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73bb3c8530
- Improved compression for triangular meshes (~10%) - Added WebAssembly decoder - Code cleanup + robustness fixes
71 lines
3.1 KiB
C++
71 lines
3.1 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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// Shared funcionality for different parallelogram prediction schemes.
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#ifndef DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_PARALLELOGRAM_SHARED_H_
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#define DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_PARALLELOGRAM_SHARED_H_
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#include "mesh/corner_table.h"
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#include "mesh/mesh.h"
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namespace draco {
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template <class CornerTableT>
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inline void GetParallelogramEntries(
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const CornerIndex ci, const CornerTableT *table,
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const std::vector<int32_t> &vertex_to_data_map, int *opp_entry,
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int *next_entry, int *prev_entry) {
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// One vertex of the input |table| correspond to exactly one attribute value
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// entry. The |table| can be either CornerTable for per-vertex attributes,
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// or MeshAttributeCornerTable for attributes with interior seams.
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*opp_entry = vertex_to_data_map[table->Vertex(ci).value()];
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*next_entry = vertex_to_data_map[table->Vertex(table->Next(ci)).value()];
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*prev_entry = vertex_to_data_map[table->Vertex(table->Previous(ci)).value()];
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}
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// Computes parallelogram prediction for a given corner and data entry id.
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// The prediction is stored in |out_prediction|.
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// Function returns false when the prediction couldn't be computed, e.g. because
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// not all entry points were available.
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template <class CornerTableT, typename DataTypeT>
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inline bool ComputeParallelogramPrediction(
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int data_entry_id, const CornerIndex ci, const CornerTableT *table,
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const std::vector<int32_t> &vertex_to_data_map, const DataTypeT *in_data,
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int num_components, DataTypeT *out_prediction) {
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const CornerIndex oci = table->Opposite(ci);
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if (oci < 0)
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return false;
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int vert_opp, vert_next, vert_prev;
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GetParallelogramEntries<CornerTableT>(oci, table, vertex_to_data_map,
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&vert_opp, &vert_next, &vert_prev);
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if (vert_opp < data_entry_id && vert_next < data_entry_id &&
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vert_prev < data_entry_id) {
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// Apply the parallelogram prediction.
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const int v_opp_off = vert_opp * num_components;
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const int v_next_off = vert_next * num_components;
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const int v_prev_off = vert_prev * num_components;
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for (int c = 0; c < num_components; ++c) {
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out_prediction[c] = (in_data[v_next_off + c] + in_data[v_prev_off + c]) -
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in_data[v_opp_off + c];
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}
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return true;
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}
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return false; // Not all data is available for prediction
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}
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} // namespace draco
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#endif // DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_PARALLELOGRAM_SHARED_H_
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