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openpose

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提交 665b23e5 编写于 作者: G gineshidalgo99
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Removed boost and caffe deps from headers

上级 ee10cec8
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.github/issue_template.md
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...@@ -48,6 +48,7 @@ You might select multiple topics, delete the rest: ...@@ -48,6 +48,7 @@ You might select multiple topics, delete the rest:
3. **General configuration**: 3. **General configuration**:
- **Installation mode**: CMake, sh script, manual Makefile installation, ... (Ubuntu); CMake, ... (Windows); ...? - **Installation mode**: CMake, sh script, manual Makefile installation, ... (Ubuntu); CMake, ... (Windows); ...?
- **Operating system** (`lsb_release -a` in Ubuntu): - **Operating system** (`lsb_release -a` in Ubuntu):
- **Operating system version** (e.g., Ubuntu 16, Windows 10, ...):
- **Release or Debug mode**? (by default: release): - **Release or Debug mode**? (by default: release):
- Compiler (`gcc --version` in Ubuntu or VS version in Windows): 5.4.0, ... (Ubuntu); VS2015 Enterprise Update 3, VS2017 community, ... (Windows); ...? - Compiler (`gcc --version` in Ubuntu or VS version in Windows): 5.4.0, ... (Ubuntu); VS2015 Enterprise Update 3, VS2017 community, ... (Windows); ...?
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README.md
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...@@ -4,8 +4,8 @@ ...@@ -4,8 +4,8 @@
----------------- -----------------
| | `Python (CUDA GPU)` | `Python (CPU)` | `CUDA GPU` | `CPU` | `Debug mode` | | | `Python (CUDA GPU)` | `Python (CPU)` | `CUDA GPU` | `CPU` | `Debug mode` |
| :---: | :---: | :---: | :---: |:---: | :---: | | :---: | :---: | :---: | :---: |:---: | :---: |
| **`Linux`** | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/1)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/2)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/3)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/4)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/5)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) | | **`Linux`** | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/1)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/2)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/3)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/4)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/5)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) |
| **`MacOS`** | | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/6)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) | | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/7)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/8)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) | | **`MacOS`** | | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/6)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) | | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/7)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) | [![Status](https://travis-matrix-badges.herokuapp.com/repos/CMU-Perceptual-Computing-Lab/openpose/branches/master/8)](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose) |
<!-- | **`Windows`** | | | | | | --> <!-- | **`Windows`** | | | | | | -->
...@@ -46,7 +46,7 @@ It is **authored by [Gines Hidalgo](https://www.gineshidalgo.com), [Zhe Cao](htt ...@@ -46,7 +46,7 @@ It is **authored by [Gines Hidalgo](https://www.gineshidalgo.com), [Zhe Cao](htt
- Available: command-line demo, C++ wrapper, and C++ API. - Available: command-line demo, C++ wrapper, and C++ API.
- [**Python API**](doc/modules/python_module.md). - [**Python API**](doc/modules/python_module.md).
- [**Unity Plugin**](https://github.com/CMU-Perceptual-Computing-Lab/openpose_unity_plugin). - [**Unity Plugin**](https://github.com/CMU-Perceptual-Computing-Lab/openpose_unity_plugin).
- CUDA (Nvidia GPU), OpenCL (AMD GPU), and CPU versions. - CUDA (Nvidia GPU), OpenCL (AMD GPU), and CPU-only (no GPU) versions.
- Training code included in the [**original CVPR 2017 GitHub repository**](https://github.com/ZheC/Multi-Person-Pose-Estimation). - Training code included in the [**original CVPR 2017 GitHub repository**](https://github.com/ZheC/Multi-Person-Pose-Estimation).
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doc/installation.md
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...@@ -48,14 +48,14 @@ This installation section is only intended if you plan to modify the OpenPose co ...@@ -48,14 +48,14 @@ This installation section is only intended if you plan to modify the OpenPose co
## Requirements and Dependencies ## Requirements and Dependencies
- **Requirements** for the default configuration (you might need more resources with a greater `--net_resolution` and/or `scale_number` or less resources by reducing the net resolution and/or using the MPI and MPI_4 models): - **Requirements** for the default configuration (you might need more resources with a greater `--net_resolution` and/or `scale_number` or less resources by reducing the net resolution and/or using the MPI and MPI_4 models):
- Nvidia GPU version: - CUDA (Nvidia GPU) version:
- NVIDIA graphics card with at least 1.6 GB available (the `nvidia-smi` command checks the available GPU memory in Ubuntu). - NVIDIA graphics card with at least 1.6 GB available (the `nvidia-smi` command checks the available GPU memory in Ubuntu).
- At least 2.5 GB of free RAM memory for BODY_25 model or 2 GB for COCO model (assuming cuDNN installed). - At least 2.5 GB of free RAM memory for BODY_25 model or 2 GB for COCO model (assuming cuDNN installed).
- Highly recommended: cuDNN. - Highly recommended: cuDNN.
- AMD GPU version: - OpenCL (AMD GPU) version:
- Vega series graphics card - Vega series graphics card
- At least 2 GB of free RAM memory. - At least 2 GB of free RAM memory.
- CPU version: - CPU-only (no GPU) version:
- Around 8GB of free RAM memory. - Around 8GB of free RAM memory.
- Highly recommended: a CPU with at least 8 cores. - Highly recommended: a CPU with at least 8 cores.
- **Dependencies**: - **Dependencies**:
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doc/modules/python_module.md
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...@@ -18,7 +18,7 @@ This module exposes a Python API for OpenPose. It is effectively a wrapper that ...@@ -18,7 +18,7 @@ This module exposes a Python API for OpenPose. It is effectively a wrapper that
## Compatibility ## Compatibility
The OpenPose Python module is compatible with both Python 2 and Python 3 (default and recommended). In addition, it will also run in all OpenPose compatible operating systems. It uses [Pybind11](https://github.com/pybind/pybind11) for mapping between C++ and Python datatypes. The OpenPose Python module is compatible with both Python 2 and Python 3 (default and recommended). In addition, it will also run in all OpenPose compatible operating systems. It uses [Pybind11](https://github.com/pybind/pybind11) for mapping between C++ and Python datatypes.
To compile, enable `BUILD_PYTHON` in CMake-gui. In Windows, make sure you compile the whole solution (clicking the green play button does not compile the whole solution!). You can do that by right-click on the OpenPose project solution, and clicking in `Build solution`. To compile, enable `BUILD_PYTHON` in CMake-gui. In Windows, make sure you compile the whole solution (clicking the green play button does not compile the whole solution!). You can do that by right-click on the OpenPose project solution, and clicking in `Build Solution` (or individually building the PyOpenPose module).
Pybind selects the latest version of Python by default (Python 3). To use Python 2, change `PYTHON_EXECUTABLE` and `PYTHON_LIBRARY` flags in CMake-gui to your desired Python version. Pybind selects the latest version of Python by default (Python 3). To use Python 2, change `PYTHON_EXECUTABLE` and `PYTHON_LIBRARY` flags in CMake-gui to your desired Python version.
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doc/release_notes.md
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...@@ -316,6 +316,7 @@ OpenPose Library - Release Notes ...@@ -316,6 +316,7 @@ OpenPose Library - Release Notes
33. Added the flags `--face_detector` and `--hand_detector`, that enable the user to select the face/hand rectangle detector that is used for the later face/hand keypoint detection. It includes OpenCV (for face), and also allows the user to provide its own input. Flag `--hand_tracking` is removed and integrated into this flag too. 33. Added the flags `--face_detector` and `--hand_detector`, that enable the user to select the face/hand rectangle detector that is used for the later face/hand keypoint detection. It includes OpenCV (for face), and also allows the user to provide its own input. Flag `--hand_tracking` is removed and integrated into this flag too.
34. Maximum queue size per OpenPose thread is configurable through the Wrapper class. 34. Maximum queue size per OpenPose thread is configurable through the Wrapper class.
35. Added pre-processing capabilities to Wrapper (WorkerType::PreProcessing), which will be run right after the image has been read. 35. Added pre-processing capabilities to Wrapper (WorkerType::PreProcessing), which will be run right after the image has been read.
36. Removed boost::shared_ptr and caffe::Blob dependencies from the headers. No 3rdparty dependencies left on headers (except dim3 for CUDA).
2. Functions or parameters renamed: 2. Functions or parameters renamed:
1. By default, python example `tutorial_developer/python_2_pose_from_heatmaps.py` was using 2 scales starting at -1x736, changed to 1 scale at -1x368. 1. By default, python example `tutorial_developer/python_2_pose_from_heatmaps.py` was using 2 scales starting at -1x736, changed to 1 scale at -1x368.
2. WrapperStructPose default parameters changed to match those of the OpenPose demo binary. 2. WrapperStructPose default parameters changed to match those of the OpenPose demo binary.
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doc/released_features.md
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OpenPose Library - All Released Features OpenPose Library - All Released Features
==================================== ====================================
- Jan 2018: [**Unity plugin released**](https://github.com/CMU-Perceptual-Computing-Lab/openpose_unity_plugin)! - Jan 2019: [**Unity plugin released**](https://github.com/CMU-Perceptual-Computing-Lab/openpose_unity_plugin)!
- Jan 2018: [**Improved Python API**](doc/modules/python_module.md) released! Including body, face, hands, and all the functionality of the C++ API! - Jan 2019: [**Improved Python API**](doc/modules/python_module.md) released! Including body, face, hands, and all the functionality of the C++ API!
- Dec 2018: [**Foot dataset**](https://cmu-perceptual-computing-lab.github.io/foot_keypoint_dataset) and [**new paper released**](https://arxiv.org/abs/1812.08008)! - Dec 2018: [**Foot dataset**](https://cmu-perceptual-computing-lab.github.io/foot_keypoint_dataset) and [**new paper released**](https://arxiv.org/abs/1812.08008)!
- Sep 2018: [**Experimental tracker**](./quick_start.md#tracking)! - Sep 2018: [**Experimental tracker**](./quick_start.md#tracking)!
- Jun 2018: [**Combined body-foot model released! 40% faster and 5% more accurate**](./installation.md)! - Jun 2018: [**Combined body-foot model released! 40% faster and 5% more accurate**](./installation.md)!
