I trying to install OpenVINO Toolkit version 2019R1 which the latest version of today (2019-04-11). But during installation I got this error:

Failed building wheel for onnx

I installed everything as the documentation before I was using version 2018R5 and it was installed successfully and working well, but now I want to install the new version, but it gives me the above error.

It is the complete stack trace:

Building wheels for collected packages: onnx
Building wheel for onnx (setup.py) ... error
Complete output from command c:\users\bahra\appdata\local\programs\python\python37\python.exe -u -c "import setuptools, tokenize;file='C:\Users\bahra\AppData\Local\Temp\pip-install-7w3v8o85\onnx\setup.py';f=getattr(tokenize, 'open', open)(file);code=f.read().replace('\r\n', '\n');f.close();exec(compile(code, file, 'exec'))" bdist_wheel -d C:\Users\bahra\AppData\Local\Temp\pip-wheel-zqjeth4c --python-tag cp37:
fatal: not a git repository (or any of the parent directories): .git
running bdist_wheel
running build
running build_py
running create_version
running cmake_build
-- Building for: Visual Studio 15 2017
-- Build type not set - defaulting to Release
-- Selecting Windows SDK version 10.0.17763.0 to target Windows 10.0.17134.
-- The C compiler identification is MSVC 19.16.27030.1
-- The CXX compiler identification is MSVC 19.16.27030.1
-- Check for working C compiler: C:/Program Files (x86)/Microsoft Visual Studio/2017/Enterprise/VC/Tools/MSVC/14.16.27023/bin/Hostx86/x64/cl.exe
-- Check for working C compiler: C:/Program Files (x86)/Microsoft Visual Studio/2017/Enterprise/VC/Tools/MSVC/14.16.27023/bin/Hostx86/x64/cl.exe -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Check for working CXX compiler: C:/Program Files (x86)/Microsoft Visual Studio/2017/Enterprise/VC/Tools/MSVC/14.16.27023/bin/Hostx86/x64/cl.exe
-- Check for working CXX compiler: C:/Program Files (x86)/Microsoft Visual Studio/2017/Enterprise/VC/Tools/MSVC/14.16.27023/bin/Hostx86/x64/cl.exe -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Detecting CXX compile features
-- Detecting CXX compile features - done
CMake Error at CMakeLists.txt:217 (message):
Protobuf compiler not found
Call Stack (most recent call first):
CMakeLists.txt:248 (relative_protobuf_generate_cpp)

-- Configuring incomplete, errors occurred!
See also "C:/Users/bahra/AppData/Local/Temp/pip-install-7w3v8o85/onnx/.setuptools-cmake-build/CMakeFiles/CMakeOutput.log".
Traceback (most recent call last):
File "", line 1, in
File "C:\Users\bahra\AppData\Local\Temp\pip-install-7w3v8o85\onnx\setup.py", line 328, in
'backend-test-tools = onnx.backend.test.cmd_tools:main',
File "c:\users\bahra\appdata\local\programs\python\python37\lib\site-packages\setuptools_init_.py", line 145, in setup
return distutils.core.setup(**attrs)
File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\core.py", line 148, in setup
dist.run_commands()
File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\dist.py", line 966, in run_commands
self.run_command(cmd)
File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\dist.py", line 985, in run_command
cmd_obj.run()
File "C:\Users\bahra\AppData\Roaming\Python\Python37\site-packages\wheel\bdist_wheel.py", line 192, in run
self.run_command('build')
File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\dist.py", line 985, in run_command
cmd_obj.run()
File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\command\build.py", line 135, in run
self.run_command(cmd_name)
File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\dist.py", line 985, in run_command
cmd_obj.run()
File "C:\Users\bahra\AppData\Local\Temp\pip-install-7w3v8o85\onnx\setup.py", line 203, in run
self.run_command('cmake_build')
File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\dist.py", line 985, in run_command
cmd_obj.run()
File "C:\Users\bahra\AppData\Local\Temp\pip-install-7w3v8o85\onnx\setup.py", line 190, in run
subprocess.check_call(cmake_args)
File "c:\users\bahra\appdata\local\programs\python\python37\lib\subprocess.py", line 347, in check_call
raise CalledProcessError(retcode, cmd)
subprocess.CalledProcessError: Command '['C:\Program Files\CMake\bin\cmake.exe', '-DPYTHON_INCLUDE_DIR=c:\users\bahra\appdata\local\programs\python\python37\include', '-DPYTHON_EXECUTABLE=c:\users\bahra\appdata\local\programs\python\python37\python.exe', '-DBUILD_ONNX_PYTHON=ON', '-DCMAKE_EXPORT_COMPILE_COMMANDS=ON', '-DONNX_NAMESPACE=onnx', '-DPY_EXT_SUFFIX=.cp37-win_amd64.pyd', '-DPY_VERSION=3.7', '-DONNX_USE_MSVC_STATIC_RUNTIME=ON', '-DCMAKE_GENERATOR_PLATFORM=x64', 'C:\Users\bahra\AppData\Local\Temp\pip-install-7w3v8o85\onnx']' returned non-zero exit status 1.

