Deep Video Analytics is a platform for indexing and extracting information from videos and images. With latest version of docker installed correctly, you can run Deep Video Analytics in minutes locally (even without a GPU) using a single command.
Documentation & tutorial
For a quick overview we strongly recommend going through the presentation in readme.pdf
Documentation along with a tutorial is being written in /docs/tutorial directory.
- OCR example has been moved to /docs/experiments/ocr directory.
- More experiments coming soon!
We provide instructions for deploying DVA in three scenarios.
deploy/cpu contains docker-compose files for non-GPU single machine deployments on Linode, AWS, GCP etc.
deploy/gpu contains docker-compose files for GPU single machine deployments on GCP, AWS etc.
deploy/kube contains files used for launching DVA in a scalable GKE + GCS setup
- deploy/dev contains docker-compose files for interactively developing DVA by using host server directory mapped as a volume.
- /client : Python client using DVA REST API
- /configs : ngnix config + defaults.py defining models + processing pipelines (can be replaced by mounting a volume)
- /deploy : Dockerfiles + Instructions for development, single machine deployment abnd scalable deployment with Kubernetes
- /docs : Documentation, tutorial and experiments
- /tests : Files required for testing
- /repos : Code copied from third party repos, e.g. Yahoo LOPQ, TF-CTPN etc.
- /server : dvalib + django server contains contains bulk of the code for UI, App and models.
- /logs : Empty dir for storing logs
Libraries modified in code and their licenses
|Library||Link to the license|
|Original CRNN code by Baoguang Shi||MIT License|
|Object Detector App using TF Object detection API||MIT License|
|CRF as RNN||MIT License|
|Text Detection CTPN||MIT License|
|Segment annotator||BSD 3-clause|
|TF Object detection API||Apache 2.0|
|TF models/slim||Apache 2.0|
|TF models/delf||Apache 2.0|
|Youtube 8M feature extractor||Apache 2.0|
|Open Images Pre-trained network||Apache 2.0|
Additional libraries & frameworks
- FFmpeg (not linked, called via a Subprocess)
- All packages in requirements.txt
- All dependancies in Dockerfile
License & Copyright
Copyright 2016-2017, Akshay Bhat, Cornell University, All rights reserved.
Deep Video Analytics is currently in active development. The license will be relaxed once a stable release version is reached. Please contact me for more information. For more information see answer on this issue