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examples/tests/clTest.cpp
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...@@ -5,6 +5,10 @@ ...@@ -5,6 +5,10 @@
#include <openpose/flags.hpp> #include <openpose/flags.hpp>
// OpenPose dependencies // OpenPose dependencies
#include <openpose/headers.hpp> #include <openpose/headers.hpp>
// Caffe dependencies
#ifdef USE_CAFFE
#include <caffe/blob.hpp>
#endif
// OpenCL dependencies // OpenCL dependencies
#ifdef USE_OPENCL #ifdef USE_OPENCL
#include <openpose/gpu/opencl.hcl> #include <openpose/gpu/opencl.hcl>
...@@ -72,7 +76,8 @@ DEFINE_string(image_path, "examples/media/COCO_val2014_00000000019 ...@@ -72,7 +76,8 @@ DEFINE_string(image_path, "examples/media/COCO_val2014_00000000019
typedef cl::KernelFunctor<cl::Buffer, int, int, float> ScaleFunctor; typedef cl::KernelFunctor<cl::Buffer, int, int, float> ScaleFunctor;
const std::string scaleKernelString = MULTI_LINE_STRING( const std::string scaleKernelString = MULTI_LINE_STRING(
__kernel void scaleKernel(__global float* targetPtr, const int targetWidth, const int targetHeight, const float scale) __kernel void scaleKernel(__global float* targetPtr, const int targetWidth, const int targetHeight,
const float scale)
{ {
int x = get_global_id(0); int x = get_global_id(0);
int y = get_global_id(1); int y = get_global_id(1);
...@@ -111,7 +116,8 @@ int clTest() ...@@ -111,7 +116,8 @@ int clTest()
std::unique_ptr<caffe::Net<float>> upCaffeNet; std::unique_ptr<caffe::Net<float>> upCaffeNet;
caffe::Caffe::set_mode(caffe::Caffe::GPU); caffe::Caffe::set_mode(caffe::Caffe::GPU);
caffe::Caffe::SelectDevice(0, true); caffe::Caffe::SelectDevice(0, true);
upCaffeNet.reset(new caffe::Net<float>{"models/pose/coco/pose_deploy_linevec.prototxt", caffe::TEST, caffe::Caffe::GetDefaultDevice()}); upCaffeNet.reset(new caffe::Net<float>{
"models/pose/coco/pose_deploy_linevec.prototxt", caffe::TEST, caffe::Caffe::GetDefaultDevice()});
upCaffeNet->CopyTrainedLayersFrom("models/pose/coco/pose_iter_440000.caffemodel"); upCaffeNet->CopyTrainedLayersFrom("models/pose/coco/pose_iter_440000.caffemodel");
op::OpenCL::getInstance(0, CL_DEVICE_TYPE_GPU, true); op::OpenCL::getInstance(0, CL_DEVICE_TYPE_GPU, true);
...@@ -125,19 +131,16 @@ int clTest() ...@@ -125,19 +131,16 @@ int clTest()
blob_proto.set_height(imgResize.size().width); blob_proto.set_height(imgResize.size().width);
blob_proto.set_width(imgResize.size().height); blob_proto.set_width(imgResize.size().height);
blob_proto.clear_data(); blob_proto.clear_data();
for (int c = 0; c < 3; ++c) { for (int c = 0; c < 3; ++c)
for (int h = 0; h < imgResize.size().height; ++h) { for (int h = 0; h < imgResize.size().height; ++h)
for (int w = 0; w < imgResize.size().width; ++w) { for (int w = 0; w < imgResize.size().width; ++w)
blob_proto.add_data(imgResize.at<cv::Vec3f>(h, w)[c]); blob_proto.add_data(imgResize.at<cv::Vec3f>(h, w)[c]);
}
}
}
blob_proto.set_num(1); blob_proto.set_num(1);
caffe::Blob<float>* input_layer = upCaffeNet->input_blobs()[0]; caffe::Blob<float>* input_layer = upCaffeNet->input_blobs()[0];
input_layer->FromProto(blob_proto); input_layer->FromProto(blob_proto);
upCaffeNet->Forward(0); upCaffeNet->Forward(0);
boost::shared_ptr<caffe::Blob<float> > output_blob = upCaffeNet->blob_by_name("net_output"); boost::shared_ptr<caffe::Blob<float>> output_blob = upCaffeNet->blob_by_name("net_output");
// Test // Test
cl::Device& device = op::OpenCL::getInstance(0)->getDevice(); cl::Device& device = op::OpenCL::getInstance(0)->getDevice();
...@@ -156,8 +159,9 @@ int clTest() ...@@ -156,8 +159,9 @@ int clTest()
// Read it // Read it
// Read back image to GPU // Read back image to GPU
float* heatmaps = new float[output_blob->shape()[1] * output_blob->shape()[2] * output_blob->shape()[3]]; float* heatmaps = new float[output_blob->shape()[1] * output_blob->shape()[2] * output_blob->shape()[3]];
op::OpenCL::getInstance(0)->getQueue().enqueueReadBuffer(outputBuffer, CL_TRUE, 0, op::OpenCL::getInstance(0)->getQueue().enqueueReadBuffer(
output_blob->shape()[1] * output_blob->shape()[2] * output_blob->shape()[3] * sizeof(float), heatmaps); outputBuffer, CL_TRUE, 0,
output_blob->shape()[1] * output_blob->shape()[2] * output_blob->shape()[3] * sizeof(float), heatmaps);
int heatmapChannels = output_blob->shape()[1]; int heatmapChannels = output_blob->shape()[1];
int shape = output_blob->shape()[2] * output_blob->shape()[3]; int shape = output_blob->shape()[2] * output_blob->shape()[3];
...@@ -172,11 +176,11 @@ int clTest() ...@@ -172,11 +176,11 @@ int clTest()
} }
} }
#if defined(USE_OPENCL) && defined(CL_HPP_ENABLE_EXCEPTIONS) #if defined(USE_OPENCL) && defined(CL_HPP_ENABLE_EXCEPTIONS)
catch (const cl::Error& e) catch (const cl::Error& e)
{ {
op::error(std::string(e.what()) + " : " + op::OpenCL::clErrorToString(e.err()) + " ID: " + op::error(std::string(e.what()) + " : " + op::OpenCL::clErrorToString(e.err()) + " ID: " +
std::to_string(0), __LINE__, __FUNCTION__, __FILE__); std::to_string(0), __LINE__, __FUNCTION__, __FILE__);
} }
#endif #endif
catch (const std::exception& e) catch (const std::exception& e)
{ {
...@@ -223,6 +227,6 @@ int main() ...@@ -223,6 +227,6 @@ int main()
#else #else
op::error("OpenPose must be compiled with the `USE_CAFFE` & `USE_OPENCL` macro definitions in order to run" op::error("OpenPose must be compiled with the `USE_CAFFE` & `USE_OPENCL` macro definitions in order to run"
" this functionality.", __LINE__, __FUNCTION__, __FILE__); " this functionality.", __LINE__, __FUNCTION__, __FILE__);
return 0; return -1;
#endif #endif
} }
examples/tests/resizeTest.cpp
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...@@ -15,7 +15,7 @@ ...@@ -15,7 +15,7 @@
cv::Mat gpuResize(cv::Mat& img, const cv::Size& newSize) cv::Mat gpuResize(cv::Mat& img, const cv::Size& newSize)
{ {
#ifdef USE_CUDA #if defined USE_CAFFE && defined USE_CUDA
// Upload to Source to GPU // Upload to Source to GPU
float* cpuPtr = &img.at<float>(0); float* cpuPtr = &img.at<float>(0);
float* gpuPtr; float* gpuPtr;
...@@ -49,6 +49,7 @@ ...@@ -49,6 +49,7 @@
UNUSED(newSize); UNUSED(newSize);
op::error("OpenPose must be compiled with the `USE_CAFFE` & `USE_CUDA` macro definitions in order to run" op::error("OpenPose must be compiled with the `USE_CAFFE` & `USE_CUDA` macro definitions in order to run"
" this functionality.", __LINE__, __FUNCTION__, __FILE__); " this functionality.", __LINE__, __FUNCTION__, __FILE__);
return cv::Mat();
#endif #endif
} }
......
include/openpose/core/arrayCpuGpu.hpp 0 → 100644
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#ifndef OPENPOSE_CORE_ARRAY_CPU_GPU_HPP
#define OPENPOSE_CORE_ARRAY_CPU_GPU_HPP
#include <memory> // std::shared_ptr
#include <vector>
#include <openpose/core/macros.hpp>
namespace op
{
/**
* ArrayCpuGpu<T>: Bind of caffe::Blob<T> to avoid Caffe as dependency in the headers.
*/
template<typename T>
class ArrayCpuGpu
{
public:
ArrayCpuGpu();
explicit ArrayCpuGpu(const void* caffeBlobTPtr);
explicit ArrayCpuGpu(const int num, const int channels, const int height, const int width);
// explicit ArrayCpuGpu(const std::vector<int>& shape);
void Reshape(const int num, const int channels, const int height, const int width);
void Reshape(const std::vector<int>& shape);
// // void Reshape(const BlobShape& shape);
// // void ReshapeLike(const Blob& other);
// void ReshapeLike(const ArrayCpuGpu& other);
std::string shape_string() const;
const std::vector<int>& shape() const;
int shape(const int index) const;
int num_axes() const;
int count() const;
int count(const int start_axis, const int end_axis) const;
int count(const int start_axis) const;
int CanonicalAxisIndex(const int axis_index) const;
// int num() const;
// int channels() const;
// int height() const;
// int width() const;
// int LegacyShape(const int index) const;
// int offset(const int n, const int c = 0, const int h = 0, const int w = 0) const;
// int offset(const std::vector<int>& indices) const;
// // void CopyFrom(const Blob<T>& source, bool copy_diff = false, bool reshape = false);
// void CopyFrom(const ArrayCpuGpu<T>& source, bool copy_diff = false, bool reshape = false);
T data_at(const int n, const int c, const int h, const int w) const;
T diff_at(const int n, const int c, const int h, const int w) const;
// T data_at(const std::vector<int>& index) const; // Caffe warning
// T diff_at(const std::vector<int>& index) const;
// // const boost::shared_ptr<SyncedMemory>& data() const;
// // const boost::shared_ptr<SyncedMemory>& diff() const;
const T* cpu_data() const;
void set_cpu_data(T* data);
const int* gpu_shape() const;
const T* gpu_data() const;
void set_gpu_data(T* data);
const T* cpu_diff() const;
const T* gpu_diff() const;
T* mutable_cpu_data();
T* mutable_gpu_data();
T* mutable_cpu_diff();
T* mutable_gpu_diff();
void Update();
// void FromProto(const BlobProto& proto, bool reshape = true);
// void ToProto(BlobProto* proto, bool write_diff = false) const;
// T asum_data() const;
// T asum_diff() const;
// T sumsq_data() const;
// T sumsq_diff() const;
// void scale_data(T scale_factor);
// void scale_diff(T scale_factor);
// // void ShareData(const Blob& other);
// // void ShareDiff(const Blob& other);
// // bool ShapeEquals(const BlobProto& other);
private:
// PIMPL idiom
// http://www.cppsamples.com/common-tasks/pimpl.html
struct ImplArrayCpuGpu;
std::shared_ptr<ImplArrayCpuGpu> spImpl;
// PIMP requires DELETE_COPY & destructor, or extra code
// http://oliora.github.io/2015/12/29/pimpl-and-rule-of-zero.html
DELETE_COPY(ArrayCpuGpu);
};
// // Static methods
// OVERLOAD_C_OUT(ArrayCpuGpu)
}
#endif // OPENPOSE_CORE_ARRAY_CPU_GPU_HPP
include/openpose/core/common.hpp
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...@@ -8,6 +8,7 @@ ...@@ -8,6 +8,7 @@
#include <vector> #include <vector>
// OpenPose most used classes // OpenPose most used classes
#include <openpose/core/array.hpp> #include <openpose/core/array.hpp>
#include <openpose/core/arrayCpuGpu.hpp>
#include <openpose/core/macros.hpp> #include <openpose/core/macros.hpp>
#include <openpose/core/point.hpp> #include <openpose/core/point.hpp>
#include <openpose/core/rectangle.hpp> #include <openpose/core/rectangle.hpp>
......
include/openpose/core/headers.hpp
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...@@ -3,6 +3,7 @@ ...@@ -3,6 +3,7 @@
// core module // core module
#include <openpose/core/array.hpp> #include <openpose/core/array.hpp>
#include <openpose/core/arrayCpuGpu.hpp>
#include <openpose/core/common.hpp> #include <openpose/core/common.hpp>
#include <openpose/core/cvMatToOpInput.hpp> #include <openpose/core/cvMatToOpInput.hpp>
#include <openpose/core/cvMatToOpOutput.hpp> #include <openpose/core/cvMatToOpOutput.hpp>
......