---

Failed building wheel for onnx
Running setup.py clean for onnx
Failed to build onnx
Installing collected packages: onnx, test-generator, defusedxml
Running setup.py install for onnx ... error
Complete output from command c:\users\bahra\appdata\local\programs\python\python37\python.exe -u -c "import setuptools, tokenize;file='C:\Users\bahra\AppData\Local\Temp\pip-install-7w3v8o85\onnx\setup.py';f=getattr(tokenize, 'open', open)(file);code=f.read().replace('\r\n', '\n');f.close();exec(compile(code, file, 'exec'))" install --record C:\Users\bahra\AppData\Local\Temp\pip-record-aj9pyef5\install-record.txt --single-version-externally-managed --compile --user --prefix=:
fatal: not a git repository (or any of the parent directories): .git
running install
running build
running build_py
running create_version
running cmake_build
-- Selecting Windows SDK version 10.0.17763.0 to target Windows 10.0.17134.
CMake Error at CMakeLists.txt:217 (message):
Protobuf compiler not found
Call Stack (most recent call first):
CMakeLists.txt:248 (relative_protobuf_generate_cpp)

-- Configuring incomplete, errors occurred!
See also "C:/Users/bahra/AppData/Local/Temp/pip-install-7w3v8o85/onnx/.setuptools-cmake-build/CMakeFiles/CMakeOutput.log".
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "C:\Users\bahra\AppData\Local\Temp\pip-install-7w3v8o85\onnx\setup.py", line 328, in <module>
    'backend-test-tools = onnx.backend.test.cmd_tools:main',
  File "c:\users\bahra\appdata\local\programs\python\python37\lib\site-packages\setuptools\__init__.py", line 145, in setup
    return distutils.core.setup(**attrs)
  File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\core.py", line 148, in setup
    dist.run_commands()
  File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\dist.py", line 966, in run_commands
    self.run_command(cmd)
  File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\dist.py", line 985, in run_command
    cmd_obj.run()
  File "c:\users\bahra\appdata\local\programs\python\python37\lib\site-packages\setuptools\command\install.py", line 61, in run
    return orig.install.run(self)
  File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\command\install.py", line 545, in run
    self.run_command('build')
  File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\cmd.py", line 313, in run_command
    self.distribution.run_command(command)
  File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\dist.py", line 985, in run_command
    cmd_obj.run()
  File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\command\build.py", line 135, in run
    self.run_command(cmd_name)
  File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\cmd.py", line 313, in run_command
    self.distribution.run_command(command)
  File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\dist.py", line 985, in run_command
    cmd_obj.run()
  File "C:\Users\bahra\AppData\Local\Temp\pip-install-7w3v8o85\onnx\setup.py", line 203, in run
    self.run_command('cmake_build')
  File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\cmd.py", line 313, in run_command
    self.distribution.run_command(command)
  File "c:\users\bahra\appdata\local\programs\python\python37\lib\distutils\dist.py", line 985, in run_command
    cmd_obj.run()
  File "C:\Users\bahra\AppData\Local\Temp\pip-install-7w3v8o85\onnx\setup.py", line 190, in run
    subprocess.check_call(cmake_args)
  File "c:\users\bahra\appdata\local\programs\python\python37\lib\subprocess.py", line 347, in check_call
    raise CalledProcessError(retcode, cmd)
subprocess.CalledProcessError: Command '['C:\\Program Files\\CMake\\bin\\cmake.exe', '-DPYTHON_INCLUDE_DIR=c:\\users\\bahra\\appdata\\local\\programs\\python\\python37\\include', '-DPYTHON_EXECUTABLE=c:\\users\\bahra\\appdata\\local\\programs\\python\\python37\\python.exe', '-DBUILD_ONNX_PYTHON=ON', '-DCMAKE_EXPORT_COMPILE_COMMANDS=ON', '-DONNX_NAMESPACE=onnx', '-DPY_EXT_SUFFIX=.cp37-win_amd64.pyd', '-DPY_VERSION=3.7', '-DONNX_USE_MSVC_STATIC_RUNTIME=ON', '-DCMAKE_GENERATOR_PLATFORM=x64', 'C:\\Users\\bahra\\AppData\\Local\\Temp\\pip-install-7w3v8o85\\onnx']' returned non-zero exit status 1.

----------------------------------------

Command "c:\users\bahra\appdata\local\programs\python\python37\python.exe -u -c "import setuptools, tokenize;file='C:\Users\bahra\AppData\Local\Temp\pip-install-7w3v8o85\onnx\setup.py';f=getattr(tokenize, 'open', open)(file);code=f.read().replace('\r\n', '\n');f.close();exec(compile(code, file, 'exec'))" install --record C:\Users\bahra\AppData\Local\Temp\pip-record-aj9pyef5\install-record.txt --single-version-externally-managed --compile --user --prefix=" failed with error code 1 in C:\Users\bahra\AppData\Local\Temp\pip-install-7w3v8o85\onnx\

---

Warning: please expect that Model Optimizer conversion might be slow.
You can boost conversion speed by installing protobuf-*.egg located in the
"model-optimizer\install_prerequisites" folder or building protobuf library from sources.
For more information please refer to Model Optimizer FAQ, question #80.

