Inference Engine Python* API
Project description
OpenVINO™ Toolkit
OpenVINO™ toolkit quickly deploys applications and solutions that emulate human vision. Based on Convolutional Neural Networks (CNNs), the toolkit extends computer vision (CV) workloads across Intel® hardware, maximizing performance. The OpenVINO™ toolkit includes the Deep Learning Deployment Toolkit (DLDT).
OpenVINO™ toolkit:
- Enables CNN-based deep learning inference on the edge
- Supports heterogeneous execution across an Intel® CPU, Intel® Integrated Graphics, Intel® FPGA, Intel® Neural Compute Stick 2, and Intel® Vision Accelerator Design with Intel® Movidius™ VPUs
- Speeds time-to-market via an easy-to-use library of computer vision functions and pre-optimized kernels
- Includes optimized calls for computer vision standards, including OpenCV* and OpenCL™
Operating Systems:
- Ubuntu* 18.04 long-term support (LTS), 64-bit
- Windows* 10, 64-bit
- macOS* 10.15, 64-bit
Install the Runtime Package Using the PyPI Repository
- Set up and update pip to the highest version:
python3 -m pip install --upgrade pip
- Install the Intel® distribution of OpenVINO™ toolkit:
pip install openvino
- Add PATH to environment variables.
- Ubuntu* 18.04 and macOS*:
export LD_LIBRARY_PATH=<library_dir>:${LD_LIBRARY_PATH}
- Windows* 10:
set PATH=<library_dir>;%PATH%
How to find library_dir
:
- Ubuntu*, macOS*:
- standard user:
echo $(python3 -m site --user-base)/lib
- root or sudo user:
/usr/local/lib
- virtual environments or custom Python installations (from sources or tarball):
echo $(which python3)/../../lib
- standard user:
- Windows*:
- standard Python:
python -c "import os, sys; print((os.path.dirname(sys.executable))+'\Library\\bin')"
- virtual environments or custom Python installations (from sources or tarball):
python -c "import os, sys; print((os.path.dirname(sys.executable))+'\..\Library\\bin')"
- standard Python:
- Verify that the package is installed:
python3 -c "import openvino"
Now you are ready to develop and run your application.
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