Files
FastDeploy/fastdeploy/pybind/main.h
huangjianhui b565c15bf7 [Model] Add tinypose single && pipeline model (#177)
* Add tinypose model

* Add PPTinypose python API

* Fix picodet preprocess bug && Add Tinypose examples

* Update tinypose example code

* Update ppseg preprocess if condition

* Update ppseg backend support type

* Update permute.h

* Update README.md

* Update code with comments

* Move files dir

* Delete premute.cc

* Add single model pptinypose

* Delete pptinypose old code in ppdet

* Code format

* Add ppdet + pptinypose pipeline model

* Fix bug for posedetpipeline

* Change Frontend to ModelFormat

* Change Frontend to ModelFormat in __init__.py

* Add python posedetpipeline/

* Update pptinypose example dir name

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Create keypointdetection_result.md

* Create README.md

* Create README.md

* Create README.md

* Update README.md

* Update README.md

* Create README.md

* Fix det_keypoint_unite_infer.py bug

* Create README.md

* Update PP-Tinypose by comment

* Update by comment

* Add pipeline directory

* Add pptinypose dir

* Update pptinypose to align accuracy

* Addd warpAffine processor

* Update GetCpuMat to  GetOpenCVMat

* Add comment for pptinypose && pipline

* Update docs/main_page.md

* Add README.md for pptinypose

* Add README for det_keypoint_unite

* Remove ENABLE_PIPELINE option

* Remove ENABLE_PIPELINE option

* Change pptinypose default backend

* PP-TinyPose Pipeline support multi PP-Detection models

* Update pp-tinypose comment

* Update by comments

* Add single test example

Co-authored-by: Jason <jiangjiajun@baidu.com>
2022-10-21 09:28:23 +08:00

134 lines
4.2 KiB
C++

// 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.
#pragma once
#include <pybind11/numpy.h>
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
#include <type_traits>
#include "fastdeploy/runtime.h"
#ifdef ENABLE_VISION
#include "fastdeploy/vision.h"
#include "fastdeploy/pipeline.h"
#endif
#ifdef ENABLE_TEXT
#include "fastdeploy/text.h"
#endif
#include "fastdeploy/core/float16.h"
namespace fastdeploy {
void BindBackend(pybind11::module&);
void BindVision(pybind11::module&);
void BindText(pybind11::module& m);
void BindPipeline(pybind11::module& m);
pybind11::dtype FDDataTypeToNumpyDataType(const FDDataType& fd_dtype);
FDDataType NumpyDataTypeToFDDataType(const pybind11::dtype& np_dtype);
void PyArrayToTensor(pybind11::array& pyarray, FDTensor* tensor,
bool share_buffer = false);
void PyArrayToTensorList(std::vector<pybind11::array>& pyarray,
std::vector<FDTensor>* tensor,
bool share_buffer = false);
pybind11::array TensorToPyArray(const FDTensor& tensor);
#ifdef ENABLE_VISION
cv::Mat PyArrayToCvMat(pybind11::array& pyarray);
#endif
template <typename T>
FDDataType CTypeToFDDataType() {
if (std::is_same<T, int32_t>::value) {
return FDDataType::INT32;
} else if (std::is_same<T, int64_t>::value) {
return FDDataType::INT64;
} else if (std::is_same<T, float>::value) {
return FDDataType::FP32;
} else if (std::is_same<T, double>::value) {
return FDDataType::FP64;
}
FDASSERT(false,
"CTypeToFDDataType only support int32/int64/float32/float64 now.");
return FDDataType::FP32;
}
template <typename T>
std::vector<pybind11::array> PyBackendInfer(
T& self, const std::vector<std::string>& names,
std::vector<pybind11::array>& data) {
std::vector<FDTensor> inputs(data.size());
for (size_t i = 0; i < data.size(); ++i) {
// TODO(jiangjiajun) here is considered to use user memory directly
auto dtype = NumpyDataTypeToFDDataType(data[i].dtype());
std::vector<int64_t> data_shape;
data_shape.insert(data_shape.begin(), data[i].shape(),
data[i].shape() + data[i].ndim());
inputs[i].Resize(data_shape, dtype);
memcpy(inputs[i].MutableData(), data[i].mutable_data(), data[i].nbytes());
inputs[i].name = names[i];
}
std::vector<FDTensor> outputs(self.NumOutputs());
self.Infer(inputs, &outputs);
std::vector<pybind11::array> results;
results.reserve(outputs.size());
for (size_t i = 0; i < outputs.size(); ++i) {
auto numpy_dtype = FDDataTypeToNumpyDataType(outputs[i].dtype);
results.emplace_back(pybind11::array(numpy_dtype, outputs[i].shape));
memcpy(results[i].mutable_data(), outputs[i].Data(),
outputs[i].Numel() * FDDataTypeSize(outputs[i].dtype));
}
return results;
}
} // namespace fastdeploy
namespace pybind11 {
namespace detail {
// Note: use same enum number of float16 in numpy.
// import numpy as np
// print np.dtype(np.float16).num # 23
constexpr int NPY_FLOAT16_ = 23;
// Note: Since float16 is not a builtin type in C++, we register
// fastdeploy::float16 as numpy.float16.
// Ref: https://github.com/pybind/pybind11/issues/1776
template <>
struct npy_format_descriptor<fastdeploy::float16> {
static pybind11::dtype dtype() {
handle ptr = npy_api::get().PyArray_DescrFromType_(NPY_FLOAT16_);
return reinterpret_borrow<pybind11::dtype>(ptr);
}
static std::string format() {
// Note: "e" represents float16.
// Details at:
// https://docs.python.org/3/library/struct.html#format-characters.
return "e";
}
static constexpr auto name = _("float16");
};
} // namespace detail
} // namespace pybind11