私的AI研究会 > OMZonRaspi
OpenVINO™ Toolkit「2021.3」を Raspberry Pi4 にインストールする手順を再確認する。サイトの説明がバージョンの古いものが多くなってきているのでオフィシャルサイト に従って進める。
2021年04月04日現在、OpenVINO™ ツールキットの最新バージョンは 2021.3
● VNCビューアなどで、Raspberry Pi 上のブラウザでオフィシャルサイトのダウンロードページから下記のファイルをダウンロードする。
● ファイル名：l_openvino_toolkit_runtime_raspbian_p_2021.3.394.tgz
※ファイルは「~/Download」ディレクトリに配置される。
pi@raspberrypi:~ $ cd ~/Downloads pi@raspberrypi:~/Downloads $ ls l_openvino_toolkit_runtime_raspbian_p_2021.3.394.tgz
pi@raspberrypi:~/Downloads $ sudo mkdir -p /opt/intel/openvino pi@raspberrypi:~/Downloads $ ls /opt Wolfram intel minecraft-pi pigpio vc pi@raspberrypi:~/Downloads $ ls /opt/intel openvino
pi@raspberrypi:~/Downloads $ sudo tar -xf l_openvino_toolkit_runtime_raspbian_p_2021.3.394.tgz --strip 1 -C /opt/intel/openvino pi@raspberrypi:~/Downloads $ ls /opt/intel/openvino bin deployment_tools documentation inference_engine install_dependencies licensing opencv python
pi@raspberrypi:~/Downloads $ sudo apt update
pi@raspberrypi:~/Downloads $ sudo apt install cmake
パッケージリストを読み込んでいます... 完了
依存関係ツリーを作成しています
状態情報を読み取っています... 完了
以下の追加パッケージがインストールされます:
cmake-data libjsoncpp1 librhash0
:
この操作後に追加で 22.3 MB のディスク容量が消費されます。
続行しますか? [Y/n] y
取得:1 http://ftp.jaist.ac.jp/raspbian buster/main armhf libjsoncpp1 armhf 1.7.4-3 [66.2 kB]
取得:2 http://ftp.jaist.ac.jp/raspbian buster/main armhf librhash0 armhf 1.3.8-1 [132 kB]
:pi@raspberrypi-mas:~/Downloads $ source /opt/intel/openvino_2021/bin/setupvars.sh -bash: /opt/intel/openvino_2021/bin/setupvars.sh: そのようなファイルやディレクトリはありません pi@raspberrypi-mas:~/Downloads $ ls /opt/intel openvino pi@raspberrypi-mas:~/Downloads $ sudo mv /opt/intel/openvino /opt/intel/openvino_2021 pi@raspberrypi-mas:~/Downloads $ ls /opt/intel openvino_2021 pi@raspberrypi-mas:~/Downloads $ source /opt/intel/openvino_2021/bin/setupvars.sh [setupvars.sh] OpenVINO environment initialized実行して[setupvars.sh] OpenVINO environment initializedと表示されればOK。
pi@raspberrypi:~/Downloads $ echo "source /opt/intel/openvino_2021/bin/setupvars.sh" >> ~/.bashrcターミナルソフトを終了して、再度開いて[setupvars.sh] OpenVINO environment initializedと表示されればOK。
pi@raspberrypi:~ $ sh /opt/intel/openvino_2021/install_dependencies/install_NCS_udev_rules.sh Updating udev rules... Udev rules have been successfully installed.udev rules installedと表示されればOK。
pi@raspberrypi:~ $ mkdir build && cd build
pi@raspberrypi:~/build $ cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_CXX_FLAGS="-march=armv7-a" /opt/intel/openvino_2021/deployment_tools/inference_engine/samples/cpp -- The C compiler identification is GNU 8.3.0 -- The CXX compiler identification is GNU 8.3.0 -- Check for working C compiler: /usr/bin/cc -- Check for working C compiler: /usr/bin/cc -- 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: /usr/bin/c++ -- Check for working CXX compiler: /usr/bin/c++ -- works -- Detecting CXX compiler ABI info -- Detecting CXX compiler ABI info - done -- Detecting CXX compile features -- Detecting CXX compile features - done -- Looking for C++ include unistd.h -- Looking for C++ include unistd.h - found -- Looking for C++ include stdint.h -- Looking for C++ include stdint.h - found -- Looking for C++ include sys/types.h -- Looking for C++ include sys/types.h - found -- Looking for C++ include fnmatch.h -- Looking for C++ include fnmatch.h - found -- Looking for strtoll -- Looking for strtoll - found -- Found InferenceEngine: /opt/intel/openvino_2021/deployment_tools/inference_engine/lib/armv7l/libinference_engine.so (Required is at least version "2.1") -- Configuring done -- Generating done -- Build files have been written to: /home/pi/build