Current label file for the person-vehicle-bike-detection-crossroad-0078 model only contains 3 objects. Could you provide the complete label file with all objects trained? thanks.

in the human_pose_estimation_demo,when i use "-d MYRIAD",
i will get error ：
[35mE: [ncAPI] [ 0] ncDeviceOpen:668 failed to find device
[0m
[ ERROR ] Can not init USB device: NC_DEVICE_NOT_FOUND

I'm not familiar with license and law.
What is the license for human pose estimation model (human-pose-estimation-0001)?
Also, Can this model be used in commercial applications? Thanks,

• https://download.01.org/opencv/2019/open_model_zoo/R1/2019/human-pose-estimation-0001/FP32/
• https://github.com/opencv/openvino_training_extensions/tree/develop/pytorch_toolkit/human_pose_estimation

I would like to try and replicate something like the smart classroom demo but I only am interested with the raising hand detection. My questions are:

1. Considering on the fact I dont need other functionality, basically I just need person-detection-raisinghand-recognition-0001 (both bin and xml) right or do i need to use all 5 of the models like the smart classroom models?
   2.I have tried numerous ways on how to actually start coding(visual studio,pycharm) and after a week I am still stuck at square one so Can anybody please guide me step by step on how to actually setup my environment?

Hi, I am a bit confused with the output shape of text-detection-0001.

As stated in paper:

As shown in Fig. 3, the whole model has two separate headers, one for text/non-text prediction, and the other for link prediction. Softmax is used in both, so their outputs have 1*2=2 and 8*2=16 channels, respectively.

As stated in model description:

The net outputs two blobs. Refer to PixelNet for details.
[1x2x192x320] - logits related to text/no-text classification for each pixel.
[1x8x192x320] - logits related to linkage between pixels and their neighbors.

Shapes of "logits related to linkage between pixels and their neighbors" from description and paper are different.

And model's outputs shape is (1, 16, 192, 320) in single object, which is a third output shape (not described in description or paper). What does it mean? Please help to understand.

Hi,
I see that each HumanPose is constituted by a vector of cv::Point2f keypoints and a single confidence score for the whole pose, but I would like the score for each keypoint.

Looking at the code it seems that peak.cpp is the code part responsible for the computation of the entire pose score, but I do not understand where the single keypoint score is stored.

Could you please help me?

Thank you,
Cataldo

Hello. I am trying to use open vino's version of opencv which is already build with IE backend but i am unable to do so. Whenever i try to load .xml and .bin files of the model in the cv.dnn.readNet , i get the following error:

Traceback (most recent call last):
File "facedetection.py", line 16, in
'pruned_mobilenet_reduced_ssd_shared_weights/dldt/face-detection-adas-0001.xml')
cv2.error: OpenCV(4.0.0) /io/opencv/modules/dnn/src/dnn.cpp:2538: error: (-2:Unspecified error) Build OpenCV with Inference Engine to enable loading models from Model Optimizer. in function 'readFromModelOptimizer

The installation guide says to source the /opt/intel/openvino_2019.1.094/bin/setupvars.sh script in order to update the $OpenCV_DIR variable which I did but it didnt work. When i echo the variable, it points to the following path:

/opt/intel/openvino_2019.1.094/opencv/cmake

I even tried to sym link the cv2.so file from /opt/intel/openvino_2019.1.094/python/python3.5/ directory to the /usr/local/lib/python3.5/dist-packages/ directory but still it doesnt work.
Can you'll please enlist the exact steps to be taken or where i am going wrong? Thanks in advance.

my envs: openVINO2019.1.148+win10+VS2015
when i use face-detection-adas-0001.xml,face-detection-adas-0001.bin model (from here)to test correctness，the facemodel can't forward,throw a exception, any body give a advice? thanks

        Size model_size = Size( 672, 384);
	string xmlFile = "D:\\Downloads\\face-detection-adas-0001.xml"; // 1*3*384*672  N*C*H*W输入
	string model = "D:\\Downloads\\face-detection-adas-0001.bin";
	Net facemodel = readNetFromModelOptimizer(xmlFile, model);
	facemodel.setPreferableBackend(DNN_BACKEND_INFERENCE_ENGINE);
	facemodel.setPreferableTarget(DNN_TARGET_CPU);

	// Process frames.
	Mat frame;
	VideoCapture cap(0);
	while (waitKey(1)<0)
	{
		cap >> frame;
		Mat blob;
		 blobFromImage(frame, blob, 1, model_size);
		 facemodel.setInput(blob);
		 Mat outs = facemodel.forward(); // here is exception, 0x00007FFE2FB7D4F6 (cpu_extension_avx2.dll)处(位于 OpenVINO.exe 中)引发的异常: 0xC0000005: 读取位置 0x000000000000000F 时发生访问冲突。如有适用于此异常的处理程序，该程序便可安全地继续运行。

		for (size_t i = 0; i < outs.rows; i++)
		{
			// process ...

