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* 20.04 long-term support (LTS), 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-ubuntu20
- Add PATH to environment variables.
- Ubuntu* 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.
Metadata
Release files for openvino-ubuntu20 2021.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| openvino_ubuntu20-2021.2-170-cp38-cp38-manylinux2014_x86_64.whl | CPython 3.8 | CPython 3.8 | Linux glibc 2.17+ x86-64 | Details |
| openvino_ubuntu20-2021.2-170-cp37-cp37m-manylinux2014_x86_64.whl | CPython 3.7 | CPython 3.7 pymalloc | Linux glibc 2.17+ x86-64 | Details |
Total release size: 63.8 MB
Release files / openvino_ubuntu20-2021.2-170-cp38-cp38-manylinux2014_x86_64.whl
| Download URL | openvino_ubuntu20-2021.2-170-cp38-cp38-manylinux2014_x86_64.whl |
|---|---|
| Size | 31.8 MB |
| Tags | CPython 3.8 Linux glibc 2.17+ x86-64 |
|
SHA-256 checksum How to use checksums |
9ee6304ece01e48f65230b5a6c8d9d47e553419ee5f72109337ce0f988051212
|
|
BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.9
|
Release files / openvino_ubuntu20-2021.2-170-cp37-cp37m-manylinux2014_x86_64.whl
| Download URL | openvino_ubuntu20-2021.2-170-cp37-cp37m-manylinux2014_x86_64.whl |
|---|---|
| Size | 32.0 MB |
| Tags | CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.17+ x86-64 |
|
SHA-256 checksum How to use checksums |
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|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.9
|