pi@raspberrypi:~/build $ make -j2 object_detection_sample_ssd Scanning dependencies of target format_reader Scanning dependencies of target gflags_nothreads_static [ 9%] Building CXX object thirdparty/gflags/CMakeFiles/gflags_nothreads_static.dir/src/gflags.cc.o [ 18%] Building CXX object common/format_reader/CMakeFiles/format_reader.dir/MnistUbyte.cpp.o [ 27%] Building CXX object common/format_reader/CMakeFiles/format_reader.dir/bmp.cpp.o [ 36%] Building CXX object common/format_reader/CMakeFiles/format_reader.dir/format_reader.cpp.o [ 45%] Building CXX object thirdparty/gflags/CMakeFiles/gflags_nothreads_static.dir/src/gflags_reporting.cc.o [ 54%] Building CXX object common/format_reader/CMakeFiles/format_reader.dir/opencv_wraper.cpp.o [ 63%] Building CXX object thirdparty/gflags/CMakeFiles/gflags_nothreads_static.dir/src/gflags_completions.cc.o [ 72%] Linking CXX static library ../../armv7l/Release/lib/libgflags_nothreads.a [ 72%] Built target gflags_nothreads_static [ 81%] Linking CXX shared library ../../armv7l/Release/lib/libformat_reader.so [ 81%] Built target format_reader Scanning dependencies of target object_detection_sample_ssd [ 90%] Building CXX object object_detection_sample_ssd/CMakeFiles/object_detection_sample_ssd.dir/main.cpp.o [100%] Linking CXX executable ../armv7l/Release/object_detection_sample_ssd [100%] Built target object_detection_sample_ssd
pi@raspberrypi:~/build $ git clone --depth 1 https://github.com/openvinotoolkit/open_model_zoo Cloning into 'open_model_zoo'... remote: Enumerating objects: 2754, done. remote: Counting objects: 100% (2754/2754), done. remote: Compressing objects: 100% (2292/2292), done. remote: Total 2754 (delta 779), reused 1173 (delta 357), pack-reused 0 Receiving objects: 100% (2754/2754), 127.57 MiB | 2.35 MiB/s, done. Resolving deltas: 100% (779/779), done. Checking out files: 100% (2248/2248), done.
pi@raspberrypi:~/build $ cd open_model_zoo/tools/downloader
pi@raspberrypi:~/build/open_model_zoo/tools/downloader $ python3 -m pip install -r requirements.in
Looking in indexes: https://pypi.org/simple, https://www.piwheels.org/simple
Collecting pyyaml (from -r requirements.in (line 1))
Downloading https://files.pythonhosted.org/packages/a0/a4/d63f2d7597e1a4b55aa3b4d6c5b029991d3b824b5bd331af8d4ab1ed687d/PyYAML-5.4.1.tar.gz (175kB)
100% |████████████████████████████████| 184kB 1.1MB/s
Installing build dependencies ... done
Requirement already satisfied: requests in /usr/lib/python3/dist-packages (from -r requirements.in (line 2)) (2.21.0)
Building wheels for collected packages: pyyaml
Running setup.py bdist_wheel for pyyaml ... done
Stored in directory: /home/pi/.cache/pip/wheels/2a/d4/92/cf299bdf4162957ca8126b46e913e29f76a4f17ca762c45028
Successfully built pyyaml
Installing collected packages: pyyaml
Successfully installed pyyaml-5.4.1
