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History

Andrey Zhavoronkov e7808cfb03 Data streaming using chunks (#1007 ) Huge feature (200+ commits from different developers). It completely changes layout of data (please expect very long DB migration process if you have a lot of tasks). The primary idea is to send data as zip chunks (e.g. 36 images in one chunk) or encoded video chunks and decode them on the client side. It helps to solve the problem with latency when you try to view a separate frame in the UI quickly (play mode). Another important feature of the patch is to provide access to the original images. Thus for annotations the client uses compressed chunks but if you want to export a dataset Datumaro will use original chunks (but video will be decoded with original quality and encoded with maximum/optimal quality in any case).		6 years ago
..
auto_annotation	pass in model name and task id to run auto annotation script (#934 )	6 years ago
cli	Data streaming using chunks (#1007 )	6 years ago
coco	Upgrade Numpy to avoid Arbitrary Code Execution. Upgrade Django to avoid MitM (#575 )	7 years ago
mask	Fixed '=' to '==' for numpy in requirments (#556 )	7 years ago
open_model_zoo	Bump tensorflow from 1.12.3 to 1.15.0 in /cvat/requirements (#968 )	6 years ago
tfrecords	updated CUDA to version 10 (#1138 )	6 years ago
voc	VOC converter: Use depth from CVAT XML if available (#885 )	6 years ago
yolo	fixed label order (#669 )	7 years ago
README.md	YOLO adapted version of PASCAL VOC converter.py (#454 )	7 years ago
__init__.py	Moved development on public github.	8 years ago

README.md

CVAT utilities

Description

This folder contains some useful utilities for Computer Vision Annotation Tool (CVAT). To read about a certain utility please choose a link: