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https://git.mirrors.martin98.com/https://github.com/google/draco
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73bb3c8530
- Improved compression for triangular meshes (~10%) - Added WebAssembly decoder - Code cleanup + robustness fixes
66 lines
3.1 KiB
C++
66 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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// Functions for creating prediction schemes for decoders using the provided
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// prediction method id.
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#ifndef DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_PREDICTION_SCHEME_DECODER_FACTORY_H_
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#define DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_PREDICTION_SCHEME_DECODER_FACTORY_H_
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#include "compression/attributes/prediction_schemes/prediction_scheme_factory.h"
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#include "compression/mesh/mesh_decoder.h"
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namespace draco {
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// Creates a prediction scheme for a given decoder and given prediction method.
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// The prediction schemes are automatically initialized with decoder specific
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// data if needed.
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template <typename DataTypeT,
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class TransformT = PredictionSchemeTransform<DataTypeT, DataTypeT>>
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std::unique_ptr<PredictionScheme<DataTypeT, TransformT>>
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CreatePredictionSchemeForDecoder(PredictionSchemeMethod method, int att_id,
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const PointCloudDecoder *decoder,
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const TransformT &transform) {
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const PointAttribute *const att = decoder->point_cloud()->attribute(att_id);
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if (decoder->GetGeometryType() == TRIANGULAR_MESH) {
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// Cast the decoder to mesh decoder. This is not necessarily safe if there
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// is some other decoder decides to use TRIANGULAR_MESH as the return type,
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// but unfortunately there is not nice work around for this without using
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// RTTI (double dispatch and similar conecepts will not work because of the
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// template nature of the prediction schemes).
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const MeshDecoder *const mesh_decoder =
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static_cast<const MeshDecoder *>(decoder);
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auto ret = CreateMeshPredictionScheme<MeshDecoder, DataTypeT, TransformT>(
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mesh_decoder, method, att_id, transform, decoder->bitstream_version());
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if (ret)
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return ret;
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// Otherwise try to create another prediction scheme.
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}
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return CreatePredictionScheme<DataTypeT, TransformT>(method, att, transform);
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}
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// Create a prediction scheme using a default transform constructor.
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template <typename DataTypeT,
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class TransformT = PredictionSchemeTransform<DataTypeT, DataTypeT>>
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std::unique_ptr<PredictionScheme<DataTypeT, TransformT>>
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CreatePredictionSchemeForDecoder(PredictionSchemeMethod method, int att_id,
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const PointCloudDecoder *decoder) {
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return CreatePredictionSchemeForDecoder<DataTypeT, TransformT>(
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method, att_id, decoder, TransformT());
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}
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} // namespace draco
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#endif // DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_PREDICTION_SCHEME_DECODER_FACTORY_H_
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