I would like to implement a custom image classifier using MaskRCNN.
In order to increase the speed of the network, i would like to optimise the inference.
I already used OpenCV DNN library, but i would like to do a step forward with OpenVINO.
I used successfully OpenVINO Model optimiser (python), to build the .xml and .bin file representing my network.
I successfully builded OpenVINO Sample directory with Visual Studio 2017 and run MaskRCNNDemo project.
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
Then i tried to reproduce this project in a separate project... First i had to watch dependancies...
<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)
With it i've build a new project, with my own classes and way to open images (multiframe tiff). This work without problem then i will not describe (i use with a CV DNN inference engine without problem).
I wanted to build the same project than MaskRCNNDemo : 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.
I added the following dll to the project target dir :
cpu_extension.dll
inference_engined.dll
libiomp5md.dll
mkl_tiny_omp.dll
MKLDNNPlugind.dll
opencv_world345d.dll
tiffd.dll
tiffxxd.dll
I successfully compiled and execute but i faced two issues :
OLD CODE:
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);
OUTPUT :
[ INFO ] Loading plugin
API version ............ 1.5
Build .................. win_20181005
Description ....... MKLDNNPlugin
NEW CODE:
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);
OUTPUT :
[INFO] - Loading VINO Plugin...
000001A242280A18 // Like memory adress ???
Second Issue :
When i try to extract my ROI and masks from New Code, if i have a "match", i always have :
- score =1.0
- x1=x2=0.0
- y1=y2=1.0
But the mask looks well extracted...
New Code :
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]
Then it is impossible for me to place the mask in the image and resize it while i don't have correct bbox coordinate...
Do anybody have an idea about what i make badly ?
How to create and link correctly an OpenVINO project using cpu_extension ?
Thanks !
