry) {
// One vertex of the input |table| correspond to exactly one attribute value
// entry. The |table| can be either CornerTable for per-vertex attributes,
// or MeshAttributeCornerTable for attributes with interior seams.
*opp_entry = vertex_to_data_map[table->Vertex(ci).value()];
*next_entry = vertex_to_data_map[table->Vertex(table->Next(ci)).value()];
*prev_entry = vertex_to_data_map[table->Vertex(table->Previous(ci)).value()];
}
// Computes parallelogram prediction for a given corner and data entry id.
// The prediction is stored in |out_prediction|.
// Function returns false when the prediction couldn't be computed, e.g. because
// not all entry points were available.
template <class CornerTableT, typename DataTypeT>
inline bool ComputeParallelogramPrediction(
int data_entry_id, const CornerIndex ci, const CornerTableT *table,
const std::vector<int32_t> &vertex_to_data_map, const DataTypeT *in_data,
int num_components, DataTypeT *out_prediction) {
const CornerIndex oci = table->Opposite(ci);
if (oci == kInvalidCornerIndex) {
return false;
}
int vert_opp, vert_next, vert_prev;
GetParallelogramEntries<CornerTableT>(oci, table, vertex_to_data_map,
&vert_opp, &vert_next, &vert_prev);
if (vert_opp < data_entry_id && vert_next < data_entry_id &&
vert_prev < data_entry_id) {
// Apply the parallelogram prediction.
const int v_opp_off = vert_opp * num_components;
const int v_next_off = vert_next * num_components;
const int v_prev_off = vert_prev * num_components;
for (int c = 0; c < num_components; ++c) {
out_prediction[c] = (in_data[v_next_off + c] + in_data[v_prev_off + c]) -
in_data[v_opp_off + c];
}
return true;
}
return false; // Not all data is available for prediction
}
} // namespace draco
#endif // DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_PARALLELOGRAM_SHARED_H_
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