include/openpose/core/macros.hpp
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...@@ -54,6 +54,24 @@ const std::string OPEN_POSE_NAME_AND_VERSION = OPEN_POSE_NAME_STRING + " " + OPE ...@@ -54,6 +54,24 @@ const std::string OPEN_POSE_NAME_AND_VERSION = OPEN_POSE_NAME_STRING + " " + OPE
template classType OP_API className<double>; \ template classType OP_API className<double>; \
template classType OP_API className<long double> template classType OP_API className<long double>
// Instantiate a class with float and double specifications
#define COMPILE_TEMPLATE_FLOATING_TYPES_CLASS(className) COMPILE_TEMPLATE_FLOATING_TYPES(className, class)
#define COMPILE_TEMPLATE_FLOATING_TYPES_STRUCT(className) COMPILE_TEMPLATE_FLOATING_TYPES(className, struct)
#define COMPILE_TEMPLATE_FLOATING_TYPES(className, classType) \
char gInstantiationGuard##className; \
template classType OP_API className<float>; \
template classType OP_API className<double>
// Instantiate a class with float and double specifications
#define COMPILE_TEMPLATE_FLOATING_INT_TYPES_CLASS(className) COMPILE_TEMPLATE_FLOATING_INT_TYPES(className, class)
#define COMPILE_TEMPLATE_FLOATING_INT_TYPES_STRUCT(className) COMPILE_TEMPLATE_FLOATING_INT_TYPES(className, struct)
#define COMPILE_TEMPLATE_FLOATING_INT_TYPES(className, classType) \
char gInstantiationGuard##className; \
template classType OP_API className<int>; \
template classType OP_API className<unsigned int>; \
template classType OP_API className<float>; \
template classType OP_API className<double>
/** /**
* cout operator overload calling toString() function * cout operator overload calling toString() function
* @return std::ostream containing output from toString() * @return std::ostream containing output from toString()
...@@ -65,25 +83,9 @@ const std::string OPEN_POSE_NAME_AND_VERSION = OPEN_POSE_NAME_STRING + " " + OPE ...@@ -65,25 +83,9 @@ const std::string OPEN_POSE_NAME_AND_VERSION = OPEN_POSE_NAME_STRING + " " + OPE
return ostream; \ return ostream; \
} }
// Instantiate a class with float and double specifications
#define COMPILE_TEMPLATE_FLOATING_TYPES_CLASS(className) COMPILE_TEMPLATE_FLOATING_TYPES(className, class)
#define COMPILE_TEMPLATE_FLOATING_TYPES_STRUCT(className) COMPILE_TEMPLATE_FLOATING_TYPES(className, struct)
#define COMPILE_TEMPLATE_FLOATING_TYPES(className, classType) \
char gInstantiationGuard##className; \
template classType OP_API className<float>; \
template classType OP_API className<double>
// PIMPL does not work if function arguments need the 3rd-party class. Alternative: // PIMPL does not work if function arguments need the 3rd-party class. Alternative:
// stackoverflow.com/questions/13978775/how-to-avoid-include-dependency-to-external-library?answertab=active#tab-top // stackoverflow.com/questions/13978775/how-to-avoid-include-dependency-to-external-library?answertab=active#tab-top
struct dim3; struct dim3;
namespace caffe
{
template <typename T> class Blob;
}
namespace boost
{
template <typename T> class shared_ptr; // E.g., boost::shared_ptr<caffe::Blob<float>>
}
// Compabitility for OpenCV 4.0 while preserving 2.4.X and 3.X compatibility // Compabitility for OpenCV 4.0 while preserving 2.4.X and 3.X compatibility
// Note: // Note:
......
include/openpose/net/bodyPartConnectorCaffe.hpp
浏览文件 @ 665b23e5
...@@ -17,7 +17,7 @@ namespace op ...@@ -17,7 +17,7 @@ namespace op
virtual ~BodyPartConnectorCaffe(); virtual ~BodyPartConnectorCaffe();
virtual void Reshape(const std::vector<caffe::Blob<T>*>& bottom, const int gpuID = 0); virtual void Reshape(const std::vector<ArrayCpuGpu<T>*>& bottom, const int gpuID = 0);
virtual inline const char* type() const { return "BodyPartConnector"; } virtual inline const char* type() const { return "BodyPartConnector"; }
...@@ -35,23 +35,23 @@ namespace op ...@@ -35,23 +35,23 @@ namespace op
void setScaleNetToOutput(const T scaleNetToOutput); void setScaleNetToOutput(const T scaleNetToOutput);
virtual void Forward(const std::vector<caffe::Blob<T>*>& bottom, Array<T>& poseKeypoints, virtual void Forward(const std::vector<ArrayCpuGpu<T>*>& bottom, Array<T>& poseKeypoints,
Array<T>& poseScores); Array<T>& poseScores);
virtual void Forward_cpu(const std::vector<caffe::Blob<T>*>& bottom, Array<T>& poseKeypoints, virtual void Forward_cpu(const std::vector<ArrayCpuGpu<T>*>& bottom, Array<T>& poseKeypoints,
Array<T>& poseScores); Array<T>& poseScores);
virtual void Forward_gpu(const std::vector<caffe::Blob<T>*>& bottom, Array<T>& poseKeypoints, virtual void Forward_gpu(const std::vector<ArrayCpuGpu<T>*>& bottom, Array<T>& poseKeypoints,
Array<T>& poseScores); Array<T>& poseScores);
virtual void Forward_ocl(const std::vector<caffe::Blob<T>*>& bottom, Array<T>& poseKeypoints, virtual void Forward_ocl(const std::vector<ArrayCpuGpu<T>*>& bottom, Array<T>& poseKeypoints,
Array<T>& poseScores); Array<T>& poseScores);
virtual void Backward_cpu(const std::vector<caffe::Blob<T>*>& top, const std::vector<bool>& propagate_down, virtual void Backward_cpu(const std::vector<ArrayCpuGpu<T>*>& top, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom); const std::vector<ArrayCpuGpu<T>*>& bottom);
virtual void Backward_gpu(const std::vector<caffe::Blob<T>*>& top, const std::vector<bool>& propagate_down, virtual void Backward_gpu(const std::vector<ArrayCpuGpu<T>*>& top, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom); const std::vector<ArrayCpuGpu<T>*>& bottom);
private: private:
PoseModel mPoseModel; PoseModel mPoseModel;
......
include/openpose/net/maximumCaffe.hpp
浏览文件 @ 665b23e5
...@@ -16,23 +16,23 @@ namespace op ...@@ -16,23 +16,23 @@ namespace op
virtual ~MaximumCaffe(); virtual ~MaximumCaffe();
virtual void LayerSetUp(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void LayerSetUp(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual void Reshape(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void Reshape(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual inline const char* type() const { return "Maximum"; } virtual inline const char* type() const { return "Maximum"; }
virtual void Forward(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void Forward(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual void Forward_cpu(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void Forward_cpu(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual void Forward_gpu(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void Forward_gpu(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual void Backward_cpu(const std::vector<caffe::Blob<T>*>& top, const std::vector<bool>& propagate_down, virtual void Backward_cpu(const std::vector<ArrayCpuGpu<T>*>& top, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom); const std::vector<ArrayCpuGpu<T>*>& bottom);
virtual void Backward_gpu(const std::vector<caffe::Blob<T>*>& top, const std::vector<bool>& propagate_down, virtual void Backward_gpu(const std::vector<ArrayCpuGpu<T>*>& top, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom); const std::vector<ArrayCpuGpu<T>*>& bottom);
private: private:
std::array<int, 4> mBottomSize; std::array<int, 4> mBottomSize;
......
include/openpose/net/net.hpp
浏览文件 @ 665b23e5
...@@ -13,6 +13,8 @@ namespace op ...@@ -13,6 +13,8 @@ namespace op
virtual void initializationOnThread() = 0; virtual void initializationOnThread() = 0;
virtual void forwardPass(const Array<float>& inputData) const = 0; virtual void forwardPass(const Array<float>& inputData) const = 0;
virtual std::shared_ptr<ArrayCpuGpu<float>> getOutputBlobArray() const = 0;
}; };
} }
......
include/openpose/net/netCaffe.hpp
浏览文件 @ 665b23e5
...@@ -18,7 +18,7 @@ namespace op ...@@ -18,7 +18,7 @@ namespace op
void forwardPass(const Array<float>& inputNetData) const; void forwardPass(const Array<float>& inputNetData) const;
boost::shared_ptr<caffe::Blob<float>> getOutputBlob() const; std::shared_ptr<ArrayCpuGpu<float>> getOutputBlobArray() const;
private: private:
// PIMPL idiom // PIMPL idiom
......
include/openpose/net/netOpenCv.hpp
浏览文件 @ 665b23e5
...@@ -17,7 +17,7 @@ namespace op ...@@ -17,7 +17,7 @@ namespace op
void forwardPass(const Array<float>& inputNetData) const; void forwardPass(const Array<float>& inputNetData) const;
boost::shared_ptr<caffe::Blob<float>> getOutputBlob() const; std::shared_ptr<ArrayCpuGpu<float>> getOutputBlobArray() const;
private: private:
// PIMPL idiom // PIMPL idiom
......
include/openpose/net/nmsCaffe.hpp
浏览文件 @ 665b23e5
...@@ -16,9 +16,9 @@ namespace op ...@@ -16,9 +16,9 @@ namespace op
virtual ~NmsCaffe(); virtual ~NmsCaffe();
virtual void LayerSetUp(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void LayerSetUp(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual void Reshape(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top, virtual void Reshape(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top,
const int maxPeaks, const int outputChannels = -1, const int gpuID = 0); const int maxPeaks, const int outputChannels = -1, const int gpuID = 0);
virtual inline const char* type() const { return "Nms"; } virtual inline const char* type() const { return "Nms"; }
...@@ -28,19 +28,19 @@ namespace op ...@@ -28,19 +28,19 @@ namespace op
// Empirically gives better results (copied from Matlab original code) // Empirically gives better results (copied from Matlab original code)
void setOffset(const Point<T>& offset); void setOffset(const Point<T>& offset);
virtual void Forward(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void Forward(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual void Forward_cpu(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void Forward_cpu(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual void Forward_gpu(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void Forward_gpu(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual void Forward_ocl(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void Forward_ocl(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual void Backward_cpu(const std::vector<caffe::Blob<T>*>& top, const std::vector<bool>& propagate_down, virtual void Backward_cpu(const std::vector<ArrayCpuGpu<T>*>& top, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom); const std::vector<ArrayCpuGpu<T>*>& bottom);
virtual void Backward_gpu(const std::vector<caffe::Blob<T>*>& top, const std::vector<bool>& propagate_down, virtual void Backward_gpu(const std::vector<ArrayCpuGpu<T>*>& top, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom); const std::vector<ArrayCpuGpu<T>*>& bottom);
private: private:
T mThreshold; T mThreshold;
......
include/openpose/net/resizeAndMergeCaffe.hpp
浏览文件 @ 665b23e5
...@@ -16,9 +16,9 @@ namespace op ...@@ -16,9 +16,9 @@ namespace op
virtual ~ResizeAndMergeCaffe(); virtual ~ResizeAndMergeCaffe();
virtual void LayerSetUp(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void LayerSetUp(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual void Reshape(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top, virtual void Reshape(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top,
const T netFactor, const T scaleFactor, const bool mergeFirstDimension = true, const T netFactor, const T scaleFactor, const bool mergeFirstDimension = true,
const int gpuID = 0); const int gpuID = 0);
...@@ -26,19 +26,19 @@ namespace op ...@@ -26,19 +26,19 @@ namespace op
void setScaleRatios(const std::vector<T>& scaleRatios); void setScaleRatios(const std::vector<T>& scaleRatios);
virtual void Forward(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void Forward(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual void Forward_cpu(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void Forward_cpu(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual void Forward_gpu(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void Forward_gpu(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual void Forward_ocl(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top); virtual void Forward_ocl(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top);
virtual void Backward_cpu(const std::vector<caffe::Blob<T>*>& top, const std::vector<bool>& propagate_down, virtual void Backward_cpu(const std::vector<ArrayCpuGpu<T>*>& top, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom); const std::vector<ArrayCpuGpu<T>*>& bottom);
virtual void Backward_gpu(const std::vector<caffe::Blob<T>*>& top, const std::vector<bool>& propagate_down, virtual void Backward_gpu(const std::vector<ArrayCpuGpu<T>*>& top, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom); const std::vector<ArrayCpuGpu<T>*>& bottom);
private: private:
std::vector<T*> mTempGPUData; std::vector<T*> mTempGPUData;
......
