* Add preview && some fixes
* Fix case with sub dirs on cloud storage
* Move server part from ui_support_cloud_storage && fix missing id field
* Add support_key_secret_key_pair
* Fix several moments
* Add index resetting
* Fix pylint errors
* Remove excess migration
* tmp
* Some fixes
* Fixes
* fix
* [server] Add cloud storage status && fixes
* Remove unused import
* Add manifest set_index method
* Implement status support for Azure blob container
* Move specific attributes parsing into utils
* Fix missing in migration
* Fix error display
* some fix
* Update migration dependency
* Update google cloud storage status
* Update migrtaions
* Update CHANGELOG
* Fix issue of infinite loop due to incorrect status comparison.
* Update CHANGELOG.md
* Fix PEP8.
* Update failure case to break from infinite loop.
* Update utils/cli/core/core.py
Co-authored-by: Boris Sekachev <boris.sekachev@intel.com>
* Add check for unknown failure.
* Fix logging in failure case.
* Update CHANGELOG.md
Co-authored-by: Boris Sekachev <boris.sekachev@intel.com>
Co-authored-by: André Aquilina <andre.aquilina@dysismedical.com>
* add cli kwargs for image_quality and frame_step when creating task
* add **kwargs to the tasks_data function call
* add the corresponding options into argument parser
* Update core.py
update license header
* update license header
* fix definition.py help text
* Add option to include git repository for annotation synchronisation.
* Add arge parser for git dataset repository in task create.
* Update changelog.
* Add API for git.
* Add verification procedure for dataset repository creation.
Co-authored-by: André Aquilina <andre.aquilina@dysismedical.com>
* Added support for manifest file
* Added data migration
* Updated tests
* Update CHANGELOG
* Update manifest documentation
* Fix case with 3d data
Co-authored-by: Nikita Manovich <nikita.manovich@intel.com>
* Added ability to upload meta information with video & some fixes
* Added documentation for data on the fly preparation
* Added ability to prepare meta information for video manually
* fix
* style: fix codacy issues
* Refactoring
* docs: add optional parameter
* Add test
* Add license header
* Update CHANGELOG
Co-authored-by: Boris Sekachev <boris.sekachev@yandex.ru>
* Initial experiments with nuclio
* Update nuclio prototype
* Improve nuclio prototype for dextr.
* Dummy lambda manager
* OpenFaaS prototype (dextr.bin and dextr.xml are empty).
* Moved openfaas prototype.
* Add comments
* Add serializers and HLD for lambda_manager
* Initial version of Mask RCNN (without debugging)
* Initial version for faster_rcnn_inception_v2_coco
* Fix faster_rcnn_inception_v2_coco
* Implemented mask_rcnn_inception_resnet_v2_atrous_coco
* Implemented yolo detector as a lambda function
* Removed dextr app.
* Added types for each function (detector and interactor)
* Initial version of lambda_manager.
* Implement a couple of methods for lambda:
GET /api/v1/lambda/functions
GET /api/v1/lambda/functions/public.dextr
* First working version of dextr serverless function
* First version of dextr which works in UI.
* Modify omz.public.faster_rcnn_inception_v2_coco
- image decoding
- restart policy always for the function
* Improve omz.public.mask_rcnn_inception_resnet_v2_atrous_coco
* Improve omz.public.yolo-v3-tf function
* Implemented the initial version of requests for lambda manager.
* First working version of POST /api/v1/lambda/requests
* Updated specification of function.yaml (added labels and used annotations section).
* Added health check for containers (nuclio dashboard feature)
* Read labels spec from function.yaml.
* Added settings for NUCLIO
* Fixed a couple of typos. Now it works in most cases.
* Remove Plugin REST API
* Remove tf_annotation app (it will be replaced by serverless function)
* Remove tf_annotation and cuda components
* Cleanup docs and Dockerfile from CUDA component.
* Just renamed directories inside serverless
* Remove redundant files and code
* Remove redundant files.
* Remove outdated files
* Remove outdated code
* Delete reid app and add draft of serverless function for reid.
* Model list in UI.
* Fixed the framework name (got it from lambda function).
