我想使用 MaskRCNN 实现自定义图像分类器。
为了提高网络的速度，我想优化推理。
我已经使用过 OpenCV DNN 库，但我想用 OpenVINO 向前迈出一步。
我成功使用 OpenVINO 模型优化器 (python) 来构建代表我的网络的 .xml 和 .bin 文件。
我使用 Visual Studio 2017 成功构建了 OpenVINO 示例目录并运行了 MaskRCNNDemo 项目。
mask_rcnn_demo.exe -m .\Release\frozen_inference_graph.xml -i .\Release\input.jpg
InferenceEngine:
API version ............ 1.4
Build .................. 19154
[ INFO ] Parsing input parameters
[ INFO ] Files were added: 1
[ INFO ] .\Release\input.jpg
[ INFO ] Loading plugin
API version ............ 1.5
Build .................. win_20181005
Description ....... MKLDNNPlugin
[ INFO ] Loading network files
[ INFO ] Preparing input blobs
[ WARNING ] Image is resized from (4288, 2848) to (800, 800)
[ INFO ] Batch size is 1
[ INFO ] Preparing output blobs
[ INFO ] Loading model to the plugin
[ INFO ] Start inference (1 iterations)
Average running time of one iteration: 2593.81 ms
[ INFO ] Processing output blobs
[ INFO ] Detected class 16 with probability 0.986519: [2043.3, 1104.9], [2412.87, 1436.52]
[ INFO ] Image out.png created!
[ INFO ] Execution successful
然后我试图在一个单独的项目中重现这个项目......首先我必须观察依赖关系......
<MaskRCNNDemo>
//References
<format_reader/> => Open CV Images, resize it and get uchar data
<ie_cpu_extension/> => CPU extension for un-managed layers (?)
//Linker
format_reader.lib => Format Reader Lib (VINO Samples Compiled)
cpu_extension.lib => CPU extension Lib (VINO Samples Compiled)
inference_engined.lib => Inference Engine lib (VINO)
opencv_world401d.lib => OpenCV Lib
libiomp5md.lib => Dependancy
... (other libs)
有了它，我用我自己的类和打开图像的方式（多帧 tiff）构建了一个新项目。这项工作没有问题，我不会描述（我使用 CV DNN 推理引擎没有问题）。
我想构建与 MaskRCNNDemo 相同的项目：CustomIA
<CustomIA>
//References
None => I use my own libtiff way to open image and i resize with OpenCV
None => I will just add include to cpu_extension source code.
//Linker
opencv_world345d.lib => OpenCV 3.4.5 library
tiffd.lib => Libtiff Library
cpu_extension.lib => CPU extension compiled with sample
inference_engined.lib => Inference engine lib.
我将以下 dll 添加到项目目标目录：
cpu_extension.dll
inference_engined.dll
libiomp5md.dll
mkl_tiny_omp.dll
MKLDNNPlugind.dll
opencv_world345d.dll
tiffd.dll
tiffxxd.dll
我成功编译并执行，但我遇到了两个问题：
旧代码：
slog::info << "Loading plugin" << slog::endl;
InferencePlugin plugin = PluginDispatcher({ FLAGS_pp, "../../../lib/intel64" , "" }).getPluginByDevice(FLAGS_d);
/** Loading default extensions **/
if (FLAGS_d.find("CPU") != std::string::npos) {
/**
* cpu_extensions library is compiled from "extension" folder containing
* custom MKLDNNPlugin layer implementations. These layers are not supported
* by mkldnn, but they can be useful for inferring custom topologies.
**/
plugin.AddExtension(std::make_shared<Extensions::Cpu::CpuExtensions>());
}
/** Printing plugin version **/
printPluginVersion(plugin, std::cout);
输出 ：
[ INFO ] Loading plugin
API version ............ 1.5
Build .................. win_20181005
Description ....... MKLDNNPlugin
新代码：
VINOEngine::VINOEngine()
{
// Loading Plugin
std::cout << std::endl;
std::cout << "[INFO] - Loading VINO Plugin..." << std::endl;
this->plugin= PluginDispatcher({ "", "../../../lib/intel64" , "" }).getPluginByDevice("CPU");
this->plugin.AddExtension(std::make_shared<Extensions::Cpu::CpuExtensions>());
printPluginVersion(this->plugin, std::cout);
输出 ：
[INFO] - Loading VINO Plugin...
000001A242280A18 // Like memory adress ???
第二期：
当我尝试从新代码中提取我的 ROI 和掩码时，如果我有一个“匹配”，我总是有：
- 分数 =1.0
- x1=x2=0.0
- y1=y2=1.0
但是面具看起来很好提取......
新代码：
float score = box_info[2];
if (score > this->Conf_Threshold)
{
// On reconstruit les coordonnées de la box..
float x1 = std::min(std::max(0.0f, box_info[3] * Image.cols), static_cast<float>(Image.cols));
float y1 = std::min(std::max(0.0f, box_info[4] * Image.rows), static_cast<float>(Image.rows));
float x2 = std::min(std::max(0.0f, box_info[5] * Image.cols), static_cast<float>(Image.cols));
float y2 = std::min(std::max(0.0f, box_info[6] * Image.rows), static_cast<float>(Image.rows));
int box_width = std::min(static_cast<int>(std::max(0.0f, x2 - x1)), Image.cols);
int box_height = std::min(static_cast<int>(std::max(0.0f, y2 - y1)), Image.rows);
Image is resized from (4288, 2848) to (800, 800)
Detected class 62 with probability 1: [4288, 0], [4288, 0]
然后，当我没有正确的 bbox 坐标时，我不可能将蒙版放置在图像中并调整其大小......
有人知道我做得不好吗？
如何使用 cpu_extension 正确创建和链接 OpenVINO 项目？
谢谢 ！