src/openpose/core/CMakeLists.txt
浏览文件 @ 665b23e5
set(CMAKE_CXX_SOURCE_FILE_EXTENSIONS C;M;c++;cc;cpp;cxx;mm;CPP;cl) set(CMAKE_CXX_SOURCE_FILE_EXTENSIONS C;M;c++;cc;cpp;cxx;mm;CPP;cl)
set(SOURCES_OP_CORE set(SOURCES_OP_CORE
array.cpp array.cpp
arrayCpuGpu.cpp
cvMatToOpInput.cpp cvMatToOpInput.cpp
cvMatToOpOutput.cpp cvMatToOpOutput.cpp
datum.cpp datum.cpp
......
src/openpose/core/arrayCpuGpu.cpp 0 → 100644
浏览文件 @ 665b23e5
#ifdef USE_CAFFE
#include <caffe/blob.hpp>
#endif
#include <openpose/utilities/errorAndLog.hpp>
#include <openpose/core/arrayCpuGpu.hpp>
namespace op
{
template<typename T>
struct ArrayCpuGpu<T>::ImplArrayCpuGpu
{
#ifdef USE_CAFFE
std::unique_ptr<caffe::Blob<T>> upCaffeBlobT;
caffe::Blob<T>* pCaffeBlobT;
#endif
};
const std::string constructorErrorMessage = "ArrayCpuGpu class only implemented for Caffe DL framework (enable"
" `USE_CAFFE` in CMake-GUI).";
template<typename T>
ArrayCpuGpu<T>::ArrayCpuGpu()
{
try
{
#ifdef USE_CAFFE
spImpl.reset(new ImplArrayCpuGpu{});
spImpl->upCaffeBlobT.reset(new caffe::Blob<T>{});
spImpl->pCaffeBlobT = spImpl->upCaffeBlobT.get();
#else
error(constructorErrorMessage, __LINE__, __FUNCTION__, __FILE__);
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
}
}
template<typename T>
ArrayCpuGpu<T>::ArrayCpuGpu(const void* caffeBlobTPtr)
{
try
{
#ifdef USE_CAFFE
spImpl.reset(new ImplArrayCpuGpu{});
spImpl->pCaffeBlobT = (caffe::Blob<T>*)caffeBlobTPtr;
#else
UNUSED(caffeBlobTPtr);
error(constructorErrorMessage, __LINE__, __FUNCTION__, __FILE__);
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
}
}
template<typename T>
ArrayCpuGpu<T>::ArrayCpuGpu(const int num, const int channels, const int height, const int width)
{
try
{
#ifdef USE_CAFFE
spImpl.reset(new ImplArrayCpuGpu{});
spImpl->upCaffeBlobT.reset(new caffe::Blob<T>{num, channels, height, width});
spImpl->pCaffeBlobT = spImpl->upCaffeBlobT.get();
#else
UNUSED(num);
UNUSED(channels);
UNUSED(height);
UNUSED(width);
error(constructorErrorMessage, __LINE__, __FUNCTION__, __FILE__);
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
}
}
// template<typename T>
// ArrayCpuGpu<T>::ArrayCpuGpu(const std::vector<int>& shape)
// {
// try
// {
// #ifdef USE_CAFFE
// spImpl.reset(new ImplArrayCpuGpu{});
// spImpl->upCaffeBlobT.reset(new caffe::Blob<T>{shape});
// spImpl->pCaffeBlobT = spImpl->upCaffeBlobT.get();
// #else
// error(constructorErrorMessage, __LINE__, __FUNCTION__, __FILE__);
// #endif
// }
// catch (const std::exception& e)
// {
// error(e.what(), __LINE__, __FUNCTION__, __FILE__);
// }
// }
template<typename T>
void ArrayCpuGpu<T>::Reshape(const int num, const int channels, const int height, const int width)
{
try
{
#ifdef USE_CAFFE
spImpl->pCaffeBlobT->Reshape(num, channels, height, width);
#else
UNUSED(num);
UNUSED(channels);
UNUSED(height);
UNUSED(width);
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
}
}
template<typename T>
void ArrayCpuGpu<T>::Reshape(const std::vector<int>& shape)
{
try
{
#ifdef USE_CAFFE
spImpl->pCaffeBlobT->Reshape(shape);
#else
UNUSED(shape);
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
}
}
template<typename T>
std::string ArrayCpuGpu<T>::shape_string() const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->shape_string();
#else
return "";
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return "";
}
}
std::vector<int> DUMB_VECTOR;
template<typename T>
const std::vector<int>& ArrayCpuGpu<T>::shape() const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->shape();
#else
return DUMB_VECTOR;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return DUMB_VECTOR;
}
}
template<typename T>
int ArrayCpuGpu<T>::shape(const int index) const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->shape(index);
#else
UNUSED(index);
return -1;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return -1;
}
}
template<typename T>
int ArrayCpuGpu<T>::num_axes() const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->num_axes();
#else
return -1;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return -1;
}
}
template<typename T>
int ArrayCpuGpu<T>::count() const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->count();
#else
return -1;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return -1;
}
}
template<typename T>
int ArrayCpuGpu<T>::count(const int start_axis, const int end_axis) const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->count(start_axis, end_axis);
#else
UNUSED(start_axis);
UNUSED(end_axis);
return -1;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return -1;
}
}
template<typename T>
int ArrayCpuGpu<T>::count(const int start_axis) const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->count(start_axis);
#else
UNUSED(start_axis);
return -1;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return -1;
}
}
template<typename T>
int ArrayCpuGpu<T>::CanonicalAxisIndex(const int axis_index) const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->CanonicalAxisIndex(axis_index);
#else
UNUSED(axis_index);
return -1;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return -1;
}
}
template<typename T>
T ArrayCpuGpu<T>::data_at(const int n, const int c, const int h, const int w) const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->data_at(n, c, h, w);
#else
UNUSED(n);
UNUSED(c);
UNUSED(h);
UNUSED(w);
return T{0};
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return T{0};
}
}
template<typename T>
T ArrayCpuGpu<T>::diff_at(const int n, const int c, const int h, const int w) const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->diff_at(n, c, h, w);
#else
UNUSED(n);
UNUSED(c);
UNUSED(h);
UNUSED(w);
return T{0};
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return T{0};
}
}
// template<typename T>
// T ArrayCpuGpu<T>::data_at(const std::vector<int>& index) const
// {
// try
// {
// #ifdef USE_CAFFE
// return spImpl->pCaffeBlobT->data_at(index);
// #else
// UNUSED(index);
// return T{0};
// #endif
// }
// catch (const std::exception& e)
// {
// error(e.what(), __LINE__, __FUNCTION__, __FILE__);
// return T{0};
// }
// }
// template<typename T>
// T ArrayCpuGpu<T>::diff_at(const std::vector<int>& index) const
// {
// try
// {
// #ifdef USE_CAFFE
// return spImpl->pCaffeBlobT->diff_at(index);
// #else
// UNUSED(index);
// return T{0};
// #endif
// }
// catch (const std::exception& e)
// {
// error(e.what(), __LINE__, __FUNCTION__, __FILE__);
// return T{0};
// }
// }
template<typename T>
const T* ArrayCpuGpu<T>::cpu_data() const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->cpu_data();
#else
return nullptr;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return nullptr;
}
}
template<typename T>
void ArrayCpuGpu<T>::set_cpu_data(T* data)
{
try
{
#ifdef USE_CAFFE
spImpl->pCaffeBlobT->set_cpu_data(data);
#else
UNUSED(data);
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
}
}
template<typename T>
const int* ArrayCpuGpu<T>::gpu_shape() const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->gpu_shape();
#else
return nullptr;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return nullptr;
}
}
template<typename T>
const T* ArrayCpuGpu<T>::gpu_data() const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->gpu_data();
#else
return nullptr;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return nullptr;
}
}
template<typename T>
void ArrayCpuGpu<T>::set_gpu_data(T* data)
{
try
{
#ifdef USE_CAFFE
spImpl->pCaffeBlobT->set_gpu_data(data);
#else
UNUSED(data);
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
}
}
template<typename T>
const T* ArrayCpuGpu<T>::cpu_diff() const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->cpu_diff();
#else
return nullptr;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return nullptr;
}
}
template<typename T>
const T* ArrayCpuGpu<T>::gpu_diff() const
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->gpu_diff();
#else
return nullptr;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return nullptr;
}
}
template<typename T>
T* ArrayCpuGpu<T>::mutable_cpu_data()
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->mutable_cpu_data();
#else
return nullptr;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return nullptr;
}
}
template<typename T>
T* ArrayCpuGpu<T>::mutable_gpu_data()
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->mutable_gpu_data();
#else
return nullptr;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return nullptr;
}
}
template<typename T>
T* ArrayCpuGpu<T>::mutable_cpu_diff()
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->mutable_cpu_diff();
#else
return nullptr;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return nullptr;
}
}
template<typename T>
T* ArrayCpuGpu<T>::mutable_gpu_diff()
{
try
{
#ifdef USE_CAFFE
return spImpl->pCaffeBlobT->mutable_gpu_diff();
#else
return nullptr;
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return nullptr;
}
}
template<typename T>
void ArrayCpuGpu<T>::Update()
{
try
{
#ifdef USE_CAFFE
spImpl->pCaffeBlobT->Update();
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
}
}
COMPILE_TEMPLATE_FLOATING_INT_TYPES_CLASS(ArrayCpuGpu);
}
src/openpose/face/faceExtractorCaffe.cpp
浏览文件 @ 665b23e5
...@@ -22,9 +22,9 @@ namespace op ...@@ -22,9 +22,9 @@ namespace op
std::shared_ptr<ResizeAndMergeCaffe<float>> spResizeAndMergeCaffe; std::shared_ptr<ResizeAndMergeCaffe<float>> spResizeAndMergeCaffe;
std::shared_ptr<MaximumCaffe<float>> spMaximumCaffe; std::shared_ptr<MaximumCaffe<float>> spMaximumCaffe;
// Init with thread // Init with thread
boost::shared_ptr<caffe::Blob<float>> spCaffeNetOutputBlob; std::shared_ptr<ArrayCpuGpu<float>> spCaffeNetOutputBlob;
std::shared_ptr<caffe::Blob<float>> spHeatMapsBlob; std::shared_ptr<ArrayCpuGpu<float>> spHeatMapsBlob;
std::shared_ptr<caffe::Blob<float>> spPeaksBlob; std::shared_ptr<ArrayCpuGpu<float>> spPeaksBlob;
ImplFaceExtractorCaffe(const std::string& modelFolder, const int gpuId, const bool enableGoogleLogging) : ImplFaceExtractorCaffe(const std::string& modelFolder, const int gpuId, const bool enableGoogleLogging) :
netInitialized{false}, netInitialized{false},
...@@ -78,17 +78,19 @@ namespace op ...@@ -78,17 +78,19 @@ namespace op
inline void reshapeFaceExtractorCaffe(std::shared_ptr<ResizeAndMergeCaffe<float>>& resizeAndMergeCaffe, inline void reshapeFaceExtractorCaffe(std::shared_ptr<ResizeAndMergeCaffe<float>>& resizeAndMergeCaffe,
std::shared_ptr<MaximumCaffe<float>>& maximumCaffe, std::shared_ptr<MaximumCaffe<float>>& maximumCaffe,
boost::shared_ptr<caffe::Blob<float>>& caffeNetOutputBlob, std::shared_ptr<ArrayCpuGpu<float>>& caffeNetOutputBlob,
std::shared_ptr<caffe::Blob<float>>& heatMapsBlob, std::shared_ptr<ArrayCpuGpu<float>>& heatMapsBlob,
std::shared_ptr<caffe::Blob<float>>& peaksBlob, std::shared_ptr<ArrayCpuGpu<float>>& peaksBlob,
const int gpuID) const int gpuID)
{ {
try try
{ {
// HeatMaps extractor blob and layer // HeatMaps extractor blob and layer
const bool mergeFirstDimension = true; const bool mergeFirstDimension = true;
resizeAndMergeCaffe->Reshape({caffeNetOutputBlob.get()}, {heatMapsBlob.get()}, resizeAndMergeCaffe->Reshape(
FACE_CCN_DECREASE_FACTOR, 1.f, mergeFirstDimension, gpuID); std::vector<ArrayCpuGpu<float>*>{caffeNetOutputBlob.get()},
std::vector<ArrayCpuGpu<float>*>{heatMapsBlob.get()},
FACE_CCN_DECREASE_FACTOR, 1.f, mergeFirstDimension, gpuID);
// Pose extractor blob and layer // Pose extractor blob and layer
maximumCaffe->Reshape({heatMapsBlob.get()}, {peaksBlob.get()}); maximumCaffe->Reshape({heatMapsBlob.get()}, {peaksBlob.get()});
// Cuda check // Cuda check
...@@ -153,9 +155,9 @@ namespace op ...@@ -153,9 +155,9 @@ namespace op
cudaCheck(__LINE__, __FUNCTION__, __FILE__); cudaCheck(__LINE__, __FUNCTION__, __FILE__);
#endif #endif
// Initialize blobs // Initialize blobs
upImpl->spCaffeNetOutputBlob = upImpl->spNetCaffe->getOutputBlob(); upImpl->spCaffeNetOutputBlob = upImpl->spNetCaffe->getOutputBlobArray();
upImpl->spHeatMapsBlob = {std::make_shared<caffe::Blob<float>>(1,1,1,1)}; upImpl->spHeatMapsBlob = {std::make_shared<ArrayCpuGpu<float>>(1,1,1,1)};
upImpl->spPeaksBlob = {std::make_shared<caffe::Blob<float>>(1,1,1,1)}; upImpl->spPeaksBlob = {std::make_shared<ArrayCpuGpu<float>>(1,1,1,1)};
#ifdef USE_CUDA #ifdef USE_CUDA
cudaCheck(__LINE__, __FUNCTION__, __FILE__); cudaCheck(__LINE__, __FUNCTION__, __FILE__);
#endif #endif
......
