Comments (14)
alalek
commented on May 18, 2024
4
3.4.3
This means that used OpenCV binaries are not from OpenVINO package (-openvino suffix is expected in version identifier).
Check cv.__file__ and cv.getBuildInformation() to confirm that.
sudo
Don't use sudo. At least it drops environment variables (due to security reasons).
from open_model_zoo.
dongyangli-del
commented on May 18, 2024
2
Hello, When I input the command " sudo python3 face_detection.py", it tells me that : Traceback (most recent call last):
File "face_detection.py", line 3, in
net = cv.dnn.readNet('face-detection-adas-0001.xml', 'face-detection-adas-0001.bin')
cv2.error: OpenCV(3.4.3) /home/pi/opencv-python/opencv/modules/dnn/src/dnn.cpp:2365: error: (-2:Unspecified error) Build OpenCV with Inference Engine to enable loading models from Model Optimizer. in function 'readFromModelOptimizer'
Have you ever come across a problem like this? Any good Suggestions? thank you!
from open_model_zoo.
snosov1
commented on May 18, 2024
1
@dkurt, any ideas?
from open_model_zoo.
dkurt
commented on May 18, 2024
@sovereignscout, Please show the output of the following python commands from your script:
import cv2 as cv
print(cv.__file__)from open_model_zoo.
farshadopencv
commented on May 18, 2024
Hi. I get same error when I use bin and xml files in readFromModelOptimizer function in openvino's version of opencv built in openvino.
I also build opencv 4.0.0-openvino and opencv 4.1.0 with
-DWITH_INF_ENGINE=ON -DENABLE_CXX11=ON
to use IE backend and it build successfully, but again I got error
Build OpenCV with Inference Engine to enable loading models from Model Optimizer. in function 'readFromModelOptimizer, when I use bin and xml files in readFromModelOptimizer function
from open_model_zoo.
alalek
commented on May 18, 2024
CMake output should contain these lines:
-- Detected InferenceEngine: cmake package
...
-- Inference Engine: YES (2019010000 / 1.6.0)
-- libs: /opt/intel/openvino_2019.1.094/deployment_tools/inference_engine/lib/intel64/libinference_engine.so
-- includes: /opt/intel/openvino_2019.1.094/deployment_tools/inference_engine/include
4.0.0
4.0.0-openvino
These OpenCV versions are not able to work properly with IE from OpenVINO 2019R1.
You should use OpenCV 4.1.0 / 4.1.0-openvino / master.
from open_model_zoo.
dkurt
commented on May 18, 2024
@farshadopencv, Please analyze the CMake summary. It contains all the information about your build: getBuildInformation
from open_model_zoo.
farshadopencv
commented on May 18, 2024
@alalek @dkurt Thanks for your help. Now I can build opencv 4.1.0 with IE backend. But now I encounter another problem. when I pass my bin, xml files of model into object_detection.cpp script, I have following error:
OpenCV(4.1.0) Error: Assertion failed (> Failed to initialize Inference Engine backend: Unsupported primitive of type: PriorBoxClustered name: PriorBoxClustered_5
..\src\mkldnn_plugin\mkldnn_node.cpp:167
c:\program files (x86)\intelswtools\openvino_2019.1.087\deployment_tools\inference_engine\include\details/ie_exception_conversion.hpp:71
) in cv::dnn::InfEngineBackendNet::initPlugin, file C:\o\opencv\modules\dnn\src\op_inf_engine.cpp, line 813
I changed object_detection.cpp to avoid parser as follows:
**#define _CRT_SECURE_NO_WARNINGS
#include
#include
#include <opencv2/dnn.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
#include "common.hpp"
std::string keys =
"{ help h | | Print help message. }"
"{ @alias | | An alias name of model to extract preprocessing parameters from models.yml file. }"
"{ zoo | models.yml | An optional path to file with preprocessing parameters }"
"{ device | 0 | camera device number. }"
"{ input i | | Path to input image or video file. Skip this argument to capture frames from a camera. }"
