* Replaced wget by curl
* Moved CI stuff into Dockerfile.ci
* Use docker-compose to run commnands inside docker (need environment variables)
* Added patool again (to support different archive formats)
* Roll back tensorflow version: 1.15 -> 1.13.1
Fixed https://github.com/opencv/cvat/issues/982
Fixed https://github.com/opencv/cvat/issues/1017
* datumaro install tensorflow 2.x now. It breaks automatic annotation
using TF.
* Follow redirects in curl (auto_segmentation)
* added tfrecord loader/dumper
* add comment
* remove unused import
* used the latest version of tensorflow(1.12.3) which supports cuda 9.0
updated cudnn library
install tensorflow by default and replace it by tensorflow-gpu in case
of cuda support is enabled
* Updated changelog
* OpenVINO installation
* Separate tf_annotation -> tf_annotation and cuda support.
* TF Annotation app now supports openVino backend
* Doc for CUDA component
* OpenVINO Readme file was added
* OpenVINO env and pip requirements for model optimizer
* Update logging
* TF annotation Readme file was added
* Update CHANGELOG
* Keep aspect ratio for image, not reverse input channels
* Move analytics into components