src/openpose/hand/handExtractorCaffe.cpp
浏览文件 @ 665b23e5
#if defined USE_CAFFE #ifdef USE_CAFFE
#include <caffe/blob.hpp> #include <caffe/blob.hpp>
#endif #endif
#include <opencv2/opencv.hpp> // CV_WARP_INVERSE_MAP, CV_INTER_LINEAR #include <opencv2/opencv.hpp> // CV_WARP_INVERSE_MAP, CV_INTER_LINEAR
...@@ -16,16 +16,16 @@ namespace op ...@@ -16,16 +16,16 @@ namespace op
{ {
struct HandExtractorCaffe::ImplHandExtractorCaffe struct HandExtractorCaffe::ImplHandExtractorCaffe
{ {
#if defined USE_CAFFE #ifdef USE_CAFFE
bool netInitialized; bool netInitialized;
const int mGpuId; const int mGpuId;
std::shared_ptr<NetCaffe> spNetCaffe; std::shared_ptr<NetCaffe> spNetCaffe;
std::shared_ptr<ResizeAndMergeCaffe<float>> spResizeAndMergeCaffe; std::shared_ptr<ResizeAndMergeCaffe<float>> spResizeAndMergeCaffe;
std::shared_ptr<MaximumCaffe<float>> spMaximumCaffe; std::shared_ptr<MaximumCaffe<float>> spMaximumCaffe;
// Init with thread // Init with thread
boost::shared_ptr<caffe::Blob<float>> spCaffeNetOutputBlob; std::shared_ptr<ArrayCpuGpu<float>> spCaffeNetOutputBlob;
std::shared_ptr<caffe::Blob<float>> spHeatMapsBlob; std::shared_ptr<ArrayCpuGpu<float>> spHeatMapsBlob;
std::shared_ptr<caffe::Blob<float>> spPeaksBlob; std::shared_ptr<ArrayCpuGpu<float>> spPeaksBlob;
ImplHandExtractorCaffe(const std::string& modelFolder, const int gpuId, ImplHandExtractorCaffe(const std::string& modelFolder, const int gpuId,
const bool enableGoogleLogging) : const bool enableGoogleLogging) :
...@@ -40,7 +40,7 @@ namespace op ...@@ -40,7 +40,7 @@ namespace op
#endif #endif
}; };
#if defined USE_CAFFE #ifdef USE_CAFFE
void cropFrame(Array<float>& handImageCrop, cv::Mat& affineMatrix, const cv::Mat& cvInputData, void cropFrame(Array<float>& handImageCrop, cv::Mat& affineMatrix, const cv::Mat& cvInputData,
const Rectangle<float>& handRectangle, const int netInputSide, const Rectangle<float>& handRectangle, const int netInputSide,
const Point<int>& netOutputSize, const bool mirrorImage) const Point<int>& netOutputSize, const bool mirrorImage)
...@@ -162,17 +162,19 @@ namespace op ...@@ -162,17 +162,19 @@ namespace op
inline void reshapeHandExtractorCaffe(std::shared_ptr<ResizeAndMergeCaffe<float>>& resizeAndMergeCaffe, inline void reshapeHandExtractorCaffe(std::shared_ptr<ResizeAndMergeCaffe<float>>& resizeAndMergeCaffe,
std::shared_ptr<MaximumCaffe<float>>& maximumCaffe, std::shared_ptr<MaximumCaffe<float>>& maximumCaffe,
boost::shared_ptr<caffe::Blob<float>>& caffeNetOutputBlob, std::shared_ptr<ArrayCpuGpu<float>>& caffeNetOutputBlob,
std::shared_ptr<caffe::Blob<float>>& heatMapsBlob, std::shared_ptr<ArrayCpuGpu<float>>& heatMapsBlob,
std::shared_ptr<caffe::Blob<float>>& peaksBlob, std::shared_ptr<ArrayCpuGpu<float>>& peaksBlob,
const int gpuID) const int gpuID)
{ {
try try
{ {
// HeatMaps extractor blob and layer // HeatMaps extractor blob and layer
const bool mergeFirstDimension = true; const bool mergeFirstDimension = true;
resizeAndMergeCaffe->Reshape({caffeNetOutputBlob.get()}, {heatMapsBlob.get()}, resizeAndMergeCaffe->Reshape(
HAND_CCN_DECREASE_FACTOR, 1.f, mergeFirstDimension, gpuID); std::vector<ArrayCpuGpu<float>*>{caffeNetOutputBlob.get()},
std::vector<ArrayCpuGpu<float>*>{heatMapsBlob.get()},
HAND_CCN_DECREASE_FACTOR, 1.f, mergeFirstDimension, gpuID);
// Pose extractor blob and layer // Pose extractor blob and layer
maximumCaffe->Reshape({heatMapsBlob.get()}, {peaksBlob.get()}); maximumCaffe->Reshape({heatMapsBlob.get()}, {peaksBlob.get()});
// Cuda check // Cuda check
...@@ -194,7 +196,7 @@ namespace op ...@@ -194,7 +196,7 @@ namespace op
const ScaleMode heatMapScaleMode, const ScaleMode heatMapScaleMode,
const bool enableGoogleLogging) : const bool enableGoogleLogging) :
HandExtractorNet{netInputSize, netOutputSize, numberScales, rangeScales, heatMapTypes, heatMapScaleMode} HandExtractorNet{netInputSize, netOutputSize, numberScales, rangeScales, heatMapTypes, heatMapScaleMode}
#if defined USE_CAFFE #ifdef USE_CAFFE
, upImpl{new ImplHandExtractorCaffe{modelFolder, gpuId, enableGoogleLogging}} , upImpl{new ImplHandExtractorCaffe{modelFolder, gpuId, enableGoogleLogging}}
#endif #endif
{ {
...@@ -228,19 +230,19 @@ namespace op ...@@ -228,19 +230,19 @@ namespace op
{ {
try try
{ {
#if defined USE_CAFFE #ifdef USE_CAFFE
// Logging // Logging
log("Starting initialization on thread.", Priority::Low, __LINE__, __FUNCTION__, __FILE__); log("Starting initialization on thread.", Priority::Low, __LINE__, __FUNCTION__, __FILE__);
// Initialize Caffe net // Initialize Caffe net
upImpl->spNetCaffe->initializationOnThread(); upImpl->spNetCaffe->initializationOnThread();
#if defined USE_CUDA #ifdef USE_CUDA
cudaCheck(__LINE__, __FUNCTION__, __FILE__); cudaCheck(__LINE__, __FUNCTION__, __FILE__);
#endif #endif
// Initialize blobs // Initialize blobs
upImpl->spCaffeNetOutputBlob = upImpl->spNetCaffe->getOutputBlob(); upImpl->spCaffeNetOutputBlob = upImpl->spNetCaffe->getOutputBlobArray();
upImpl->spHeatMapsBlob = {std::make_shared<caffe::Blob<float>>(1,1,1,1)}; upImpl->spHeatMapsBlob = {std::make_shared<ArrayCpuGpu<float>>(1,1,1,1)};
upImpl->spPeaksBlob = {std::make_shared<caffe::Blob<float>>(1,1,1,1)}; upImpl->spPeaksBlob = {std::make_shared<ArrayCpuGpu<float>>(1,1,1,1)};
#if defined USE_CUDA #ifdef USE_CUDA
cudaCheck(__LINE__, __FUNCTION__, __FILE__); cudaCheck(__LINE__, __FUNCTION__, __FILE__);
#endif #endif
// Logging // Logging
...@@ -258,7 +260,7 @@ namespace op ...@@ -258,7 +260,7 @@ namespace op
{ {
try try
{ {
#if defined USE_CAFFE #ifdef USE_CAFFE
if (mEnabled && !handRectangles.empty()) if (mEnabled && !handRectangles.empty())
{ {
// Sanity check // Sanity check
...@@ -409,7 +411,7 @@ namespace op ...@@ -409,7 +411,7 @@ namespace op
{ {
try try
{ {
#if defined USE_CAFFE #ifdef USE_CAFFE
// 1. Deep net // 1. Deep net
upImpl->spNetCaffe->forwardPass(mHandImageCrop); upImpl->spNetCaffe->forwardPass(mHandImageCrop);
......