"{ framework f | | Optional name of an origin framework of the model. Detect it automatically if it does not set. }"
"{ classes | | Optional path to a text file with names of classes to label detected objects. }"
"{ thr | .5 | Confidence threshold. }"
"{ nms | .4 | Non-maximum suppression threshold. }"
"{ backend | 0 | Choose one of computation backends: "
"0: automatically (by default), "
"1: Halide language (http://halide-lang.org/), "
"2: Intel's Deep Learning Inference Engine (https://software.intel.com/openvino-toolkit), "
"3: OpenCV implementation }"
"{ target | 0 | Choose one of target computation devices: "
"0: CPU target (by default), "
"1: OpenCL, "
"2: OpenCL fp16 (half-float precision), "
"3: VPU }";
using namespace cv;
using namespace dnn;
float confThreshold, nmsThreshold;
std::vectorstd::string classes;
void postprocess(Mat& frame, const std::vector& out, Net& net);
void drawPred(int classId, float conf, int left, int top, int right, int bottom, Mat& frame);
void callback(int pos, void* userdata);
std::vector getOutputsNames(const Net& net);
int main(int argc, char** argv)
{
confThreshold = 0.6f;
nmsThreshold = .4f;
float scale = 0.00784f;
Scalar mean = Scalar(127.5, 127.5, 127.5);
bool swapRB = true;
int inpWidth = 300;
int inpHeight = 300;
int backend = 2;
int target = 0;
std::string modelPath = "E:\carPlateSsdlite.bin";
std::string configPath = "E:\carPlateSsdlite.xml";
Net net = readNet(modelPath, configPath);
net.setPreferableBackend(backend);
net.setPreferableTarget(target);
std::vector<String> outNames = net.getUnconnectedOutLayersNames();
static const std::string kWinName = "Deep learning object detection in OpenCV";
namedWindow(kWinName, WINDOW_NORMAL);
int initialConf = (int)(confThreshold * 100);
createTrackbar("Confidence threshold, %", kWinName, &initialConf, 99, callback);
Mat blob;
Mat frame = imread("E:\img25.jpg", 1);
while (waitKey(1) < 0)
{
if (frame.empty())
{
waitKey();
break;
}
Size inpSize(inpWidth > 0 ? inpWidth : frame.cols,
inpHeight > 0 ? inpHeight : frame.rows);
blobFromImage(frame, blob, scale, inpSize, mean, swapRB, false);
net.setInput(blob);
if (net.getLayer(0)->outputNameToIndex("im_info") != -1) // Faster-RCNN or R-FCN
{
resize(frame, frame, inpSize);
Mat imInfo = (Mat_<float>(1, 3) << inpSize.height, inpSize.width, 1.6f);
net.setInput(imInfo, "im_info");
}
std::vector<Mat> outs;
net.forward(outs, outNames);
postprocess(frame, outs, net);
std::vector<double> layersTimes;
double freq = getTickFrequency() / 1000;
double t = net.getPerfProfile(layersTimes) / freq;
std::string label = format("Inference time: %.2f ms", t);
putText(frame, label, Point(0, 15), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 255, 0));
imshow(kWinName, frame);
}
return 0;
}
void postprocess(Mat& frame, const std::vector& outs, Net& net)
{
static std::vector outLayers = net.getUnconnectedOutLayers();
static std::string outLayerType = net.getLayer(outLayers[0])->type;
std::vector<int> classIds;
std::vector<float> confidences;
std::vector<Rect> boxes;
if (outLayerType == "DetectionOutput")
{
CV_Assert(outs.size() > 0);
for (size_t k = 0; k < outs.size(); k++)
{
float* data = (float*)outs[k].data;
for (size_t i = 0; i < outs[k].total(); i += 7)
{
float confidence = data[i + 2];
if (confidence > confThreshold)
{
int left = (int)data[i + 3];
int top = (int)data[i + 4];
int right = (int)data[i + 5];
int bottom = (int)data[i + 6];
int width = right - left + 1;
int height = bottom - top + 1;
if (width * height <= 1)
{
left = (int)(data[i + 3] * frame.cols);
top = (int)(data[i + 4] * frame.rows);
right = (int)(data[i + 5] * frame.cols);
bottom = (int)(data[i + 6] * frame.rows);
width = right - left + 1;
height = bottom - top + 1;
}
classIds.push_back((int)(data[i + 1]) - 1); // Skip 0th background class id.
