Counting 2,653 Big Data & Machine Learning Frameworks, Toolsets, and Examples...
Suggestion? Feedback? Tweet @stkim1

Author
Last Commit
Apr. 24, 2018
Created
Jan. 17, 2017

Deep Video Analytics     Build Status Build Status

by Akshay Bhat

UI Screenshot

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.

For installation instructions & demo please visit https://www.deepvideoanalytics.com

Documentation & tutorial

Experiments

Deployment

We provide instructions for deploying DVA in three scenarios.

  1. deploy/cpu contains docker-compose files for non-GPU single machine deployments on Linode, AWS, GCP etc.

  2. deploy/gpu contains docker-compose files for GPU single machine deployments on GCP, AWS etc.

  3. deploy/kube contains files used for launching DVA in a scalable GKE + GCS setup, with and without GPUs.

Development

  • deploy/dev contains docker-compose files for interactively developing DVA by using host server directory mapped as a volume.

Code organization

  • /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 and 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 present in this repository and their licenses

Library Link to the license
YAD2K MIT License
AdminLTE2 MIT License
FabricJS MIT License
Facenet MIT License
JSFeat MIT License
MTCNN MIT License
Insight Face MIT License
CRNN.pytorch MIT License
Original CRNN code by Baoguang Shi MIT License
Object Detector App using TF Object detection API MIT License
Plotly.js MIT License
CRF as RNN MIT License
Text Detection CTPN MIT License
SphereFace 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
CROW Apache 2.0
LOPQ Apache 2.0
Open Images Pre-trained network Apache 2.0

Libraries present in container (/root/thirdparty/)

Library Link to the license
pqkmeans MIT License
faiss BSD + PATENTS License

Additional libraries & frameworks

License & Copyright

Copyright 2016-2017, Akshay Bhat, Cornell University, All rights reserved.

Contact

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

Latest Releases
docker.container.19
 Feb. 24 2018
docker.container.18
 Feb. 22 2018
docker.container.17
 Feb. 22 2018
docker.container.16
 Jan. 4 2018
docker.container.15
 Dec. 22 2017