src/openpose/net/bodyPartConnectorCaffe.cpp
浏览文件 @ 665b23e5
...@@ -53,7 +53,7 @@ namespace op ...@@ -53,7 +53,7 @@ namespace op
} }
template <typename T> template <typename T>
void BodyPartConnectorCaffe<T>::Reshape(const std::vector<caffe::Blob<T>*>& bottom, const int gpuID) void BodyPartConnectorCaffe<T>::Reshape(const std::vector<ArrayCpuGpu<T>*>& bottom, const int gpuID)
{ {
try try
{ {
...@@ -73,6 +73,7 @@ namespace op ...@@ -73,6 +73,7 @@ namespace op
mGpuID = gpuID; mGpuID = gpuID;
#else #else
UNUSED(bottom); UNUSED(bottom);
UNUSED(gpuID);
#endif #endif
} }
catch (const std::exception& e) catch (const std::exception& e)
...@@ -173,7 +174,7 @@ namespace op ...@@ -173,7 +174,7 @@ namespace op
} }
template <typename T> template <typename T>
void BodyPartConnectorCaffe<T>::Forward(const std::vector<caffe::Blob<T>*>& bottom, Array<T>& poseKeypoints, void BodyPartConnectorCaffe<T>::Forward(const std::vector<ArrayCpuGpu<T>*>& bottom, Array<T>& poseKeypoints,
Array<T>& poseScores) Array<T>& poseScores)
{ {
try try
...@@ -196,7 +197,7 @@ namespace op ...@@ -196,7 +197,7 @@ namespace op
} }
template <typename T> template <typename T>
void BodyPartConnectorCaffe<T>::Forward_cpu(const std::vector<caffe::Blob<T>*>& bottom, Array<T>& poseKeypoints, void BodyPartConnectorCaffe<T>::Forward_cpu(const std::vector<ArrayCpuGpu<T>*>& bottom, Array<T>& poseKeypoints,
Array<T>& poseScores) Array<T>& poseScores)
{ {
try try
...@@ -213,6 +214,7 @@ namespace op ...@@ -213,6 +214,7 @@ namespace op
#else #else
UNUSED(bottom); UNUSED(bottom);
UNUSED(poseKeypoints); UNUSED(poseKeypoints);
UNUSED(poseScores);
#endif #endif
} }
catch (const std::exception& e) catch (const std::exception& e)
...@@ -222,7 +224,7 @@ namespace op ...@@ -222,7 +224,7 @@ namespace op
} }
template <typename T> template <typename T>
void BodyPartConnectorCaffe<T>::Forward_ocl(const std::vector<caffe::Blob<T>*>& bottom, Array<T>& poseKeypoints, void BodyPartConnectorCaffe<T>::Forward_ocl(const std::vector<ArrayCpuGpu<T>*>& bottom, Array<T>& poseKeypoints,
Array<T>& poseScores) Array<T>& poseScores)
{ {
try try
...@@ -298,7 +300,7 @@ namespace op ...@@ -298,7 +300,7 @@ namespace op
} }
template <typename T> template <typename T>
void BodyPartConnectorCaffe<T>::Forward_gpu(const std::vector<caffe::Blob<T>*>& bottom, Array<T>& poseKeypoints, void BodyPartConnectorCaffe<T>::Forward_gpu(const std::vector<ArrayCpuGpu<T>*>& bottom, Array<T>& poseKeypoints,
Array<T>& poseScores) Array<T>& poseScores)
{ {
try try
...@@ -373,9 +375,9 @@ namespace op ...@@ -373,9 +375,9 @@ namespace op
} }
template <typename T> template <typename T>
void BodyPartConnectorCaffe<T>::Backward_cpu(const std::vector<caffe::Blob<T>*>& top, void BodyPartConnectorCaffe<T>::Backward_cpu(const std::vector<ArrayCpuGpu<T>*>& top,
const std::vector<bool>& propagate_down, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom) const std::vector<ArrayCpuGpu<T>*>& bottom)
{ {
try try
{ {
...@@ -393,9 +395,9 @@ namespace op ...@@ -393,9 +395,9 @@ namespace op
} }
template <typename T> template <typename T>
void BodyPartConnectorCaffe<T>::Backward_gpu(const std::vector<caffe::Blob<T>*>& top, void BodyPartConnectorCaffe<T>::Backward_gpu(const std::vector<ArrayCpuGpu<T>*>& top,
const std::vector<bool>& propagate_down, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom) const std::vector<ArrayCpuGpu<T>*>& bottom)
{ {
try try
{ {
......
src/openpose/net/maximumCaffe.cpp
浏览文件 @ 665b23e5
...@@ -28,8 +28,8 @@ namespace op ...@@ -28,8 +28,8 @@ namespace op
} }
template <typename T> template <typename T>
void MaximumCaffe<T>::LayerSetUp(const std::vector<caffe::Blob<T>*>& bottom, void MaximumCaffe<T>::LayerSetUp(const std::vector<ArrayCpuGpu<T>*>& bottom,
const std::vector<caffe::Blob<T>*>& top) const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -50,8 +50,8 @@ namespace op ...@@ -50,8 +50,8 @@ namespace op
} }
template <typename T> template <typename T>
void MaximumCaffe<T>::Reshape(const std::vector<caffe::Blob<T>*>& bottom, void MaximumCaffe<T>::Reshape(const std::vector<ArrayCpuGpu<T>*>& bottom,
const std::vector<caffe::Blob<T>*>& top) const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -86,8 +86,8 @@ namespace op ...@@ -86,8 +86,8 @@ namespace op
} }
template <typename T> template <typename T>
void MaximumCaffe<T>::Forward(const std::vector<caffe::Blob<T>*>& bottom, void MaximumCaffe<T>::Forward(const std::vector<ArrayCpuGpu<T>*>& bottom,
const std::vector<caffe::Blob<T>*>& top) const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -108,8 +108,8 @@ namespace op ...@@ -108,8 +108,8 @@ namespace op
} }
template <typename T> template <typename T>
void MaximumCaffe<T>::Forward_cpu(const std::vector<caffe::Blob<T>*>& bottom, void MaximumCaffe<T>::Forward_cpu(const std::vector<ArrayCpuGpu<T>*>& bottom,
const std::vector<caffe::Blob<T>*>& top) const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -127,8 +127,8 @@ namespace op ...@@ -127,8 +127,8 @@ namespace op
} }
template <typename T> template <typename T>
void MaximumCaffe<T>::Forward_gpu(const std::vector<caffe::Blob<T>*>& bottom, void MaximumCaffe<T>::Forward_gpu(const std::vector<ArrayCpuGpu<T>*>& bottom,
const std::vector<caffe::Blob<T>*>& top) const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -148,9 +148,9 @@ namespace op ...@@ -148,9 +148,9 @@ namespace op
} }
template <typename T> template <typename T>
void MaximumCaffe<T>::Backward_cpu(const std::vector<caffe::Blob<T>*>& top, void MaximumCaffe<T>::Backward_cpu(const std::vector<ArrayCpuGpu<T>*>& top,
const std::vector<bool>& propagate_down, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom) const std::vector<ArrayCpuGpu<T>*>& bottom)
{ {
try try
{ {
...@@ -168,9 +168,9 @@ namespace op ...@@ -168,9 +168,9 @@ namespace op
} }
template <typename T> template <typename T>
void MaximumCaffe<T>::Backward_gpu(const std::vector<caffe::Blob<T>*>& top, void MaximumCaffe<T>::Backward_gpu(const std::vector<ArrayCpuGpu<T>*>& top,
const std::vector<bool>& propagate_down, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom) const std::vector<ArrayCpuGpu<T>*>& bottom)
{ {
try try
{ {
......
src/openpose/net/netCaffe.cpp
浏览文件 @ 665b23e5
...@@ -44,43 +44,50 @@ namespace op ...@@ -44,43 +44,50 @@ namespace op
mCaffeTrainedModel{caffeTrainedModel}, mCaffeTrainedModel{caffeTrainedModel},
mLastBlobName{lastBlobName} mLastBlobName{lastBlobName}
{ {
const std::string message{".\nPossible causes:\n\t1. Not downloading the OpenPose trained models." try
"\n\t2. Not running OpenPose from the same directory where the `model`"
" folder is located.\n\t3. Using paths with spaces."};
if (!existFile(mCaffeProto))
error("Prototxt file not found: " + mCaffeProto + message, __LINE__, __FUNCTION__, __FILE__);
if (!existFile(mCaffeTrainedModel))
error("Caffe trained model file not found: " + mCaffeTrainedModel + message,
__LINE__, __FUNCTION__, __FILE__);
// Double if condition in order to speed up the program if it is called several times
if (enableGoogleLogging && !sGoogleLoggingInitialized)
{ {
std::lock_guard<std::mutex> lock{sMutexNetCaffe}; const std::string message{".\nPossible causes:\n\t1. Not downloading the OpenPose trained models."
"\n\t2. Not running OpenPose from the same directory where the `model`"
" folder is located.\n\t3. Using paths with spaces."};
if (!existFile(mCaffeProto))
error("Prototxt file not found: " + mCaffeProto + message, __LINE__, __FUNCTION__, __FILE__);
if (!existFile(mCaffeTrainedModel))
error("Caffe trained model file not found: " + mCaffeTrainedModel + message,
__LINE__, __FUNCTION__, __FILE__);
// Double if condition in order to speed up the program if it is called several times
if (enableGoogleLogging && !sGoogleLoggingInitialized) if (enableGoogleLogging && !sGoogleLoggingInitialized)
{
google::InitGoogleLogging("OpenPose");
sGoogleLoggingInitialized = true;
}
}
#ifdef USE_OPENCL
// Initialize OpenCL
if (!sOpenCLInitialized)
{ {
std::lock_guard<std::mutex> lock{sMutexNetCaffe}; std::lock_guard<std::mutex> lock{sMutexNetCaffe};
if (!sOpenCLInitialized) if (enableGoogleLogging && !sGoogleLoggingInitialized)
{ {
caffe::Caffe::set_mode(caffe::Caffe::GPU); google::InitGoogleLogging("OpenPose");
std::vector<int> devices; sGoogleLoggingInitialized = true;
const int maxNumberGpu = OpenCL::getTotalGPU();
for (auto i = 0; i < maxNumberGpu; i++)
devices.emplace_back(i);
caffe::Caffe::SetDevices(devices);
if (mGpuId >= maxNumberGpu)
error("Unexpected error. Please, notify us.", __LINE__, __FUNCTION__, __FILE__);
sOpenCLInitialized = true;
} }
} }
#endif #ifdef USE_OPENCL
// Initialize OpenCL
if (!sOpenCLInitialized)
{
std::lock_guard<std::mutex> lock{sMutexNetCaffe};
if (!sOpenCLInitialized)
{
caffe::Caffe::set_mode(caffe::Caffe::GPU);
std::vector<int> devices;
const int maxNumberGpu = OpenCL::getTotalGPU();
for (auto i = 0; i < maxNumberGpu; i++)
devices.emplace_back(i);
caffe::Caffe::SetDevices(devices);
if (mGpuId >= maxNumberGpu)
error("Unexpected error. Please, notify us.", __LINE__, __FUNCTION__, __FILE__);
sOpenCLInitialized = true;
}
}
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
}
} }
#endif #endif
}; };
...@@ -113,10 +120,10 @@ namespace op ...@@ -113,10 +120,10 @@ namespace op
try try
{ {
#ifndef USE_CAFFE #ifndef USE_CAFFE
UNUSED(netInputSize4D);
UNUSED(caffeProto); UNUSED(caffeProto);
UNUSED(caffeTrainedModel); UNUSED(caffeTrainedModel);
UNUSED(gpuId); UNUSED(gpuId);
UNUSED(enableGoogleLogging);
UNUSED(lastBlobName); UNUSED(lastBlobName);
error("OpenPose must be compiled with the `USE_CAFFE` macro definition in order to use this" error("OpenPose must be compiled with the `USE_CAFFE` macro definition in order to use this"
" functionality.", __LINE__, __FUNCTION__, __FILE__); " functionality.", __LINE__, __FUNCTION__, __FILE__);
...@@ -166,6 +173,7 @@ namespace op ...@@ -166,6 +173,7 @@ namespace op
#endif #endif
// Set spOutputBlob // Set spOutputBlob
upImpl->spOutputBlob = upImpl->upCaffeNet->blob_by_name(upImpl->mLastBlobName); upImpl->spOutputBlob = upImpl->upCaffeNet->blob_by_name(upImpl->mLastBlobName);
// Sanity check
if (upImpl->spOutputBlob == nullptr) if (upImpl->spOutputBlob == nullptr)
error("The output blob is a nullptr. Did you use the same name than the prototxt? (Used: " error("The output blob is a nullptr. Did you use the same name than the prototxt? (Used: "
+ upImpl->mLastBlobName + ").", __LINE__, __FUNCTION__, __FILE__); + upImpl->mLastBlobName + ").", __LINE__, __FUNCTION__, __FILE__);
...@@ -227,12 +235,12 @@ namespace op ...@@ -227,12 +235,12 @@ namespace op
} }
} }
boost::shared_ptr<caffe::Blob<float>> NetCaffe::getOutputBlob() const std::shared_ptr<ArrayCpuGpu<float>> NetCaffe::getOutputBlobArray() const
{ {
try try
{ {
#ifdef USE_CAFFE #ifdef USE_CAFFE
return upImpl->spOutputBlob; return std::make_shared<ArrayCpuGpu<float>>(upImpl->spOutputBlob.get());
#else #else
return nullptr; return nullptr;
#endif #endif
......