boxes.push_back(Rect(left, top, width, height));
confidences.push_back(confidence);
}
}
}
}
else if (outLayerType == "Region")
{
for (size_t i = 0; i < outs.size(); ++i)
{
float* data = (float*)outs[i].data;
for (int j = 0; j < outs[i].rows; ++j, data += outs[i].cols)
{
Mat scores = outs[i].row(j).colRange(5, outs[i].cols);
Point classIdPoint;
double confidence;
minMaxLoc(scores, 0, &confidence, 0, &classIdPoint);
if (confidence > confThreshold)
{
int centerX = (int)(data[0] * frame.cols);
int centerY = (int)(data[1] * frame.rows);
int width = (int)(data[2] * frame.cols);
int height = (int)(data[3] * frame.rows);
int left = centerX - width / 2;
int top = centerY - height / 2;
classIds.push_back(classIdPoint.x);
confidences.push_back((float)confidence);
boxes.push_back(Rect(left, top, width, height));
}
}
}
}
else
CV_Error(Error::StsNotImplemented, "Unknown output layer type: " + outLayerType);
std::vector<int> indices;
NMSBoxes(boxes, confidences, confThreshold, nmsThreshold, indices);
for (size_t i = 0; i < indices.size(); ++i)
{
int idx = indices[i];
Rect box = boxes[idx];
drawPred(classIds[idx], confidences[idx], box.x, box.y,
box.x + box.width, box.y + box.height, frame);
}
}
void drawPred(int classId, float conf, int left, int top, int right, int bottom, Mat& frame)
{
rectangle(frame, Point(left, top), Point(right, bottom), Scalar(0, 255, 0));
std::string label = format("%.2f", conf);
if (!classes.empty())
{
CV_Assert(classId < (int)classes.size());
label = classes[classId] + ": " + label;
}
int baseLine;
Size labelSize = getTextSize(label, FONT_HERSHEY_SIMPLEX, 0.5, 1, &baseLine);
top = max(top, labelSize.height);
rectangle(frame, Point(left, top - labelSize.height),
Point(left + labelSize.width, top + baseLine), Scalar::all(255), FILLED);
putText(frame, label, Point(left, top), FONT_HERSHEY_SIMPLEX, 0.5, Scalar());
}
void callback(int pos, void*)
{
confThreshold = pos * 0.01f;
}**
from open_model_zoo.
dkurt
commented on May 18, 2024
OpenCV(4.1.0) Error: Assertion failed (> Failed to initialize Inference Engine backend: Unsupported primitive of type: PriorBoxClustered name: PriorBoxClustered_5
..\src\mkldnn_plugin\mkldnn_node.cpp:167
c:\program files (x86)\intelswtools\openvino_2019.1.087\deployment_tools\inference_engine\include\details/ie_exception_conversion.hpp:71
) in cv::dnn::InfEngineBackendNet::initPlugin, file C:\o\opencv\modules\dnn\src\op_inf_engine.cpp, line 813
Similar issue: opencv/opencv#14409. It looks like there is something wrong with Windows package.
@farshadopencv please check the solution from opencv/opencv#14409 (comment). It looks like your CPU might also don't support AVX2.
from open_model_zoo.
cuixing158
commented on May 18, 2024
@farshadopencv thank you give a example!!! I ran successfully on "Release" mode
from open_model_zoo.
