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// ----------------------------------------------------------------------------
// - Open3D: www.open3d.org -
// ----------------------------------------------------------------------------
// The MIT License (MIT)
//
// Copyright (c) 2018-2021 www.open3d.org
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
// IN THE SOFTWARE.
// ----------------------------------------------------------------------------
#include "open3d/ml/contrib/IoU.h"
#include "open3d/core/TensorCheck.h"
#include "open3d/utility/Logging.h"
#include "pybind/core/tensor_converter.h"
#include "pybind/docstring.h"
#include "pybind/ml/contrib/contrib.h"
#include "pybind/open3d_pybind.h"
#include "pybind/pybind_utils.h"
namespace open3d {
namespace ml {
namespace contrib {
py::array IouBevCPU(py::array boxes_a, py::array boxes_b) {
core::Tensor boxes_a_tensor =
core::PyArrayToTensor(boxes_a, true).Contiguous();
core::AssertTensorDtype(boxes_a_tensor, core::Float32);
core::AssertTensorShape(boxes_a_tensor, {utility::nullopt, 5});
int64_t num_a = boxes_a_tensor.GetLength();
core::Tensor boxes_b_tensor =
core::PyArrayToTensor(boxes_b, true).Contiguous();
core::AssertTensorDtype(boxes_b_tensor, core::Float32);
core::AssertTensorShape(boxes_b_tensor, {utility::nullopt, 5});
int64_t num_b = boxes_b_tensor.GetLength();
core::Tensor iou_tensor = core::Tensor(
{boxes_a_tensor.GetLength(), boxes_b_tensor.GetLength()},
core::Float32, core::Device("CPU:0"));
IoUBevCPUKernel(boxes_a_tensor.GetDataPtr<float>(),
boxes_b_tensor.GetDataPtr<float>(),
iou_tensor.GetDataPtr<float>(), num_a, num_b);
return core::TensorToPyArray(iou_tensor);
}
py::array Iou3dCPU(py::array boxes_a, py::array boxes_b) {
core::Tensor boxes_a_tensor =
core::PyArrayToTensor(boxes_a, true).Contiguous();
core::AssertTensorDtype(boxes_a_tensor, core::Float32);
core::AssertTensorShape(boxes_a_tensor, {utility::nullopt, 7});
int64_t num_a = boxes_a_tensor.GetLength();
core::Tensor boxes_b_tensor =
core::PyArrayToTensor(boxes_b, true).Contiguous();
core::AssertTensorDtype(boxes_b_tensor, core::Float32);
core::AssertTensorShape(boxes_b_tensor, {utility::nullopt, 7});
int64_t num_b = boxes_b_tensor.GetLength();
core::Tensor iou_tensor = core::Tensor(
{boxes_a_tensor.GetLength(), boxes_b_tensor.GetLength()},
core::Float32, core::Device("CPU:0"));
IoU3dCPUKernel(boxes_a_tensor.GetDataPtr<float>(),
boxes_b_tensor.GetDataPtr<float>(),
iou_tensor.GetDataPtr<float>(), num_a, num_b);
return core::TensorToPyArray(iou_tensor);
}
#ifdef BUILD_CUDA_MODULE
py::array IouBevCUDA(py::array boxes_a, py::array boxes_b) {
core::Device cuda_device("CUDA:0");
core::Tensor boxes_a_tensor =
core::PyArrayToTensor(boxes_a, true).Contiguous().To(cuda_device);
core::AssertTensorDtype(boxes_a_tensor, core::Float32);
core::AssertTensorShape(boxes_a_tensor, {utility::nullopt, 5});
int64_t num_a = boxes_a_tensor.GetLength();
core::Tensor boxes_b_tensor =
core::PyArrayToTensor(boxes_b, true).Contiguous().To(cuda_device);
core::AssertTensorDtype(boxes_b_tensor, core::Float32);
core::AssertTensorShape(boxes_b_tensor, {utility::nullopt, 5});
int64_t num_b = boxes_b_tensor.GetLength();
core::Tensor iou_tensor = core::Tensor(
{boxes_a_tensor.GetLength(), boxes_b_tensor.GetLength()},
core::Float32, cuda_device);
IoUBevCUDAKernel(boxes_a_tensor.GetDataPtr<float>(),
boxes_b_tensor.GetDataPtr<float>(),
iou_tensor.GetDataPtr<float>(), num_a, num_b);
return core::TensorToPyArray(iou_tensor.To(core::Device("CPU:0")));
}
py::array Iou3dCUDA(py::array boxes_a, py::array boxes_b) {
core::Device cuda_device("CUDA:0");
core::Tensor boxes_a_tensor =
core::PyArrayToTensor(boxes_a, true).Contiguous().To(cuda_device);
core::AssertTensorDtype(boxes_a_tensor, core::Float32);
core::AssertTensorShape(boxes_a_tensor, {utility::nullopt, 7});
int64_t num_a = boxes_a_tensor.GetLength();
core::Tensor boxes_b_tensor =
core::PyArrayToTensor(boxes_b, true).Contiguous().To(cuda_device);
core::AssertTensorDtype(boxes_b_tensor, core::Float32);
core::AssertTensorShape(boxes_b_tensor, {utility::nullopt, 7});
int64_t num_b = boxes_b_tensor.GetLength();
core::Tensor iou_tensor = core::Tensor(
{boxes_a_tensor.GetLength(), boxes_b_tensor.GetLength()},
core::Float32, cuda_device);
IoU3dCUDAKernel(boxes_a_tensor.GetDataPtr<float>(),
boxes_b_tensor.GetDataPtr<float>(),
iou_tensor.GetDataPtr<float>(), num_a, num_b);
return core::TensorToPyArray(iou_tensor.To(core::Device("CPU:0")));
}
#endif
void pybind_contrib_iou(py::module& m_contrib) {
m_contrib.def("iou_bev_cpu", &IouBevCPU, "boxes_a"_a, "boxes_b"_a);
m_contrib.def("iou_3d_cpu", &Iou3dCPU, "boxes_a"_a, "boxes_b"_a);
#ifdef BUILD_CUDA_MODULE
// These CUDA functions still uses numpy arrays as input and output, i.e.
// data will be copy to and from the CUDA device.
m_contrib.def("iou_bev_cuda", &IouBevCUDA, "boxes_a"_a, "boxes_b"_a);
m_contrib.def("iou_3d_cuda", &Iou3dCUDA, "boxes_a"_a, "boxes_b"_a);
#endif
}
} // namespace contrib
} // namespace ml
} // namespace open3d
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