		}
		imshow("", frame);
	}

human-pose-estimation-0001 experiment results is okay, and in order to further study, .caffemodel and .prototxt files are needed, Are there the links to them ?

I downloaded the model "mobilenet-ssd" with the downloader.py, then I got a file named "ssd_mobilenet_v2_coco.frozen.pb".
I try to load this model with command "net = cv2.dnn.readNetFromTensorflow("ssd_mobilenet_v2_coco.frozen.pb")", then I got following error: "cv2.error: OpenCV(3.4.4) C:\projects\opencv-python\opencv\modules\dnn\src\tensorflow\tf_importer.cpp:497: error: (-2:Unspecified error) Input layer not found: Postprocessor/BatchMultiClassNonMaxSuppression/map/while/NextIteration in function 'cv::dnn::experimental_dnn_34_v10::`anonymous-namespace'::TFImporter::connect'"

Anyone know what's going on here? And how to fix this?

./downloader.py --name resnet-50

###############|| Downloading topologies ||###############

========= Downloading /home/biaolitao/open_model_zoo/model_downloader/classification/resnet/v1/50/caffe/resnet-50.prototxt
Error Connecting: ('Connection aborted.', ConnectionResetError(104, 'Connection reset by peer'))

###############|| Post processing ||###############

FAILED:
resnet-50

I'm using NCS2 with Raspi3 B+. I followed the instructions from the official page to install latest version of OpenVino toolkit on my Raspbian OS Stretch. The facial detection example works fine with object_detection_sample_ssd. So, I downloaded the facial-landmarks-35-adas-0002.bin and .xml in the similar manner and tried running it with the following command: ./armv7l/Release/object_detection_sample_ssd -m facial-landmarks-35-adas-0002.xml -d MYRIAD -i ~/image.png

It gives the following output:
[ INFO ] InferenceEngine:
API version ............ 1.6
Build .................. 22443
Parsing input parameters
[ INFO ] Files were added: 1
[ INFO ] /home/pi/image.png
[ INFO ] Loading plugin

API version ............ 1.6
Build .................. 22443
Description ....... myriadPlugin

[ INFO ] Loading network files:
facial-landmarks-35-adas-0002.xml
facial-landmarks-35-adas-0002.bin
[ INFO ] Preparing input blobs
[ INFO ] Batch size is 1
[ INFO ] Preparing output blobs
[ ERROR ] Can't find a DetectionOutput layer in the topology

I got the same error with the 2018 OpenVino toolkit.

I am using the text-recognition model to perform OCR. The model has an output that I have been unable to decode.
This is the class I'm using to generate the model output.

class TextRecognizer:
    def __init__(self):
        model_xml = 'models/text-recognition-0012.xml'
        model_bin = 'models/text-recognition-0012.bin'
        
        plugin = IEPlugin(device='CPU')
        net = IENetwork(model=model_xml, weights=model_bin)
        plugin.add_cpu_extension("/home/claudio/inference_engine_samples_build/intel64/Release/lib/libcpu_extension.so")
        
        supported_layers = plugin.get_supported_layers(net)
        not_supported_layers = [l for l in net.layers.keys() if l not in supported_layers]
        if len(not_supported_layers) != 0:
            print('thing')
        
        print("Preparing input blobs")
        self.input_blob = next(iter(net.inputs))
        self.out_blob = next(iter(net.outputs))
        
        print("Loading model to the plugin")
        self.exec_net = plugin.load(network=net)
        del net
        
    def process(self, img_source):
        img = img_source.copy()
        input_width = 120
        input_height = 32
        img_height = img.shape[0]
        img_width = img.shape[1]
        # rw = img_width/float(input_width)
        # rh = img_height/float(input_height)
        #img = cv2.resize(img, (input_width, input_height))
        plot_gray(img)
        blob = cv2.dnn.blobFromImage(img, 1.0, (input_width, input_height))
        tt.tic()
        
        res = self.exec_net.infer()
        res = res[self.out_blob]
        tt.toc("Infer")
        #print(res.shape)
        #print(res)
        return res

And this is the function I wrote for CTC Decoding.

symbols = "0123456789abcdefghijklmnopqrstuvwxyz#"

def ctc_decoder(data, alphabet):
    result = ""
    prev_pad = False
    num_classes = len(alphabet)
    for i in range(data.shape[0]):
        symbol = alphabet[np.argmax(data[i])]
        if symbol != alphabet[-1]:
            if len(result) == 0 or prev_pad or (len(result) > 0 and symbol != result[-1]):
                prev_pad = False
                result = result + symbol
        else:
            prev_pad = True
    return result

The text detection demo outputs the expected text, but with my decoder I only get nonsense. How do I properly use and decode the model?

uests.exceptions.ConnectionError: HTTPSConnectionPool(host='docs.google.com', port=443): Max retries exceeded with url: /uc?export=download&id=0BzKzrI_SkD1_MjFjNTlnempHNWs (Caused by <class
'ConnectionRefusedError'>: [Errno 111] Connection refused)

when start download model ssd512.