pi@raspberrypi:~/build/open_model_zoo/tools/downloader $ python3 downloader.py --name face-detection-adas-0001 ################|| Downloading face-detection-adas-0001 ||################ ========== Downloading /home/pi/build/open_model_zoo/tools/downloader/intel/face-detection-adas-0001/FP32/face-detection-adas-0001.xml ... 100%, 226 KB, 275 KB/s, 0 seconds passed ========== Downloading /home/pi/build/open_model_zoo/tools/downloader/intel/face-detection-adas-0001/FP32/face-detection-adas-0001.bin ... 100%, 4113 KB, 1757 KB/s, 2 seconds passed ========== Downloading /home/pi/build/open_model_zoo/tools/downloader/intel/face-detection-adas-0001/FP16/face-detection-adas-0001.xml ... 100%, 226 KB, 270 KB/s, 0 seconds passed ========== Downloading /home/pi/build/open_model_zoo/tools/downloader/intel/face-detection-adas-0001/FP16/face-detection-adas-0001.bin ... 100%, 2056 KB, 1202 KB/s, 1 seconds passed ========== Downloading /home/pi/build/open_model_zoo/tools/downloader/intel/face-detection-adas-0001/FP16-INT8/face-detection-adas-0001.xml ... 100%, 502 KB, 483 KB/s, 1 seconds passed ========== Downloading /home/pi/build/open_model_zoo/tools/downloader/intel/face-detection-adas-0001/FP16-INT8/face-detection-adas-0001.bin ... 100%, 1074 KB, 814 KB/s, 1 seconds passed
$ cd~/build pi@raspberrypi:~/build $ cp open_model_zoo/tools/downloader/intel/face-detection-adas-0001/FP16-INT8/face-detection-adas-0001.bin ./ pi@raspberrypi:~/build $ cp open_model_zoo/tools/downloader/intel/face-detection-adas-0001/FP16-INT8/face-detection-adas-0001.xml ./ pi@raspberrypi:~/build $ ls CMakeCache.txt benchmark_app face-detection-adas-0001.bin hello_query_device open_model_zoo CMakeFiles classification_sample_async face-detection-adas-0001.xml hello_reshape_ssd speech_sample Makefile cmake_install.cmake hello_classification ngraph_function_creation_sample style_transfer_sample armv7l common hello_nv12_input_classification object_detection_sample_ssd thirdparty
pi@raspberrypi-mas:~/build $ ./armv7l/Release/object_detection_sample_ssd -m face-detection-adas-0001.xml -d MYRIAD -i ~/Images/input.jpg
[ INFO ] InferenceEngine:
API version ............ 2.1
Build .................. 2021.3.0-2787-60059f2c755-releases/2021/3
Description ....... API
Parsing input parameters
[ INFO ] Files were added: 1
[ INFO ] /home/pi/Images/input.jpg
[ INFO ] Loading Inference Engine
[ INFO ] Device info:
MYRIAD
myriadPlugin version ......... 2.1
Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
[ INFO ] Loading network files:
face-detection-adas-0001.xml
[ INFO ] Preparing input blobs
[ INFO ] Batch size is 1
[ INFO ] Preparing output blobs
[ INFO ] Loading model to the device
[ ERROR ] Failed to compile layer "conv1/fq_input_0": unsupported layer type "FakeQuantize"
エラーとなるので学習済みモデルを 2021.2 版のものを使う。pi@raspberrypi-mas:~/build $ ./armv7l/Release/object_detection_sample_ssd -m face-detection-adas-0001.xml -d MYRIAD -i ~/Images/input.jpg
[ INFO ] InferenceEngine:
API version ............ 2.1
Build .................. 2021.3.0-2787-60059f2c755-releases/2021/3
Description ....... API
Parsing input parameters
[ INFO ] Files were added: 1
[ INFO ] /home/pi/Images/input.jpg
[ INFO ] Loading Inference Engine
[ INFO ] Device info:
MYRIAD
myriadPlugin version ......... 2.1
Build ........... 2021.3.0-2787-60059f2c755-releases/2021/3
[ INFO ] Loading network files:
face-detection-adas-0001.xml
[ INFO ] Preparing input blobs
[ INFO ] Batch size is 1
[ INFO ] Preparing output blobs
[ INFO ] Loading model to the device
[ INFO ] Create infer request
[ WARNING ] Image is resized from (1440, 1048) to (672, 384)
[ INFO ] Batch size is 1
[ INFO ] Start inference
[ INFO ] Processing output blobs
[0,1] element, prob = 1 (615,122)-(827,377) batch id : 0 WILL BE PRINTED!
[1,1] element, prob = 1 (875,378)-(1068,628) batch id : 0 WILL BE PRINTED!
