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151 lines
6.0 KiB
151 lines
6.0 KiB
# OpenVINO Samples for Intel® RealSense™ cameras
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Examples in this folder are designed to complement existing
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[SDK examples](../../examples) and demonstrate how Intel RealSense cameras can
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be used together with the OpenVINO™ toolkit in the domain of computer-vision.
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> RealSense examples have been designed and tested with the following OpenVINO versions
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> 2019.3.379
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> 2020.3.194
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> 2020.4.287
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> 2021.1.110
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> 2021.3.394
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>
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> Working with other versions may require code changes.
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## List of Samples:
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1. [Face](./face) - Facial recognition
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2. [DNN](./dnn) - Object detection with MobileNet-SSD
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## Getting Started:
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Before attempting any installation of OpenVINO, it is highly recommended that
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you check the latest [OpenVINO Getting Started guide](https://docs.openvinotoolkit.org/latest/index.html). This guide is in no way comprehensive.
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* [Windows Installation](#windows)
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* [Linux Installation](#linux)
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These samples also require OpenCV, though this is not an OpenVINO requirement.
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The OpenCV installation (or where it was built, e.g. `C:/work/opencv/build`)
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should be pointed to using a CMake `OpenCV_DIR` entry. Please refer to
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[OpenCV samples](../opencv) for additional information.
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> NOTE: You can use the OpenCV that is packaged with OpenVINO if you don't want
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> to bother with installing it yourself. Add `-DOpenCV_DIR=<openvino-dir>/opencv/cmake`
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> to your CMake command-line.
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### Windows
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See the Windows-specific OpenVINO guide [here](https://docs.openvinotoolkit.org/latest/_docs_install_guides_installing_openvino_windows.html).
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After downloading and installing OpenVINO in `C:\work\intel\openvino`:
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1. Open a shell window
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```bash
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> cd C:\work\intel\openvino
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```
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2. Make sure you have Python and its scripts, e.g. `pip`, installed and on your
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path, otherwise some failures may be encountered:
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```bash
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> set "PATH=%PATH%;C:/Program Files (x86)/Microsoft Visual Studio/Shared/Python36_64;C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python36_64\Scripts"
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> bin\setupvars.bat
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```
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3. Install prerequisites
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```bash
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> cd deployment_tools\model_optimizer\install_prerequisites
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> install_prerequisites.bat
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...
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```
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> NOTE: We ran into issues with the `networkx` library because of API changes.
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> When manually revering back to version `1.11` everything worked.
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> NOTE: If you have to redo this step or the following, you may want to clean
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> any previously-installed packages. By default, OpenVINO installs these under
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> `C:\Users\<user>\Documents\Intel\OpenVINO`.
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4. Run the demo scripts and perform additional configuration steps:
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```bash
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> cd ../../demo
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> demo_squeezenet_download_convert_run.bat
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...
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> demo_security_barrier_camera.bat
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...
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```
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5. Download models
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```bash
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> python tools/model_downloader/downloader.py --all --output_dir C:\Users\<user>\Documents\Intel\OpenVINO\models
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```
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This will take a while.
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6. Convert additional public models
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Some models are put inside a `public` directory in their source (TensorFlow,
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etc.) format and must be converted to the OpenVINO IR format. This can be done
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with:
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```bash
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> cd C:\Users\${USER}\Documents\Intel\OpenVINO\models
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> python C:\work\intel\openvino\deployment_tools\tools\model_downloader\converter.py --name faster_rcnn_resnet101_coco [--mo C:\work\intel\openvino\deployment_tools\model_optimizer\mo.py]
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```
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Please refer to the example `CMakeLists.txt` files provided in this directory
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and the individual samples to see how to properly integrate with OpenVINO.
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### Runtime Dependencies
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Many of the examples require DLL files or collaterals that need to be found.
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Rather than specify a hard-coded path, they usually expect these to be available
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in the same directory as the .exe.
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If the .exe is at `c:/work/lrs/build/Release` then place any missing DLLs or
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models in the same directory, or change the code to look in a different place.
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For example, the following OpenCV DLLs were needed for the non-Debug executable,
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and were copied from `${OpenCV_DIR}/bin` to the `RelWithDebInfo` directory where
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the .exe is written:
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opencv_core411.dll
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opencv_highgui411.dll
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opencv_imgcodecs411.dll
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opencv_imgproc411.dll
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opencv_videoio411.dll
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The pre-trained model files used by the examples are provided automatically when
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CMake is run, and are placed in each sample's build directory. For example, the
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following three are placed in `build/wrappers/openvino/face`:
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README.txt
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face-detection-adas-0001.xml
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face-detection-adas-0001.bin
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Pre-trained models were taken from the [OpenVINO model zoo](https://software.intel.com/en-us/openvino-toolkit/documentation/pretrained-models),
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and [public models](https://software.intel.com/en-us/articles/model-downloader-essentials)
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were converted using the Model Converter.
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### The Device
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The OpenVINO models may be loaded into any available device—CPU, GPU, Movidius™
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Neural Compute Stick, or FPGA—provided the right .dll or .so files are
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available.
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By default, the samples use the `CPU` device for running rather than assuming a
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GPU. If no discreet GPU is available, the CPU will likely run faster, but feel
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free to experiment by chaning the device.
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To use the `CPU` device, the samples compile and depend on `cpu_extension.dll`
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(Windows) or `libcpu_extension.so` (Linux) at runtime.
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If you encounter runtime error complaining of a missing component by these names,
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these can be found as a result of the regular build and then placed in the same
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place as all the model files (i.e., the current directory or alongside the .exe).
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### Linux
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1. Download the latest OpenVINO toolkit and follow the [instructions for Linux installation](https://docs.openvinotoolkit.org/latest/_docs_install_guides_installing_openvino_linux.html). These are very similar to
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the Windows instructions above.
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2. Follow [the instructions](https://github.com/IntelRealSense/librealsense/blob/master/doc/installation.md) to build `librealsense` from source, but:
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* Add `-DBUILD_OPENVINO_EXAMPLES=true -DOpenCV_DIR=... -DINTEL_OPENVINO_DIR=...` to your `cmake` command
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3. Make sure you have `$LD_LIBRARY_PATH` pointing to the OpenVINO libraries when
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running the examples. Run `source $INTEL_OPENVINO_DIR/bin/setupvars.sh` to do
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this.
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