#dldt The Preprocessor block has been removed. Only nodes performing mean value subtraction and scaling (if applicable) are kept.
[ ERROR ] Found the following nodes '[]' with name 'swapped_proposals' but there should be exactly 1. Looks like ObjectDetectionAPIProposalAndROIPoolingReplacement replacement didn't work.

Hello. I wanted to use the pedestrian-detection-adas-0002 model with open vino for which i required to convert the the model files into .xml and .bin IR files using model optimizer. However, i cannot find the .caffemodel weight files along with the .prototxt file. Am i going about this the wrong way or they haven't provided the files for some reason? Thanks in advance.

i run the demo bin in ubuntu 16 virtual machine,but it only run a few secods be killed. i check the reason is memory leak,

Hi,
In the description of human-pose-estimation-0001.md it states that the mean Average Precision on Coco is 42.8%. In the OpenPose paper, the authors report an mAP of around 60%. Does this mean that the current implementation is not as accurate?
Thanks,

Hi is it possible to download the caffemodel associated to the sample "person-vehicle-bike-detection-crossroad-0078". The deploy file is available but the caffemodel is not available.

Thanks

It stated:

The blob is constructed from a 60x60 pixel BGR image with subtracted mean of (120, 110, 104) and scale factor of 0.0039.

And I have spent a lot of time, to figure out, that right parameters must come without mean and scale, or you'll get warped/distorted result.

# original, not working
blob = cv2.dnn.blobFromImage(face, 0.0039, (60, 60), mean=[120, 110, 104], swapRB=False)

# working
blob = cv2.dnn.blobFromImage(face, 1, (60, 60))
# also working, but worser
blob = cv2.dnn.blobFromImage(face, 1, (60, 60), mean=[120,110,104], swapRB=False)

I fond some models from https://download.01.org/ ,like driver-action-recognition-adas-0002-decoder/ ,but the demo about how to use it is not present . So，will it be released?

There is a brief explanation here about how the model was trained that says: "The network is able to recognize age of people in [18, 75] years old range, it is not applicable for children since their faces were not in the training set."

Then, in the code the operation done to get that number is:

ageBlob->buffer().as<float*>()[idx] * 100

I assume that output of ageBlob is a number in the range [0, 1], and if it is then multiplied by 100 it could give an age in the range [0, 100]. Taking into account the description given above, shouldn't it be something like:

18 + (75 - 18) * ageBlob->buffer().as<float*>()[idx]

Could we know more details about the training of this model?

Thanks

In the demos directory, I created a build directory for cmake compilation.
command:

cmake -DCMAKE_BUILD_TYPE=Release ..

but, an error occurred:

CMake Error: The following variables are used in this project, but they are set to NOTFOUND.
Please set them or make sure they are set and tested correctly in the CMake files:
intel_omp_lib
linked by target "cpu_extension" in directory /home/intel/code/open_model_zoo/demos/extension
-- Configuring incomplete, errors occurred!

I found out that this problem was caused by a path error in /open_model_zoo/demos/cmake/feature_defs.cmake:

find_library(intel_omp_lib iomp5
PATHS ${InferenceEngine_INCLUDE_DIRS}/../external/mkltiny_lnx/lib
PATHS ${InferenceEngine_INCLUDE_DIRS}/../temp/mkltiny_lnx_20180511/lib
)

After modification, cmake can be compiled normally.

How to deploy openvino to another win10 computer (product side) that is not installed. If I have a complete program locally, I only need to deploy the local program to the target win10 computer. Do the target computers need to install some additional libraries? Such as python, MsBuild, Visual Studio...etc?

I get the following error message when I run any demo in Debug mode, but which I don't get when I run them in Release mode (in Windows 10, Visual Studio 2015, x64, with the latest version of OpenVINO):

Unhandled exception at 0x00007FFE52C6CEA8 (ucrtbase.dll) in interactive_face_detection_demo.exe: An invalid parameter was passed to a function that considers invalid parameters fatal.

This happens in the getSuitablePlugin(TargetDevice device) function in ie_plugin_dispatcher.hpp, and the value of the input variable "device" is "eCPU". I don't know what else to do with this. Any help, please?