[2,1] element, prob = 0.0756836 (1227,2)-(1338,139) batch id : 0
[3,1] element, prob = 0.0756836 (1312,1)-(1397,100) batch id : 0
[4,1] element, prob = 0.0683594 (1337,6)-(1435,113) batch id : 0
[5,1] element, prob = 0.0629883 (1231,21)-(1290,96) batch id : 0
:
:
[86,1] element, prob = 0.0366211 (1120,69)-(1222,230) batch id : 0
[87,1] element, prob = 0.0356445 (230,19)-(281,92) batch id : 0
[88,1] element, prob = 0.0356445 (1161,77)-(1203,134) batch id : 0
[89,1] element, prob = 0.0356445 (1198,77)-(1238,134) batch id : 0
[90,1] element, prob = 0.0356445 (1117,116)-(1172,196) batch id : 0
[91,1] element, prob = 0.0356445 (1158,123)-(1199,186) batch id : 0
[92,1] element, prob = 0.0356445 (273,165)-(317,239) batch id : 0
[93,1] element, prob = 0.0356445 (294,203)-(344,288) batch id : 0
[ INFO ] Image out_0.bmp created!
[ INFO ] Execution successful
[ INFO ] This sample is an API example, for any performance measurements please use the dedicated benchmark_app tool$ cd ~/build/armv7l/Release/
$ ./benchmark_app -h
[Step 1/11] Parsing and validating input arguments
[ INFO ] Parsing input parameters
benchmark_app [OPTION]
Options:
-h, --help Print a usage message
-m "<path>" Required. Path to an .xml/.onnx/.prototxt file with a trained model or to a .blob files with a trained compiled model.
-i "<path>" Optional. Path to a folder with images and/or binaries or to specific image or binary file.
-d "<device>" Optional. Specify a target device to infer on (the list of available devices is shown below). Default value is CPU. Use "-d HETERO:<comma-separated_devices_list>" format to specify HETERO plugin. Use "-d MULTI:<comma-separated_devices_list>" format to specify MULTI plugin. The application looks for a suitable plugin for the specified device.
-l "<absolute_path>" Required for CPU custom layers. Absolute path to a shared library with the kernels implementations.
Or
-c "<absolute_path>" Required for GPU custom kernels. Absolute path to an .xml file with the kernels description.
-api "<sync/async>" Optional. Enable Sync/Async API. Default value is "async".
-niter "<integer>" Optional. Number of iterations. If not specified, the number of iterations is calculated depending on a device.
-nireq "<integer>" Optional. Number of infer requests. Default value is determined automatically for device.
-b "<integer>" Optional. Batch size value. If not specified, the batch size value is determined from Intermediate Representation.
-stream_output Optional. Print progress as a plain text. When specified, an interactive progress bar is replaced with a multiline output.
-t Optional. Time in seconds to execute topology.
-progress Optional. Show progress bar (can affect performance measurement). Default values is "false".
-shape Optional. Set shape for input. For example, "input1[1,3,224,224],input2[1,4]" or "[1,3,224,224]" in case of one input size.
-layout Optional. Prompts how network layouts should be treated by application. For example, "input1[NCHW],input2[NC]" or "[NCHW]" in case of one input size.
device-specific performance options:
-nstreams "<integer>" Optional. Number of streams to use for inference on the CPU, GPU or MYRIAD devices (for HETERO and MULTI device cases use format <dev1>:<nstreams1>,<dev2>:<nstreams2> or just <nstreams>). Default value is determined automatically for a device.Please note that although the automatic selection usually provides a reasonable performance, it still may be non - optimal for some cases, especially for very small networks. See sample's README for more details. Also, using nstreams>1 is inherently throughput-oriented option, while for the best-latency estimations the number of streams should be set to 1.
-nthreads "<integer>" Optional. Number of threads to use for inference on the CPU (including HETERO and MULTI cases).
-enforcebf16 Optional. Enforcing of floating point operations execution in bfloat16 precision where it is acceptable.
-pin "YES"/"NO"/"NUMA" Optional. Enable threads->cores ("YES", default), threads->(NUMA)nodes ("NUMA") or completely disable ("NO") CPU threads pinning for CPU-involved inference.
Statistics dumping options:
-report_type "<type>" Optional. Enable collecting statistics report. "no_counters" report contains configuration options specified, resulting FPS and latency. "average_counters" report extends "no_counters" report and additionally includes average PM counters values for each layer from the network. "detailed_counters" report extends "average_counters" report and additionally includes per-layer PM counters and latency for each executed infer request.
-report_folder Optional. Path to a folder where statistics report is stored.
