Video Analytics Serving Docker images.
50K+
Video Analytics Serving (VA Serving) is a python package and microservice for deploying hardware optimized media analytics pipelines. It supports pipelines defined in GStreamer* or FFmpeg* media frameworks and provides APIs to discover, start, stop, customize and monitor pipeline execution. Video Analytics Serving is based on Intel® Distribution of OpenVINO™ Toolkit - DL Streamer and FFmpeg Video Analytics.
This container provides a standalone microservice based on DL Streamer with the following pipelines:
| Pipeline Name | Description |
|---|---|
| object_detection | Detect and label objects |
| object_classification | As object_detection adding metadata such as object subtype and color |
| object_tracking | As object_classification adding tracking identifier to metadata |
| audio_detection | Analyze audio streams for events such as breaking glass or barking dogs. |
| action_recognition | Classifies general purpose actions in input video such as tying a bow tie or shaking hands. |
IMPORTANT: Video Analytics Serving is provided as a pre-production preview. Developers deploying Video Analytics Serving based microservices should review them against their production requirements.
IMPORTANT: DL Streamer Edge AI Extension images can now be found at intel/dlstreamer-edge-ai-extension.
Docker must be given access to the HTTP port, which is 8080 by default. This example also gives access to the /tmp folder for writing metadata results.
docker run -p 8080:8080 -v /tmp:/tmp intel/video-analytics-serving
Enable GPU inference by giving docker access to device /dev/dri.
NOTE: Ubuntu20 hosts need extra docker options to access GPU
docker run -p 8080:8080 -v /tmp:/tmp --device /dev/dri intel/video-analytics-serving
This shows how to make a request via curl that does the following
curl localhost:8080/pipelines/object_detection/person_vehicle_bike -X POST -H \
'Content-Type: application/json' -d \
'{
"source": {
"uri": "https://github.com/intel-iot-devkit/sample-videos/blob/master/person-bicycle-car-detection.mp4?raw=true",
"type": "uri"
},
"parameters" : {
"threshold" : 0.75
},
"destination": {
"metadata": {
"type": "file",
"path": "/tmp/detection_results.json",
"format": "json-lines"
}
}
}'
Output can be viewed as follows
tail -f /tmp/detection_results.json
{"objects":[{"detection":{"bounding_box":{"x_max":0.7481285929679871,"x_min":0.6836653351783752,"y_max":0.9999656677246094,"y_min":0.7867168188095093},"confidence
":0.8825281858444214,"label":"person","label_id":1},"h":92,"roi_type":"person","w":50,"x":525,"y":340}],"resolution":{"height":432,"width":768},"source":"https://
github.com/intel-iot-devkit/sample-videos/blob/master/person-bicycle-car-detection.mp4?raw=true","timestamp":1833333333}
{"objects":[{"detection":{"bounding_box":{"x_max":0.7502986788749695,"x_min":0.6836960911750793,"y_max":0.9965760111808777,"y_min":0.7709739804267883},"confidence
":0.9252141118049622,"label":"person","label_id":1},"h":97,"roi_type":"person","w":51,"x":525,"y":333}],"resolution":{"height":432,"width":768},"source":"https://
github.com/intel-iot-devkit/sample-videos/blob/master/person-bicycle-car-detection.mp4?raw=true","timestamp":1916666666}
{"objects":[{"detection":{"bounding_box":{"x_max":0.7533045411109924,"x_min":0.6833932995796204,"y_max":0.9992516040802002,"y_min":0.7517305612564087},"confidence
":0.9160457849502563,"label":"person","label_id":1},"h":107,"roi_type":"person","w":54,"x":525,"y":325}],"resolution":{"height":432,"width":768},"source":"https:/
/github.com/intel-iot-devkit/sample-videos/blob/master/person-bicycle-car-detection.mp4?raw=true","timestamp":2000000000}
{"objects":[{"detection":{"bounding_box":{"x_max":0.7569090723991394,"x_min":0.6831721663475037,"y_max":0.9893120527267456,"y_min":0.745476245880127},"confidence"
:0.9452301859855652,"label":"person","label_id":1},"h":105,"roi_type":"person","w":57,"x":525,"y":322}],"resolution":{"height":432,"width":768},"source":"https://
github.com/intel-iot-devkit/sample-videos/blob/master/person-bicycle-car-detection.mp4?raw=true","timestamp":2083333333}
For more details on making custom requests or building from source see https://github.com/intel/video-analytics-serving/tree/v0.7.0-beta
LEGAL NOTICE: By accessing, downloading or using this software and any required dependent software (the "Software Package"), you agree to the terms and conditions of the software license agreements for the Software Package, which may also include notices, disclaimers, or license terms for third party software included with the Software Package. Please refer to the "third-party-programs.txt" or other similarly-named text file for additional details.
| Components | License |
|---|---|
| Dockerfile | BSD 3-clause "New" or "Revised" License Docker image with 0.7.0 tag uses openvino/ubuntu20_data_runtime as a base, and several community modules and scripts. Copyright (c) 2019-2021 Intel Corporation All rights reserved. |
| OpenVINO Ubuntu20.04 Data Runtime Docker Image | Dockerfile: Apache 2.0 License, Image: 2021.4.2 (various) |
| python-dateutil | BSD 3-clause "New" or "Revised" LicenseCopyright (c) 2018-2021 Intel Corporation All rights reserved. |
| numpy | BSD 3-clause "New" or "Revised" License (Numpy customized)Copyright (c) 2005-2021, NumPy Developers. All rights reserved. |
| Python3 | PSFCopyright © 2001-2021 Python Software Foundation; All Rights Reserved |
| Python-Pip | MIT LicenseCopyright (c) 2008-2021 The pip developers (see AUTHORS.txt file) |
| setuptools | MIT LicenseCopyright (C) 2016 Jason R Coombs [email protected] |
| jsonschema | MIT LicenseCopyright (c) 2013 Julian Berman |
| pyyaml | MIT LicenseCopyright (c) 2017-2021 Ingy döt Net |
| swagger-ui-bundle | Apache License 2.0Copyright 2020-2021 SmartBear Software Inc. |
| Tornado Web Server | Apache License 2.0Copyright: 2009-2011 Facebook |
| Requests | Apache License 2.0Copyright 2019 Kenneth Reitz |
| Zalando Connexion | Apache License 2.0Copyright 2015 Zalando SE |
| Intel® Distribution of OpenVINO™ Toolkit - OpenModelZoo | Apache License 2.0Copyright (c) 2020-2021 Intel Corporation |
| Intel® Distribution of OpenVINO™ Toolkit - Deep Learning Deployment Toolkit | Apache License 2.0Copyright (c) 2020-2021 Intel Corporation |
As with any pre-built image usage, it is the image user's responsibility to ensure that any use of this image complies with any relevant licenses and potential fees for all software contained within. We will have no indemnity or warranty coverage from suppliers.
Content type
Image
Digest
Size
930.3 MB
Last updated
almost 5 years ago
docker pull intel/video-analytics-servingPulls:
47
Last week