Original PixelLink output (net.pixel_pos_scores, net.link_pos_scores from https://github.com/ZJULearning/pixel_link/blob/master/pixel_link.py#L258) looks like floats in range 0...1:

[[ 0.24215889  0.19413042  0.14910938 ...,  0.00188291  0.00194044
   0.00193263]
 [ 0.24693285  0.28427953  0.31201595 ...,  0.00151003  0.0016161
   0.00158036]
 [ 0.29501158  0.34466279  0.46107355 ...,  0.0012383   0.00134384
   0.00133101]
 ..., 
 [ 0.00158432  0.00165696  0.0014348  ...,  0.00135033  0.00137759
   0.00137619]
 [ 0.00190641  0.00192341  0.00177216 ...,  0.00173626  0.00173059
   0.00166685]
 [ 0.00187553  0.00182314  0.00165866 ...,  0.00164717  0.00169245
   0.00167963]]

But text-detection-0001's outputs are floats in range -15.211208...15.0217495:

array([[[[  4.6511946 ,   3.3907833 ,   3.7669291 , ...,   3.72439   ,
            1.5242342 ,   1.5894152 ],
         [  4.844614  ,   3.1117034 ,   4.07622   , ...,   3.9524572 ,
            2.177125  ,   1.1225173 ],
         [  5.4335623 ,   4.2353683 ,   4.023198  , ...,   4.0421925 ,
            2.2825203 ,   0.88815284],
         ...,
         [  5.3664694 ,   2.4834807 ,   1.8314009 , ...,   1.8346828 ,
            1.0272049 ,   0.35480225],
         [  4.4519434 ,   2.1997466 ,   1.3233964 , ...,   1.7166362 ,
            1.0280185 ,   0.35244453],
         [  4.423532  ,   3.322742  ,   2.6166863 , ...,   3.3006763 ,
            2.9662962 ,   0.6041066 ]],

        [[ -0.843023  ,  -2.634922  ,  -3.119152  , ...,  -8.103498  ,
          -10.155584  ,  -9.70215   ],
         [ -0.1580252 ,  -2.6089997 ,  -2.6890798 , ...,  -7.507005  ,
           -9.210783  , -10.2020035 ],
         [  0.68314683,  -1.6999166 ,  -2.7057598 , ...,  -7.2223086 ,
           -8.905821  ,  -9.953106  ],
         ...,
         [ -0.6636865 ,  -3.6634817 ,  -4.148598  , ...,  -7.5650234 ,
           -8.270643  ,  -8.99107   ],
         [ -1.6523982 ,  -3.89168   ,  -4.290622  , ...,  -7.399207  ,
           -8.073703  ,  -8.721676  ],
         [ -1.539933  ,  -2.7685883 ,  -3.2388062 , ...,  -6.174163  ,
           -6.524869  ,  -8.545204  ]]]], dtype=float32)

I'm confused. According to original paper description, they must be in range 0...1, because they are result of Softmax function.

My code is simple:

td = cv2.dnn.readNet('./text-detection-0001.xml','./text-detection-0001.bin')
img = cv2.imread('test.jpg')
blob = cv2.dnn.blobFromImage(img, 1, (768, 1280))
td.setInput(blob)
a, b = td.forward(td.getUnconnectedOutLayersNames())

PS: Tested on OpenVINO (computer_vision_sdk_2018.5.445) with same results.

I want to use these model in Android? and only cpu,how can i do it?

import cv2

tr = cv2.dnn.readNet('./text-recognition-0012.xml', 'text-recognition-0012.bin')
img = cv2.imread('word.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
blob_r = cv2.dnn.blobFromImage(gray, 1, (120, 32))
tr.setInput(blob_r)
tr.forward()

Above code produces an error:
>>> op_inf_engine.cpp:555: error: (-215:Assertion failed) Failed to initialize Inference Engine backend: Incorrect number of input edges for layer shadow/Squeeze in function 'initPlugin'

OpenCV 4.0.1
Inference Engine 2018.R5

I see a recent 2018_R4 tag at https://github.com/opencv/dldt. Should there be a tagged commit for this repo as well? Perhaps for commit f814264?

python3 mo.py --input_model=/fine_tuned_model1/frozen_inference_graph.pb --output=detection_boxes,detection_scores,num_detections --tensorflow_use_custom_operations_config extensions/front/tf/legacy_faster_rcnn_support.json --tensorflow_object_detection_api_pipeline_config=/fine_tuned_model1/pipeline.config --input_shape=[1,256,256,3]

I am getting below error while running the above command.