-exec_graph_path Optional. Path to a file where to store executable graph information serialized.
-pc Optional. Report performance counters.
-dump_config Optional. Path to XML/YAML/JSON file to dump IE parameters, which were set by application.
-load_config Optional. Path to XML/YAML/JSON file to load custom IE parameters. Please note, command line parameters have higher priority then parameters from configuration file.
-qb Optional. Weight bits for quantization: 8 or 16 (default)
Available target devices:
$ ~/build/armv7l/Release/
$ ./hello_query_device
Available devices:
Device: MYRIAD
Metrics:
DEVICE_THERMAL : UNSUPPORTED TYPE
RANGE_FOR_ASYNC_INFER_REQUESTS : { 3, 6, 1 }
SUPPORTED_CONFIG_KEYS : [ PERF_COUNT EXCLUSIVE_ASYNC_REQUESTS LOG_LEVEL VPU_MYRIAD_PLATFORM CONFIG_FILE VPU_MYRIAD_FORCE_RESET DEVICE_ID VPU_CUSTOM_LAYERS VPU_PRINT_RECEIVE_TENSOR_TIME VPU_HW_STAGES_OPTIMIZATION MYRIAD_ENABLE_FORCE_RESET MYRIAD_CUSTOM_LAYERS MYRIAD_ENABLE_RECEIVING_TENSOR_TIME MYRIAD_THROUGHPUT_STREAMS MYRIAD_ENABLE_HW_ACCELERATION ]
SUPPORTED_METRICS : [ DEVICE_THERMAL RANGE_FOR_ASYNC_INFER_REQUESTS SUPPORTED_CONFIG_KEYS SUPPORTED_METRICS OPTIMIZATION_CAPABILITIES FULL_DEVICE_NAME AVAILABLE_DEVICES ]
OPTIMIZATION_CAPABILITIES : [ FP16 ]
FULL_DEVICE_NAME : Intel Movidius Myriad X VPU
Default values for device configuration keys:
PERF_COUNT : NO
EXCLUSIVE_ASYNC_REQUESTS : NO
LOG_LEVEL : LOG_NONE
VPU_MYRIAD_PLATFORM : ""
CONFIG_FILE : ""
VPU_MYRIAD_FORCE_RESET : NO
DEVICE_ID : ""
VPU_CUSTOM_LAYERS : ""
VPU_PRINT_RECEIVE_TENSOR_TIME : NO
VPU_HW_STAGES_OPTIMIZATION : YES
MYRIAD_ENABLE_FORCE_RESET : NO
MYRIAD_CUSTOM_LAYERS : ""
MYRIAD_ENABLE_RECEIVING_TENSOR_TIME : NO
MYRIAD_THROUGHPUT_STREAMS : -1
MYRIAD_ENABLE_HW_ACCELERATION : YES※ この環境では結果の動画保存は「2021.2」版と同様に保存ファイルが作成できない。。
INTEL_OPENVINO_DIR=/opt/intel/openvino_2021
$ python3 Python 3.7.3 (default, Jan 22 2021, 20:04:44) [GCC 8.3.0] on linux Type "help", "copyright", "credits" or "license" for more information. >>> import cv2 >>> print(cv2.getBuildInformation())
General configuration for OpenCV 4.5.2-openvino =====================================
Version control: 898c639f6ab195b81a1d3e9b2470a3f03123dd03
Platform:
Timestamp: 2021-03-19T02:53:32Z
Host: Linux 4.15.0-29-generic x86_64
Target: Linux 1 armv7l
CMake: 3.7.2
CMake generator: Ninja
CMake build tool: /usr/bin/ninja
Configuration: Release
CPU/HW features:
Baseline: NEON
required: NEON
disabled: VFPV3
C/C++:
Built as dynamic libs?: YES
C++ standard: 11
C++ Compiler: /usr/bin/arm-linux-gnueabihf-g++ (ver 6.3.0)
C++ flags (Release): -mthumb -fdata-sections -Wa,--noexecstack -fsigned-char -Wno-psabi -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 -Wno-psabi -Wsuggest-override -Wno-delete-non-virtual-dtor -Wno-comment -fdiagnostics-show-option -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -mfpu=neon -fvisibility=hidden -fvisibility-inlines-hidden -fstack-protector-strong -fPIC -O2 -DNDEBUG -DNDEBUG -D_FORTIFY_SOURCE=2
C++ flags (Debug): -mthumb -fdata-sections -Wa,--noexecstack -fsigned-char -Wno-psabi -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 -Wno-psabi -Wsuggest-override -Wno-delete-non-virtual-dtor -Wno-comment -fdiagnostics-show-option -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -mfpu=neon -fvisibility=hidden -fvisibility-inlines-hidden -fstack-protector-strong -fPIC -g -O0 -DDEBUG -D_DEBUG
