Don't be worried by complexity of this banner, with latest version of docker installed correctly, you can run Deep Video Analytics in minutes locally (even without a GPU) using a single command.
Author: Akshay Bhat, Cornell University.
Deep Video Analytics is a platform for indexing and extracting information from videos and images. For installation instructions & demo go to https://www.deepvideoanalytics.com
- Pytorch License
- Darknet License
- AdminLTE2 License
- FabricJS License
- Modified PySceneDetect License
- Modified SSD-Tensorflow Individual files are marked as Apache
- Facenet License
- MTCNN TensorFlow port of MTCNN for face detection/alignment
- Locally Optimized Product Quantization License
- Open Images Pre training network for text tags License
- JSFeat not used but included
- Segment annotator Not used but inclued
- FFmpeg Not linked, used only through a command line interface.
- Tensorflow License
- FAISS License (CC-BY-NC) will likely be removed from release candidate
- Nvidia-docker
- Docker
- OpenCV
- Numpy
Copyright 2016-2017, Akshay Bhat, Cornell University, All rights reserved.
Please contact me for more information, I plan on relaxing the license soon. For more information about the approximate timeline see my answer on this issue