WARNING: the "SecondStagePostprocessorReplacement" is a legacy replacer that will be removed in the future release. Please, consider using replacers defined in the "extensions/front/tf/ObjectDetectionAPI.py"
[ ERROR ] -------------------------------------------------
[ ERROR ] ----------------- INTERNAL ERROR ----------------
[ ERROR ] Unexpected exception happened.
[ ERROR ] Please contact Model Optimizer developers and forward the following information:
[ ERROR ] 'preprocessed_image_height'
[ ERROR ] Traceback (most recent call last):
File "/opt/intel/computer_vision_sdk_2018.3.343/deployment_tools/model_optimizer/mo/main.py", line 321, in main
return driver(argv)
File "/opt/intel/computer_vision_sdk_2018.3.343/deployment_tools/model_optimizer/mo/main.py", line 263, in driver
mean_scale_values=mean_scale)
File "/opt/intel/computer_vision_sdk_2018.3.343/deployment_tools/model_optimizer/mo/pipeline/tf.py", line 171, in tf2nx
class_registration.apply_replacements(graph, class_registration.ClassType.FRONT_REPLACER)
File "/opt/intel/computer_vision_sdk_2018.3.343/deployment_tools/model_optimizer/mo/utils/class_registration.py", line 102, in apply_replacements
replacer.find_and_replace_pattern(graph)
File "/opt/intel/computer_vision_sdk_2018.3.343/deployment_tools/model_optimizer/mo/front/tf/replacement.py", line 91, in find_and_replace_pattern
self.replace_sub_graph(graph, match)
File "/opt/intel/computer_vision_sdk_2018.3.343/deployment_tools/model_optimizer/mo/front/common/replacement.py", line 115, in replace_sub_graph
new_sub_graph = self.generate_sub_graph(graph, match)
File "/opt/intel/computer_vision_sdk_2018.3.343/deployment_tools/model_optimizer/extensions/front/tf/FasterRCNNs.py", line 243, in generate_sub_graph
config_attrs['input_height'] = graph.graph['preprocessed_image_height']
KeyError: 'preprocessed_image_height'

[ ERROR ] ---------------- END OF BUG REPORT --------------
[ ERROR ] -------------------------------------------------

when I use person-detection-action-recognition-teacher-0002.xml ,and the newest code of
"smart_classroom_demo" ,I get the following:
[ ERROR ] Error reading network: cannot parse future versions: 5

Do I need to upgrade something?

Hi open_model_zoo,
I've got the OpenVINO R5 (latest version), configured it and tried to build and run the demo (models were downloaded).
When I pass input as a camera (-i cam) it works good.
When I pass an image it fails with error

>interactive_face_detection_demo.exe -i <path to zoo>\open_model_zoo\intel_models\age-gender-recognition-retail-0013\description\age-gender-recognition-retail-0001.jpg -m <path to model>\face-detection-adas-0001.xml -m_ag <path to model>\age-gender-recognition-retail-0013.xml
InferenceEngine:
        API version ............ 1.4
        Build .................. 19154
[ INFO ] Parsing input parameters
[ INFO ] Reading input
[ ERROR ] Cannot open input file or camera: <path to zoo>\open_model_zoo\intel_models\age-gender-recognition-retail-0013\description\age-gender-recognition-retail-0001.jpg

Could you please help me what I'm doing wrong?

I tested the inference sample object_detection_sample_ssd with this model person_detection_retail_0002, which I downloaded by download.py.

but the result is not good, the pictures I used is from VOCTest dataset, it is unable to detect the persons accurately in pic.

the command is like
object_detection_sample_ssd -m person-detection-retail-0002.xml -l libcpu_extension.so -i 004690.jpg

what's wrong in my steps?

If I am trying to use it with 2018_R5:

net = cv2.dnn.readNet('face-detection-retail-0004.xml', 'face-detection-retail-0004.bin')
face = (np.random.rand(480, 320, 3) * 255).astype(np.uint8)
blob = cv2.dnn.blobFromImage(img, 1, (300, 300))
net.setInput(blob)
net.forward()

>>opencv/modules/dnn/src/op_inf_engine.cpp:555: error: (-215:Assertion failed)
Failed to initialize Inference Engine backend: 
Incorrect number of input edges for layer mbox_conf_reshape in function 'initPlugin'

With 2019_R1 all is good. I think that few month ago it was working on 2018_R5.

there are two inputs, name: "data" and name: "seq_ind" . How to set these two inputs in openCV ?

Thanks

when trying to build the demo, use cmake-GUI
cmake would automatically find the InferenceEngine_DIR and OpenCV_DIR. The value of the InferenceEngine_DIR can be changed by user , However, no matter how user change the OpenCV_DIR, The cmake would always try to find the OpenCV_DIR itself and replace the value when press the Configure button. users cannot modify OpenCV_DIR themselves.

flake8 testing of https://github.com/opencv/open_model_zoo on Python 3.7.1

$ flake8 . --count --select=E9,F63,F72,F82 --show-source --statistics

./demos/smart_classroom_demo/action_event_metrics.py:94:33: F821 undefined name 'xrange'
            for bbox_attr_id in xrange(len(bbox)):
                                ^
./demos/smart_classroom_demo/action_event_metrics.py:172:18: F821 undefined name 'xrange'
        for i in xrange(len(sorted_predicted_bboxes)):
                 ^
./demos/smart_classroom_demo/action_event_metrics.py:178:26: F821 undefined name 'xrange'
            for gt_id in xrange(len(gt_bboxes)):
                         ^
./demos/smart_classroom_demo/action_event_metrics.py:277:22: F821 undefined name 'xrange'
            for i in xrange(1, len(input_events)):
                     ^
./demos/smart_classroom_demo/action_event_metrics.py:327:29: F821 undefined name 'xrange'
            for event_id in xrange(1, len(input_events)):
                            ^
./demos/smart_classroom_demo/action_event_metrics.py:385:20: F821 undefined name 'xrange'
    for pred_id in xrange(len(pred_events)):
                   ^
./demos/smart_classroom_demo/action_event_metrics.py:388:22: F821 undefined name 'xrange'
        for gt_id in xrange(len(gt_events)):
                     ^
7     F821 undefined name 'xrange'