C Compiler: /usr/bin/arm-linux-gnueabihf-gcc
C flags (Release): -mthumb -fdata-sections -Wa,--noexecstack -fsigned-char -Wno-psabi -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-psabi -Wno-comment -fdiagnostics-show-option -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -mfpu=neon -fvisibility=hidden -fstack-protector-strong -fPIC -O2 -DNDEBUG -DNDEBUG -D_FORTIFY_SOURCE=2
C flags (Debug): -mthumb -fdata-sections -Wa,--noexecstack -fsigned-char -Wno-psabi -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-psabi -Wno-comment -fdiagnostics-show-option -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -mfpu=neon -fvisibility=hidden -fstack-protector-strong -fPIC -g -O0 -DDEBUG -D_DEBUG
Linker flags (Release): -Wl,--fix-cortex-a8 -Wl,--no-undefined -Wl,--gc-sections -Wl,-z,noexecstack -Wl,-z,relro -Wl,-z,now -Wl,--gc-sections -Wl,--as-needed -z noexecstack -z relro -z now
Linker flags (Debug): -Wl,--fix-cortex-a8 -Wl,--no-undefined -Wl,--gc-sections -Wl,-z,noexecstack -Wl,-z,relro -Wl,-z,now -Wl,--gc-sections -Wl,--as-needed -z noexecstack -z relro -z now
ccache: YES
Precompiled headers: NO
Extra dependencies: dl m pthread rt
3rdparty dependencies:
OpenCV modules:
To be built: calib3d core dnn features2d flann gapi highgui imgcodecs imgproc ml objdetect photo python3 stitching ts video videoio
Disabled: world
Disabled by dependency: -
Unavailable: java python2
Applications: tests perf_tests apps
Documentation: NO
Non-free algorithms: NO
GUI:
GTK+: YES (ver 3.22.11)
GThread : YES (ver 2.50.3)
GtkGlExt: NO
Media I/O:
ZLib: build (ver 1.2.11)
JPEG: build-libjpeg-turbo (ver 2.0.6-62)
PNG: build (ver 1.6.37)
HDR: YES
SUNRASTER: YES
PXM: YES
PFM: YES
Video I/O:
FFMPEG: YES
avcodec: YES (57.64.101)
avformat: YES (57.56.101)
avutil: YES (55.34.101)
swscale: YES (4.2.100)
avresample: NO
GStreamer: YES (1.10.4)
v4l/v4l2: YES (linux/videodev2.h)
Parallel framework: pthreads
Trace: YES (with Intel ITT)
Other third-party libraries:
Inference Engine: YES (2021030000 / 2.1.0)
* libs: /home/jenkins/workspace/OpenCV/OpenVINO/2021.3/build/debian9arm/deployment_tools/inference_engine/lib/armv7l/libinference_engine.so
* includes: /home/jenkins/workspace/OpenCV/OpenVINO/2021.3/build/debian9arm/deployment_tools/inference_engine/include
nGraph: YES (0.0.0+a5d9f96)
* libs: /home/jenkins/workspace/OpenCV/OpenVINO/2021.3/build/debian9arm/deployment_tools/ngraph/lib/libngraph.so
* includes: /home/jenkins/workspace/OpenCV/OpenVINO/2021.3/build/debian9arm/deployment_tools/ngraph/include
Custom HAL: YES (carotene (ver 0.0.1))
Protobuf: build (3.5.1)
Python 3:
Interpreter: /usr/bin/python3 (ver 3.5.3)
Libraries:
numpy: /usr/lib/python3.5/dist-packages/numpy/core/include (ver undefined - cannot be probed because of the cross-compilation)
install path: /home/jenkins/workspace/OpenCV/OpenVINO/2021.3/build/debian9arm/build_release/install/python/python3
Python (for build): /usr/bin/python2.7
Install to: /home/jenkins/workspace/OpenCV/OpenVINO/2021.3/build/debian9arm/build_release/install
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