src/openpose/net/netOpenCv.cpp
浏览文件 @ 665b23e5
...@@ -31,7 +31,6 @@ namespace op ...@@ -31,7 +31,6 @@ namespace op
// OpenCV DNN // OpenCV DNN
cv::dnn::Net mNet; cv::dnn::Net mNet;
cv::Mat mNetOutputBlob; cv::Mat mNetOutputBlob;
// std::shared_ptr<caffe::Blob<float>> spOutputBlob;
boost::shared_ptr<caffe::Blob<float>> spOutputBlob; boost::shared_ptr<caffe::Blob<float>> spOutputBlob;
ImplNetOpenCv(const std::string& caffeProto, const std::string& caffeTrainedModel, const int gpuId) : ImplNetOpenCv(const std::string& caffeProto, const std::string& caffeTrainedModel, const int gpuId) :
...@@ -39,7 +38,6 @@ namespace op ...@@ -39,7 +38,6 @@ namespace op
mCaffeProto{caffeProto}, mCaffeProto{caffeProto},
mCaffeTrainedModel{caffeTrainedModel}, mCaffeTrainedModel{caffeTrainedModel},
mNet{cv::dnn::readNetFromCaffe(caffeProto, caffeTrainedModel)}, mNet{cv::dnn::readNetFromCaffe(caffeProto, caffeTrainedModel)},
// spOutputBlob{std::make_shared<caffe::Blob<float>>(1,1,1,1)}
spOutputBlob{new caffe::Blob<float>(1,1,1,1)} spOutputBlob{new caffe::Blob<float>(1,1,1,1)}
{ {
const std::string message{".\nPossible causes:\n\t1. Not downloading the OpenPose trained models." const std::string message{".\nPossible causes:\n\t1. Not downloading the OpenPose trained models."
...@@ -139,12 +137,12 @@ namespace op ...@@ -139,12 +137,12 @@ namespace op
} }
} }
boost::shared_ptr<caffe::Blob<float>> NetOpenCv::getOutputBlob() const std::shared_ptr<ArrayCpuGpu<float>> NetOpenCv::getOutputBlobArray() const
{ {
try try
{ {
#ifdef USE_OPEN_CV_DNN #ifdef USE_OPEN_CV_DNN
return upImpl->spOutputBlob; return std::make_shared<ArrayCpuGpu<float>>(upImpl->spOutputBlob.get());
#else #else
return nullptr; return nullptr;
#endif #endif
......
src/openpose/net/nmsCaffe.cpp
浏览文件 @ 665b23e5
...@@ -14,12 +14,12 @@ namespace op ...@@ -14,12 +14,12 @@ namespace op
struct NmsCaffe<T>::ImplNmsCaffe struct NmsCaffe<T>::ImplNmsCaffe
{ {
#ifdef USE_CAFFE #ifdef USE_CAFFE
caffe::Blob<int> mKernelBlob; ArrayCpuGpu<int> mKernelBlob;
std::array<int, 4> mBottomSize; std::array<int, 4> mBottomSize;
std::array<int, 4> mTopSize; std::array<int, 4> mTopSize;
// Special Kernel for OpenCL NMS // Special Kernel for OpenCL NMS
#if defined USE_CAFFE && defined USE_OPENCL #if defined USE_CAFFE && defined USE_OPENCL
//std::shared_ptr<caffe::Blob<uint8_t>> mKernelBlobT; //std::shared_ptr<ArrayCpuGpu<uint8_t>> mKernelBlobT;
uint8_t* mKernelGpuPtr; uint8_t* mKernelGpuPtr;
uint8_t* mKernelCpuPtr; uint8_t* mKernelCpuPtr;
#endif #endif
...@@ -65,7 +65,7 @@ namespace op ...@@ -65,7 +65,7 @@ namespace op
} }
template <typename T> template <typename T>
void NmsCaffe<T>::LayerSetUp(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top) void NmsCaffe<T>::LayerSetUp(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -86,7 +86,7 @@ namespace op ...@@ -86,7 +86,7 @@ namespace op
} }
template <typename T> template <typename T>
void NmsCaffe<T>::Reshape(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top, void NmsCaffe<T>::Reshape(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top,
const int maxPeaks, const int outputChannels, const int gpuID) const int maxPeaks, const int outputChannels, const int gpuID)
{ {
try try
...@@ -127,6 +127,8 @@ namespace op ...@@ -127,6 +127,8 @@ namespace op
UNUSED(bottom); UNUSED(bottom);
UNUSED(top); UNUSED(top);
UNUSED(maxPeaks); UNUSED(maxPeaks);
UNUSED(outputChannels);
UNUSED(gpuID);
#endif #endif
} }
catch (const std::exception& e) catch (const std::exception& e)
...@@ -162,7 +164,7 @@ namespace op ...@@ -162,7 +164,7 @@ namespace op
} }
template <typename T> template <typename T>
void NmsCaffe<T>::Forward(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top) void NmsCaffe<T>::Forward(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -184,7 +186,7 @@ namespace op ...@@ -184,7 +186,7 @@ namespace op
} }
template <typename T> template <typename T>
void NmsCaffe<T>::Forward_cpu(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top) void NmsCaffe<T>::Forward_cpu(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -203,7 +205,7 @@ namespace op ...@@ -203,7 +205,7 @@ namespace op
} }
template <typename T> template <typename T>
void NmsCaffe<T>::Forward_gpu(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top) void NmsCaffe<T>::Forward_gpu(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -224,7 +226,7 @@ namespace op ...@@ -224,7 +226,7 @@ namespace op
} }
template <typename T> template <typename T>
void NmsCaffe<T>::Forward_ocl(const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top) void NmsCaffe<T>::Forward_ocl(const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -246,8 +248,8 @@ namespace op ...@@ -246,8 +248,8 @@ namespace op
} }
template <typename T> template <typename T>
void NmsCaffe<T>::Backward_cpu(const std::vector<caffe::Blob<T>*>& top, const std::vector<bool>& propagate_down, void NmsCaffe<T>::Backward_cpu(const std::vector<ArrayCpuGpu<T>*>& top, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom) const std::vector<ArrayCpuGpu<T>*>& bottom)
{ {
try try
{ {
...@@ -265,8 +267,8 @@ namespace op ...@@ -265,8 +267,8 @@ namespace op
} }
template <typename T> template <typename T>
void NmsCaffe<T>::Backward_gpu(const std::vector<caffe::Blob<T>*>& top, const std::vector<bool>& propagate_down, void NmsCaffe<T>::Backward_gpu(const std::vector<ArrayCpuGpu<T>*>& top, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom) const std::vector<ArrayCpuGpu<T>*>& bottom)
{ {
try try
{ {
......
src/openpose/net/resizeAndMergeCaffe.cpp
浏览文件 @ 665b23e5
...@@ -33,8 +33,8 @@ namespace op ...@@ -33,8 +33,8 @@ namespace op
} }
template <typename T> template <typename T>
void ResizeAndMergeCaffe<T>::LayerSetUp(const std::vector<caffe::Blob<T>*>& bottom, void ResizeAndMergeCaffe<T>::LayerSetUp(const std::vector<ArrayCpuGpu<T>*>& bottom,
const std::vector<caffe::Blob<T>*>& top) const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -56,7 +56,7 @@ namespace op ...@@ -56,7 +56,7 @@ namespace op
template <typename T> template <typename T>
void ResizeAndMergeCaffe<T>::Reshape( void ResizeAndMergeCaffe<T>::Reshape(
const std::vector<caffe::Blob<T>*>& bottom, const std::vector<caffe::Blob<T>*>& top, const T netFactor, const std::vector<ArrayCpuGpu<T>*>& bottom, const std::vector<ArrayCpuGpu<T>*>& top, const T netFactor,
const T scaleFactor, const bool mergeFirstDimension, const int gpuID) const T scaleFactor, const bool mergeFirstDimension, const int gpuID)
{ {
try try
...@@ -100,6 +100,7 @@ namespace op ...@@ -100,6 +100,7 @@ namespace op
UNUSED(netFactor); UNUSED(netFactor);
UNUSED(scaleFactor); UNUSED(scaleFactor);
UNUSED(mergeFirstDimension); UNUSED(mergeFirstDimension);
UNUSED(gpuID);
#endif #endif
} }
catch (const std::exception& e) catch (const std::exception& e)
...@@ -122,8 +123,8 @@ namespace op ...@@ -122,8 +123,8 @@ namespace op
} }
template <typename T> template <typename T>
void ResizeAndMergeCaffe<T>::Forward(const std::vector<caffe::Blob<T>*>& bottom, void ResizeAndMergeCaffe<T>::Forward(const std::vector<ArrayCpuGpu<T>*>& bottom,
const std::vector<caffe::Blob<T>*>& top) const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -145,8 +146,8 @@ namespace op ...@@ -145,8 +146,8 @@ namespace op
} }
template <typename T> template <typename T>
void ResizeAndMergeCaffe<T>::Forward_cpu(const std::vector<caffe::Blob<T>*>& bottom, void ResizeAndMergeCaffe<T>::Forward_cpu(const std::vector<ArrayCpuGpu<T>*>& bottom,
const std::vector<caffe::Blob<T>*>& top) const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -168,8 +169,8 @@ namespace op ...@@ -168,8 +169,8 @@ namespace op
} }
template <typename T> template <typename T>
void ResizeAndMergeCaffe<T>::Forward_gpu(const std::vector<caffe::Blob<T>*>& bottom, void ResizeAndMergeCaffe<T>::Forward_gpu(const std::vector<ArrayCpuGpu<T>*>& bottom,
const std::vector<caffe::Blob<T>*>& top) const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -193,8 +194,8 @@ namespace op ...@@ -193,8 +194,8 @@ namespace op
} }
template <typename T> template <typename T>
void ResizeAndMergeCaffe<T>::Forward_ocl(const std::vector<caffe::Blob<T>*>& bottom, void ResizeAndMergeCaffe<T>::Forward_ocl(const std::vector<ArrayCpuGpu<T>*>& bottom,
const std::vector<caffe::Blob<T>*>& top) const std::vector<ArrayCpuGpu<T>*>& top)
{ {
try try
{ {
...@@ -218,9 +219,9 @@ namespace op ...@@ -218,9 +219,9 @@ namespace op
} }
template <typename T> template <typename T>
void ResizeAndMergeCaffe<T>::Backward_cpu(const std::vector<caffe::Blob<T>*>& top, void ResizeAndMergeCaffe<T>::Backward_cpu(const std::vector<ArrayCpuGpu<T>*>& top,
const std::vector<bool>& propagate_down, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom) const std::vector<ArrayCpuGpu<T>*>& bottom)
{ {
try try
{ {
...@@ -238,9 +239,9 @@ namespace op ...@@ -238,9 +239,9 @@ namespace op
} }
template <typename T> template <typename T>
void ResizeAndMergeCaffe<T>::Backward_gpu(const std::vector<caffe::Blob<T>*>& top, void ResizeAndMergeCaffe<T>::Backward_gpu(const std::vector<ArrayCpuGpu<T>*>& top,
const std::vector<bool>& propagate_down, const std::vector<bool>& propagate_down,
const std::vector<caffe::Blob<T>*>& bottom) const std::vector<ArrayCpuGpu<T>*>& bottom)
{ {
try try
{ {
......