Hello, I'm trying to run the interactive_face_detection_demo in Ubuntu 18.04
After installing OpenVINO, I cloned this repo and then downloaded the models indicated in the Demo README
Once I compiled the program when I run it with this parameters:

./interactive_face_detection_demo -m ../../../model_downloader/Transportation/object_detection/face/pruned_mobilenet_reduced_ssd_shared_weights/dldt/face-detection-adas-0001.xml

I get the next output:

InferenceEngine: 
	API version ............ 1.4
	Build .................. 19154
[ INFO ] Parsing input parameters
[ INFO ] Reading input
[ INFO ] Loading plugin CPU

	API version ............ 1.5
	Build .................. lnx_20181004
	Description ....... MKLDNNPlugin
[ INFO ] Loading network files for Face Detection
[ INFO ] Batch size is set to 1
[ INFO ] Checking Face Detection network inputs
[ INFO ] Checking Face Detection network outputs
[ INFO ] Loading Face Detection model to the CPU plugin
[ ERROR ] Incorrect number of input edges for layer mbox_conf_reshape

I tried different face recognition models but in all of them I got the same output.

Does any of you got an idea what is going on?

Hi,
I tried using the person-vehicle-bike-detection-crossroad-0078 model, it correctly detects people and cars but it looks like it can't detect bikes.
Examples:

Command I used:

./object_detection_sample_ssd -m person-vehicle-bike-detection-crossroad-0078.xml - i input_image.jpg

Openvino version: 2019.1.133

Am I doing something wrong?

Hello ,
I have an OpenVino python environment running on Raspberry Pi and Neural Compute Stick 2 and inference speed is as expected.

However running sample models from Open_Model_Zoo the inference time for one pass is equivalent to running with the Rapsberry Pi CPU.

Demo tested:
https://github.com/opencv/open_model_zoo/blob/2018/demos/python_demos/text_detection_demo.py

Note:
I needed to add td.setPreferableTarget(cv2.dnn.DNN_TARGET_MYRIAD)
after line 234 to run in my OpenVino environment.

Should these demos be supported on Raspberry Pi and Neural Compute Stick 2 and if so are there any special configuration steps ?

Many thanks in advance.

Hello, dear.
I Only need a landmarks detector.

But, in "smart_classroom_demo"
-m_act "" Required. Path to the Person/Action Detection Retail model (.xml) file.
-m_fd "" Required. Path to the Face Detection Retail model (.xml) file.
-m_lm "" Required. Path to the Facial Landmarks Regression Retail model (.xml) file.
-m_reid "" Required. Path to the Face Reidentification Retail model (.xml) file.
It is able to be useful by 4 model.
How to do, I only use the "landmarks-regression-retail-0001.bin" ?
I need help.
Thanks.

Is it possible to use batch size >1 for any model in model zoo?

If I'll change <dim> in xml file, for example?

Could it have non-hardcoded value?

I want to know if there is a tutorial or a using example to show how to use Inference Engine pre-trained models in OpenCV to detect the objects like face, human, car, etc...

I have already downloaded and installed the Intel® OpenVINO™ toolkit I followed this wiki.

Basically I have two questions
Question 1: I tried to build OpenCV from source with Inference Engine, but the CMake was unable to locate the Inference Engine_DIR, It will be better to also have a tutorial to show how to build, it the wiki above it is not very clear. So I was not able to load the Inference Engine pre-trained model in the OpenCV which was built by me, it has thrwon the exception which say the Inference Engine is not enable.
OK, so I used the OpenCV which came with the OpenVINO toolkit.

Question 2: When I loaded the face-detection-adas-0001 xml and bin using cv::dnn::Net::readxxxxx(xml, bin) it was woking and did not throw any exception, but in the next step I don't know how to pass the frame (cv::Mat) to the Network and get the result. I am looking for an axample to show how to the pre-trained models in OpenCV.

Thanks!!!!

nvidia Jetson nano has gpu on it. Could we run these model on Jeston nano with target=GPU ?

when start to download model ssd512 it happened

uests.exceptions.ConnectionError: HTTPSConnectionPool(host='docs.google.com', port=443): Max retries exceeded with url: /uc?export=download&id=0BzKzrI_SkD1_MjFjNTlnempHNWs (Caused by <class 'ConnectionRefusedError'>: [Errno 111] Connection refused)

what I should do ?

security_barrier_camera_demo in python.
and trainning code.

I like pre-trained models provided by Intel OpenVino, but I want to run them using Tensorflow and GPU. For example, I am interested in people detection model written in Caffee. Is it legal to translate it to TesorFlow and use it in a commercial product? And does it makes sense? Maybe it is just better to train YOLO model for one class person?
Thank you for any help provided.