Welyweloo
commented on May 18, 2024
Hello @alalek,
I've been trying to understand your previous message.
Where should I add that -openvino suffix please? I am having the same issue.
(cv) aurelie@aurelie-VirtualBox:~/LO_Computervision_YOLO$ python object_detection_caffe.py --input IMG_4587.MOV --output ./
/home/aurelie/.virtualenvs/cv/lib/python3.8/site-packages/cv2/cv2.cpython-38-x86_64-linux-gnu.so
General configuration for OpenCV 4.5.1 =====================================
Version control: 4.5.1-dirty
Platform:
Timestamp: 2021-01-02T13:00:02Z
Host: Linux 4.15.0-1077-gcp x86_64
CMake: 3.18.4
CMake generator: Unix Makefiles
CMake build tool: /bin/gmake
Configuration: Release
CPU/HW features:
Baseline: SSE SSE2 SSE3
requested: SSE3
Dispatched code generation: SSE4_1 SSE4_2 FP16 AVX AVX2 AVX512_SKX
requested: SSE4_1 SSE4_2 AVX FP16 AVX2 AVX512_SKX
SSE4_1 (15 files): + SSSE3 SSE4_1
SSE4_2 (1 files): + SSSE3 SSE4_1 POPCNT SSE4_2
FP16 (0 files): + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 AVX
AVX (4 files): + SSSE3 SSE4_1 POPCNT SSE4_2 AVX
AVX2 (29 files): + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 FMA3 AVX AVX2
AVX512_SKX (4 files): + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 FMA3 AVX AVX2 AVX_512F AVX512_COMMON AVX512_SKX
C/C++:
Built as dynamic libs?: NO
C++ standard: 11
C++ Compiler: /usr/lib/ccache/compilers/c++ (ver 9.3.1)
C++ flags (Release): -Wl,-strip-all -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Wsuggest-override -Wno-delete-non-virtual-dtor -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -fvisibility-inlines-hidden -O3 -DNDEBUG -DNDEBUG
C++ flags (Debug): -Wl,-strip-all -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Wsuggest-override -Wno-delete-non-virtual-dtor -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -fvisibility-inlines-hidden -g -O0 -DDEBUG -D_DEBUG
C Compiler: /usr/lib/ccache/compilers/cc
C flags (Release): -Wl,-strip-all -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Wno-comment -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -O3 -DNDEBUG -DNDEBUG
C flags (Debug): -Wl,-strip-all -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Wno-comment -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -g -O0 -DDEBUG -D_DEBUG
Linker flags (Release): -Wl,--exclude-libs,libippicv.a -Wl,--exclude-libs,libippiw.a -L/root/ffmpeg_build/lib -Wl,--gc-sections -Wl,--as-needed
Linker flags (Debug): -Wl,--exclude-libs,libippicv.a -Wl,--exclude-libs,libippiw.a -L/root/ffmpeg_build/lib -Wl,--gc-sections -Wl,--as-needed
ccache: YES
Precompiled headers: NO
Extra dependencies: ade Qt5::Core Qt5::Gui Qt5::Widgets Qt5::Test Qt5::Concurrent /lib64/libpng.so /lib64/libz.so dl m pthread rt
3rdparty dependencies: ittnotify libprotobuf libjpeg-turbo libwebp libtiff libopenjp2 IlmImf quirc ippiw ippicv
OpenCV modules:
To be built: calib3d core dnn features2d flann gapi highgui imgcodecs imgproc ml objdetect photo python3 stitching video videoio
Disabled: world
Disabled by dependency: -
Unavailable: java python2 ts
Applications: -
Documentation: NO
Non-free algorithms: NO
GUI:
QT: YES (ver 5.15.0)
QT OpenGL support: NO
GTK+: NO
VTK support: NO
Media I/O:
ZLib: /lib64/libz.so (ver 1.2.7)
JPEG: libjpeg-turbo (ver 2.0.6-62)
WEBP: build (ver encoder: 0x020f)
PNG: /lib64/libpng.so (ver 1.5.13)
TIFF: build (ver 42 - 4.0.10)
JPEG 2000: build (ver 2.3.1)
OpenEXR: build (ver 2.3.0)
HDR: YES
SUNRASTER: YES
PXM: YES
PFM: YES
Video I/O:
DC1394: NO
FFMPEG: YES
avcodec: YES (58.109.100)
avformat: YES (58.61.100)
avutil: YES (56.60.100)
swscale: YES (5.8.100)
avresample: NO
GStreamer: NO
v4l/v4l2: YES (linux/videodev2.h)
Parallel framework: pthreads
Trace: YES (with Intel ITT)
Other third-party libraries:
Intel IPP: 2020.0.0 Gold [2020.0.0]
at: /tmp/pip-req-build-ms668fyv/_skbuild/linux-x86_64-3.8/cmake-build/3rdparty/ippicv/ippicv_lnx/icv
Intel IPP IW: sources (2020.0.0)
at: /tmp/pip-req-build-ms668fyv/_skbuild/linux-x86_64-3.8/cmake-build/3rdparty/ippicv/ippicv_lnx/iw
Lapack: NO
Eigen: NO
Custom HAL: NO
Protobuf: build (3.5.1)
OpenCL: YES (no extra features)
Include path: /tmp/pip-req-build-ms668fyv/opencv/3rdparty/include/opencl/1.2
Link libraries: Dynamic load
Python 3:
Interpreter: /opt/python/cp38-cp38/bin/python (ver 3.8.6)
Libraries: libpython3.8.a (ver 3.8.6)
numpy: /tmp/pip-build-env-qm375ina/overlay/lib/python3.8/site-packages/numpy/core/include (ver 1.17.3)
install path: python
Python (for build): /bin/python2.7
Java:
ant: NO
JNI: NO
Java wrappers: NO
Java tests: NO
Install to: /tmp/pip-req-build-ms668fyv/_skbuild/linux-x86_64-3.8/cmake-install
-----------------------------------------------------------------
Initializing...
Traceback (most recent call last):
File "object_detection_caffe.py", line 199, in <module>
net = cv2.dnn.readNet('/open_model_zoo-master/tools/downloader/intel/vehicle-attributes-recognition-barrier-0039/FP32/vehicle-attributes-recognition-barrier-0039.bin',
cv2.error: OpenCV(4.5.1) /tmp/pip-req-build-ms668fyv/opencv/modules/dnn/src/dnn.cpp:3901: error: (-2:Unspecified error) Build OpenCV with Inference Engine to enable loading models from Model Optimizer. in function 'readFromModelOptimizer'
from open_model_zoo.
shahla-ai
commented on May 18, 2024
hi @farshadopencv , I wish you can help me
can you tell me how you compiled OpenCV with openvino IE backend from source ?
all documentations show how to use openvino's OpenCV , but that is not what I want
best regards
from open_model_zoo.
dkurt
commented on May 18, 2024
@shahla-ai, https://github.com/opencv/opencv/wiki/Intel%27s-Deep-Learning-Inference-Engine-backend#build-opencv-from-source
from open_model_zoo.
ZhongQiyu
commented on May 18, 2024
3.4.3
This means that used OpenCV binaries are not from OpenVINO package (
-openvinosuffix is expected in version identifier). Checkcv.__file__andcv.getBuildInformation()to confirm that.sudo
Don't use
sudo. At least it drops environment variables (due to security reasons).
@alalek I was trying to figure out the information generated fromcv.getBuildInformation(), and for the point I am getting myself around with the version information:
General configuration for OpenCV 4.5.5 =====================================
Version control: 4.5.5
Is this expected to be adding a suffix of-openvino?
from open_model_zoo.
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