mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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123 lines
4.9 KiB
C++
123 lines
4.9 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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#if defined(WITH_GPU)
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#include <cuda.h>
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#include <cuda_runtime_api.h>
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#if defined(PADDLEINFERENCE_API_COMPAT_2_4_x)
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#include "paddle/include/experimental/ext_all.h"
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#elif defined(PADDLEINFERENCE_API_COMPAT_2_5_x)
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#include "paddle/include/paddle/extension.h"
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#else
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#include "paddle/extension.h"
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#endif
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namespace fastdeploy {
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namespace paddle_custom_ops {
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std::vector<paddle::Tensor> postprocess_gpu(
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const std::vector<paddle::Tensor> &hm,
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const std::vector<paddle::Tensor> ®,
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const std::vector<paddle::Tensor> &height,
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const std::vector<paddle::Tensor> &dim,
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const std::vector<paddle::Tensor> &vel,
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const std::vector<paddle::Tensor> &rot,
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const std::vector<float> &voxel_size,
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const std::vector<float> &point_cloud_range,
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const std::vector<float> &post_center_range,
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const std::vector<int> &num_classes, const int down_ratio,
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const float score_threshold, const float nms_iou_threshold,
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const int nms_pre_max_size, const int nms_post_max_size,
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const bool with_velocity);
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std::vector<paddle::Tensor> centerpoint_postprocess(
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const std::vector<paddle::Tensor> &hm,
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const std::vector<paddle::Tensor> ®,
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const std::vector<paddle::Tensor> &height,
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const std::vector<paddle::Tensor> &dim,
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const std::vector<paddle::Tensor> &vel,
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const std::vector<paddle::Tensor> &rot,
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const std::vector<float> &voxel_size,
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const std::vector<float> &point_cloud_range,
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const std::vector<float> &post_center_range,
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const std::vector<int> &num_classes, const int down_ratio,
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const float score_threshold, const float nms_iou_threshold,
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const int nms_pre_max_size, const int nms_post_max_size,
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const bool with_velocity) {
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if (hm[0].is_gpu()) {
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return postprocess_gpu(hm, reg, height, dim, vel, rot, voxel_size,
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point_cloud_range, post_center_range, num_classes,
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down_ratio, score_threshold, nms_iou_threshold,
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nms_pre_max_size, nms_post_max_size, with_velocity);
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} else {
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PD_THROW(
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"Unsupported device type for centerpoint postprocess "
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"operator.");
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}
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}
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std::vector<std::vector<int64_t>> PostProcessInferShape(
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const std::vector<std::vector<int64_t>> &hm_shape,
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const std::vector<std::vector<int64_t>> ®_shape,
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const std::vector<std::vector<int64_t>> &height_shape,
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const std::vector<std::vector<int64_t>> &dim_shape,
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const std::vector<std::vector<int64_t>> &vel_shape,
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const std::vector<std::vector<int64_t>> &rot_shape,
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const std::vector<float> &voxel_size,
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const std::vector<float> &point_cloud_range,
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const std::vector<float> &post_center_range,
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const std::vector<int> &num_classes, const int down_ratio,
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const float score_threshold, const float nms_iou_threshold,
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const int nms_pre_max_size, const int nms_post_max_size,
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const bool with_velocity) {
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if (with_velocity) {
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return {{-1, 9}, {-1}, {-1}};
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} else {
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return {{-1, 7}, {-1}, {-1}};
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}
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}
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std::vector<paddle::DataType> PostProcessInferDtype(
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const std::vector<paddle::DataType> &hm_dtype,
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const std::vector<paddle::DataType> ®_dtype,
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const std::vector<paddle::DataType> &height_dtype,
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const std::vector<paddle::DataType> &dim_dtype,
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const std::vector<paddle::DataType> &vel_dtype,
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const std::vector<paddle::DataType> &rot_dtype) {
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return {reg_dtype[0], hm_dtype[0], paddle::DataType::INT64};
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}
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} // namespace fastdeploy
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} // namespace paddle_custom_ops
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PD_BUILD_OP(centerpoint_postprocess)
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.Inputs({paddle::Vec("HM"), paddle::Vec("REG"), paddle::Vec("HEIGHT"),
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paddle::Vec("DIM"), paddle::Vec("VEL"), paddle::Vec("ROT")})
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.Outputs({"BBOXES", "SCORES", "LABELS"})
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.SetKernelFn(PD_KERNEL(fastdeploy::paddle_custom_ops::centerpoint_postprocess))
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.Attrs({"voxel_size: std::vector<float>",
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"point_cloud_range: std::vector<float>",
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"post_center_range: std::vector<float>",
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"num_classes: std::vector<int>", "down_ratio: int",
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"score_threshold: float", "nms_iou_threshold: float",
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"nms_pre_max_size: int", "nms_post_max_size: int",
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"with_velocity: bool"})
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.SetInferShapeFn(PD_INFER_SHAPE(fastdeploy::paddle_custom_ops::PostProcessInferShape))
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.SetInferDtypeFn(PD_INFER_DTYPE(fastdeploy::paddle_custom_ops::PostProcessInferDtype));
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#endif // WITH_GPU
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