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[Model] Add Paddle3D CenterPoint model (#2078)
* add centerpoint * update for review comments
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examples/vision/perception/paddle3d/centerpoint/cpp/CMakeLists.txt
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| PROJECT(infer_demo C CXX) | ||
| CMAKE_MINIMUM_REQUIRED (VERSION 3.10) | ||
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| # 指定下载解压后的fastdeploy库路径 | ||
| option(FASTDEPLOY_INSTALL_DIR "Path of downloaded fastdeploy sdk.") | ||
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| include(${FASTDEPLOY_INSTALL_DIR}/FastDeploy.cmake) | ||
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| # 添加FastDeploy依赖头文件 | ||
| include_directories(${FASTDEPLOY_INCS}) | ||
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| add_executable(infer_demo ${PROJECT_SOURCE_DIR}/infer.cc) | ||
| # 添加FastDeploy库依赖 | ||
| target_link_libraries(infer_demo ${FASTDEPLOY_LIBS}) |
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examples/vision/perception/paddle3d/centerpoint/cpp/infer.cc
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| // Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. | ||
| // | ||
| // 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. | ||
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| #include "fastdeploy/vision.h" | ||
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| int main(int argc, char* argv[]) { | ||
| fastdeploy::RuntimeOption option; | ||
| option.UseGpu(); | ||
| option.UsePaddleBackend(); | ||
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| std::string model_file = argv[1]; | ||
| std::string params_file = argv[2]; | ||
| std::string test_point = argv[3]; | ||
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| auto model = fastdeploy::vision::perception::Centerpoint( | ||
| model_file, params_file, "test", option, fastdeploy::ModelFormat::PADDLE); | ||
| assert(model.Initialized()); | ||
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| fastdeploy::vision::PerceptionResult res; | ||
| if (!model.Predict(test_point, &res)) { | ||
| std::cerr << "Failed to predict." << std::endl; | ||
| return 1; | ||
| } | ||
| std::cout << "predict result:" << res.Str() << std::endl; | ||
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| return 0; | ||
| } |
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fastdeploy/vision/perception/paddle3d/centerpoint/centerpoint.cc
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| // Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. | ||
| // | ||
| // 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. | ||
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| #include "fastdeploy/vision/perception/paddle3d/centerpoint/centerpoint.h" | ||
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| namespace fastdeploy { | ||
| namespace vision { | ||
| namespace perception { | ||
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| Centerpoint::Centerpoint(const std::string& model_file, | ||
| const std::string& params_file, | ||
| const std::string& config_file, | ||
| const RuntimeOption& custom_option, | ||
| const ModelFormat& model_format) | ||
| : preprocessor_(config_file) { | ||
| valid_gpu_backends = {Backend::PDINFER}; | ||
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| runtime_option = custom_option; | ||
| runtime_option.model_format = model_format; | ||
| runtime_option.model_file = model_file; | ||
| runtime_option.params_file = params_file; | ||
| initialized = Initialize(); | ||
| } | ||
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| bool Centerpoint::Initialize() { | ||
| if (!InitRuntime()) { | ||
| FDERROR << "Failed to initialize fastdeploy backend." << std::endl; | ||
| return false; | ||
| } | ||
| return true; | ||
| } | ||
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| bool Centerpoint::Predict(const std::string point_dir, | ||
| PerceptionResult* result) { | ||
| std::vector<PerceptionResult> results; | ||
| if (!BatchPredict({point_dir}, &results)) { | ||
| return false; | ||
| } | ||
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| if (results.size()) { | ||
| *result = std::move(results[0]); | ||
| } | ||
| return true; | ||
| } | ||
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| bool Centerpoint::BatchPredict(std::vector<std::string> points_dir, | ||
| std::vector<PerceptionResult>* results) { | ||
| int64_t num_point_dim = 5; | ||
| int with_timelag = 0; | ||
| if (!preprocessor_.Run(points_dir, num_point_dim, with_timelag, | ||
| reused_input_tensors_)) { | ||
| FDERROR << "Failed to preprocess the input image." << std::endl; | ||
| return false; | ||
| } | ||
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| results->resize(reused_input_tensors_.size()); | ||
| for (int index = 0; index < reused_input_tensors_.size(); ++index) { | ||
| std::vector<FDTensor> input_tensor; | ||
| input_tensor.push_back(reused_input_tensors_[index]); | ||
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| input_tensor[0].name = InputInfoOfRuntime(0).name; | ||
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| if (!Infer(input_tensor, &reused_output_tensors_)) { | ||
| FDERROR << "Failed to inference by runtime." << std::endl; | ||
| return false; | ||
| } | ||
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| (*results)[index].Clear(); | ||
| (*results)[index].Reserve(reused_output_tensors_[0].shape[0]); | ||
| if (!postprocessor_.Run(reused_output_tensors_, &((*results)[index]))) { | ||
| FDERROR << "Failed to postprocess the inference results by runtime." | ||
| << std::endl; | ||
| return false; | ||
| } | ||
| } | ||
| return true; | ||
| } | ||
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| } // namespace perception | ||
| } // namespace vision | ||
| } // namespace fastdeploy |
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