src/openpose/pose/poseExtractorCaffe.cpp
浏览文件 @ 665b23e5
...@@ -44,10 +44,10 @@ namespace op ...@@ -44,10 +44,10 @@ namespace op
std::vector<std::vector<int>> mNetInput4DSizes; std::vector<std::vector<int>> mNetInput4DSizes;
std::vector<double> mScaleInputToNetInputs; std::vector<double> mScaleInputToNetInputs;
// Init with thread // Init with thread
std::vector<boost::shared_ptr<caffe::Blob<float>>> spCaffeNetOutputBlobs; std::vector<std::shared_ptr<ArrayCpuGpu<float>>> spCaffeNetOutputBlobs;
std::shared_ptr<caffe::Blob<float>> spHeatMapsBlob; std::shared_ptr<ArrayCpuGpu<float>> spHeatMapsBlob;
std::shared_ptr<caffe::Blob<float>> spPeaksBlob; std::shared_ptr<ArrayCpuGpu<float>> spPeaksBlob;
std::shared_ptr<caffe::Blob<float>> spMaximumPeaksBlob; std::shared_ptr<ArrayCpuGpu<float>> spMaximumPeaksBlob;
ImplPoseExtractorCaffe( ImplPoseExtractorCaffe(
const PoseModel poseModel, const int gpuId, const std::string& modelFolder, const PoseModel poseModel, const int gpuId, const std::string& modelFolder,
...@@ -69,13 +69,13 @@ namespace op ...@@ -69,13 +69,13 @@ namespace op
}; };
#ifdef USE_CAFFE #ifdef USE_CAFFE
std::vector<caffe::Blob<float>*> caffeNetSharedToPtr( std::vector<ArrayCpuGpu<float>*> arraySharedToPtr(
std::vector<boost::shared_ptr<caffe::Blob<float>>>& caffeNetOutputBlob) const std::vector<std::shared_ptr<ArrayCpuGpu<float>>>& caffeNetOutputBlob)
{ {
try try
{ {
// Prepare spCaffeNetOutputBlobss // Prepare spCaffeNetOutputBlobss
std::vector<caffe::Blob<float>*> caffeNetOutputBlobs(caffeNetOutputBlob.size()); std::vector<ArrayCpuGpu<float>*> caffeNetOutputBlobs(caffeNetOutputBlob.size());
for (auto i = 0u ; i < caffeNetOutputBlobs.size() ; i++) for (auto i = 0u ; i < caffeNetOutputBlobs.size() ; i++)
caffeNetOutputBlobs[i] = caffeNetOutputBlob[i].get(); caffeNetOutputBlobs[i] = caffeNetOutputBlob[i].get();
return caffeNetOutputBlobs; return caffeNetOutputBlobs;
...@@ -87,26 +87,27 @@ namespace op ...@@ -87,26 +87,27 @@ namespace op
} }
} }
inline void reshapePoseExtractorCaffe(std::shared_ptr<ResizeAndMergeCaffe<float>>& resizeAndMergeCaffe, inline void reshapePoseExtractorCaffe(
std::shared_ptr<NmsCaffe<float>>& nmsCaffe, std::shared_ptr<ResizeAndMergeCaffe<float>>& resizeAndMergeCaffe,
std::shared_ptr<BodyPartConnectorCaffe<float>>& bodyPartConnectorCaffe, std::shared_ptr<NmsCaffe<float>>& nmsCaffe,
std::shared_ptr<MaximumCaffe<float>>& maximumCaffe, std::shared_ptr<BodyPartConnectorCaffe<float>>& bodyPartConnectorCaffe,
std::vector<boost::shared_ptr<caffe::Blob<float>>>& caffeNetOutputBlob, std::shared_ptr<MaximumCaffe<float>>& maximumCaffe,
std::shared_ptr<caffe::Blob<float>>& heatMapsBlob, std::vector<std::shared_ptr<ArrayCpuGpu<float>>>& caffeNetOutputBlobsShared,
std::shared_ptr<caffe::Blob<float>>& peaksBlob, std::shared_ptr<ArrayCpuGpu<float>>& heatMapsBlob,
std::shared_ptr<caffe::Blob<float>>& maximumPeaksBlob, std::shared_ptr<ArrayCpuGpu<float>>& peaksBlob,
const float scaleInputToNetInput, std::shared_ptr<ArrayCpuGpu<float>>& maximumPeaksBlob,
const PoseModel poseModel, const float scaleInputToNetInput,
const int gpuID) const PoseModel poseModel,
const int gpuID)
{ {
try try
{ {
// HeatMaps extractor blob and layer // HeatMaps extractor blob and layer
// Caffe modifies bottom - Heatmap gets resized // Caffe modifies bottom - Heatmap gets resized
const auto caffeNetOutputBlobs = caffeNetSharedToPtr(caffeNetOutputBlob); const auto caffeNetOutputBlobs = arraySharedToPtr(caffeNetOutputBlobsShared);
resizeAndMergeCaffe->Reshape(caffeNetOutputBlobs, {heatMapsBlob.get()}, resizeAndMergeCaffe->Reshape(
getPoseNetDecreaseFactor(poseModel), 1.f/scaleInputToNetInput, true, caffeNetOutputBlobs, {heatMapsBlob.get()},
gpuID); getPoseNetDecreaseFactor(poseModel), 1.f/scaleInputToNetInput, true, gpuID);
// Pose extractor blob and layer // Pose extractor blob and layer
nmsCaffe->Reshape({heatMapsBlob.get()}, {peaksBlob.get()}, getPoseMaxPeaks(), nmsCaffe->Reshape({heatMapsBlob.get()}, {peaksBlob.get()}, getPoseMaxPeaks(),
getPoseNumberBodyParts(poseModel), gpuID); getPoseNumberBodyParts(poseModel), gpuID);
...@@ -127,7 +128,7 @@ namespace op ...@@ -127,7 +128,7 @@ namespace op
void addCaffeNetOnThread( void addCaffeNetOnThread(
std::vector<std::shared_ptr<Net>>& net, std::vector<std::shared_ptr<Net>>& net,
std::vector<boost::shared_ptr<caffe::Blob<float>>>& caffeNetOutputBlob, std::vector<std::shared_ptr<ArrayCpuGpu<float>>>& caffeNetOutputBlob,
const PoseModel poseModel, const int gpuId, const std::string& modelFolder, const PoseModel poseModel, const int gpuId, const std::string& modelFolder,
const std::string& protoTxtPath, const std::string& caffeModelPath, const bool enableGoogleLogging) const std::string& protoTxtPath, const std::string& caffeModelPath, const bool enableGoogleLogging)
{ {
...@@ -147,8 +148,7 @@ namespace op ...@@ -147,8 +148,7 @@ namespace op
// UNUSED(enableGoogleLogging); // UNUSED(enableGoogleLogging);
// Initializing them on the thread // Initializing them on the thread
net.back()->initializationOnThread(); net.back()->initializationOnThread();
caffeNetOutputBlob.emplace_back(((NetCaffe*)net.back().get())->getOutputBlob()); caffeNetOutputBlob.emplace_back((net.back().get())->getOutputBlobArray());
// caffeNetOutputBlob.emplace_back(((NetOpenCv*)net.back().get())->getOutputBlob());
// Sanity check // Sanity check
if (net.size() != caffeNetOutputBlob.size()) if (net.size() != caffeNetOutputBlob.size())
error("Weird error, this should not happen. Notify us.", __LINE__, __FUNCTION__, __FILE__); error("Weird error, this should not happen. Notify us.", __LINE__, __FUNCTION__, __FILE__);
...@@ -221,10 +221,10 @@ namespace op ...@@ -221,10 +221,10 @@ namespace op
cudaCheck(__LINE__, __FUNCTION__, __FILE__); cudaCheck(__LINE__, __FUNCTION__, __FILE__);
#endif #endif
// Initialize blobs // Initialize blobs
upImpl->spHeatMapsBlob = {std::make_shared<caffe::Blob<float>>(1,1,1,1)}; upImpl->spHeatMapsBlob = {std::make_shared<ArrayCpuGpu<float>>(1,1,1,1)};
upImpl->spPeaksBlob = {std::make_shared<caffe::Blob<float>>(1,1,1,1)}; upImpl->spPeaksBlob = {std::make_shared<ArrayCpuGpu<float>>(1,1,1,1)};
if (TOP_DOWN_REFINEMENT) if (TOP_DOWN_REFINEMENT)
upImpl->spMaximumPeaksBlob = {std::make_shared<caffe::Blob<float>>(1,1,1,1)}; upImpl->spMaximumPeaksBlob = {std::make_shared<ArrayCpuGpu<float>>(1,1,1,1)};
#ifdef USE_CUDA #ifdef USE_CUDA
cudaCheck(__LINE__, __FUNCTION__, __FILE__); cudaCheck(__LINE__, __FUNCTION__, __FILE__);
#endif #endif
...@@ -295,7 +295,7 @@ namespace op ...@@ -295,7 +295,7 @@ namespace op
} }
// 2. Resize heat maps + merge different scales // 2. Resize heat maps + merge different scales
// ~5ms (GPU) / ~20ms (CPU) // ~5ms (GPU) / ~20ms (CPU)
const auto caffeNetOutputBlobs = caffeNetSharedToPtr(upImpl->spCaffeNetOutputBlobs); const auto caffeNetOutputBlobs = arraySharedToPtr(upImpl->spCaffeNetOutputBlobs);
const std::vector<float> floatScaleRatios(scaleInputToNetInputs.begin(), scaleInputToNetInputs.end()); const std::vector<float> floatScaleRatios(scaleInputToNetInputs.begin(), scaleInputToNetInputs.end());
upImpl->spResizeAndMergeCaffe->setScaleRatios(floatScaleRatios); upImpl->spResizeAndMergeCaffe->setScaleRatios(floatScaleRatios);
upImpl->spResizeAndMergeCaffe->Forward(caffeNetOutputBlobs, {upImpl->spHeatMapsBlob.get()}); upImpl->spResizeAndMergeCaffe->Forward(caffeNetOutputBlobs, {upImpl->spHeatMapsBlob.get()});
...@@ -417,7 +417,8 @@ namespace op ...@@ -417,7 +417,8 @@ namespace op
// Re-Process image // Re-Process image
// 1. Caffe deep network // 1. Caffe deep network
upImpl->spNets.at(0)->forwardPass(inputNetDataRoi); upImpl->spNets.at(0)->forwardPass(inputNetDataRoi);
std::vector<boost::shared_ptr<caffe::Blob<float>>> caffeNetOutputBlob{upImpl->spCaffeNetOutputBlobs[0]}; std::vector<std::shared_ptr<ArrayCpuGpu<float>>> caffeNetOutputBlob{
upImpl->spCaffeNetOutputBlobs[0]};
// Reshape blobs // Reshape blobs
if (!vectorsAreEqual(upImpl->mNetInput4DSizes.at(0), inputNetDataRoi.getSize())) if (!vectorsAreEqual(upImpl->mNetInput4DSizes.at(0), inputNetDataRoi.getSize()))
{ {
...@@ -431,8 +432,7 @@ namespace op ...@@ -431,8 +432,7 @@ namespace op
upImpl->mGpuId); upImpl->mGpuId);
} }
// 2. Resize heat maps + merge different scales // 2. Resize heat maps + merge different scales
// const auto caffeNetOutputBlobs = caffeNetSharedToPtr(upImpl->spCaffeNetOutputBlobs); const auto caffeNetOutputBlobs = arraySharedToPtr(caffeNetOutputBlob);
const auto caffeNetOutputBlobs = caffeNetSharedToPtr(caffeNetOutputBlob);
// const std::vector<float> floatScaleRatios( // const std::vector<float> floatScaleRatios(
// scaleInputToNetInputs.begin(), scaleInputToNetInputs.end()); // scaleInputToNetInputs.begin(), scaleInputToNetInputs.end());
const std::vector<float> floatScaleRatios{(float)scaleInputToNetInputs[0]}; const std::vector<float> floatScaleRatios{(float)scaleInputToNetInputs[0]};
......
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