* Add maxRequestBodySize for functions, remove redundant code from UI for auto_annotation.
* Update view of models page.
* Unblock mapping for "primary" models.
* Implement cleanup flag for lambda/requests and labeling mapping for functions.
* Implement protection from running multiple jobs for the same task.
* Fix invocation of functions in docker container.
* Fix Dockerfile.ci
* Remove unused files from lambda_manager
* Fix codacy warnings
* Fix codacy issues.
* Fix codacy warnings
* Implement progress and cancel (aka delete) operation.
* Send annotations in batch.
* Fix UI. Now it can retrieve information about inference requests in progress.
* Update CHANGELOG.md
* Update cvat-ui version.
* Update nuclio version.
* Implement serverless/tensorflow/faster_rcnn_inception_v2_coco
* Add information how to install nuclio platform and run serverless functions.
* Add installation instructions for serverless functions.
* Update OpenVINO files which are responsible for loading network
* relocated functions
* Update dextr function.
* Update faster_rcnn function from omz
* Fix OpenVINO Mask-RCNN
* Fix YOLO v3 serverless function.
* Dummy serverless functions for a couple of more OpenVINO models.
* Protected lambda manager views by correct permissions.
* Fix name of Faster RCNN from Tensorflow.
* Implement Mask RCNN via Tensorflow serverless function.
* Minor client changes (#1847)
* Minor client changes
* Removed extra code
* Add reid serverless function (no support in lambda manager).
* Fix contribution guide.
* Fix person-reidentification-retail-300 and implement text-detection-0004
* Add semantic-segmentation-adas-0001
* Moving model management to cvat-core (#1905)
* Squached changes
* Removed extra line
* Remove duplicated files for OpenVINO serverless functions.
* Updated CHANGELOG.md
* Remove outdated code.
* Running dextr via lambda manager (#1912)
* Deleted outdated migration.
* Add name for DEXTR function.
* Fix restart policy for serverless functions.
* Fix openvino serverless functions for images with alpha channel
* Add more tensorflow serverless functions into deploy.sh
* Use ID instead of name for DEXTR (#1926)
* Update DEXTR function
* Added source "auto" inside lambda manager for automatic annotation.
* Customize payload (depends on type of lambda function).
* First working version of REID (Server only).
* Fix codacy warnings
* Avoid exception during migration (workaround)
File "/usr/local/lib/python3.5/dist-packages/django/db/utils.py", line 89, in __exit__
raise dj_exc_value.with_traceback(traceback) from exc_value
File "/usr/local/lib/python3.5/dist-packages/django/db/backends/utils.py", line 84, in _execute
return self.cursor.execute(sql, params)
django.db.utils.ProgrammingError: table "engine_pluginoption" does not exist
* Add siammask serverless function (it doesn't work, need to serialize state)
* Run ReID from UI (#1949)
* Removed reid route in installation.md
* Fix a command to get lena image in CONTRIBUTION guide.
* Fix typo and crash in case a polygon is a line.
Co-authored-by: Boris Sekachev <40690378+bsekachev@users.noreply.github.com>
* Upload annotations on task creation
* Bulk upload v1
* Not working
* Annotation upon task creation finished
* Functionality to upload annotations on task creation
* Functionality to upload annotations on task creation
* Functionality to upload annotations on task creation
* Functionality to upload annotations on task creation
* Fix trailing whitespace
* Use status request for checking task completion
* fixed default format name
Co-authored-by: Eric Grinstein <v-ergri@microsoft.com>
Co-authored-by: Andrey Zhavoronkov <andrey.zhavoronkov@intel.com>
Co-authored-by: Nikita Manovich <40690625+nmanovic@users.noreply.github.com>
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).
* 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)
Andrey Zhavoronkov
Maria Khrustaleva
Timur Osmanov
Jan Hünnemeyer
Chris
Dmitry Kalinin
Nikita Manovich
Diego Cesar
André Aquilina
qztseng
Boris Sekachev
Adam Harvey
Ali Jahani
Vitaliy Nishukov
Maxim Zhiltsov
Nikita Manovich
Young
Liron Ilouz
Eric Grinstein
Andrey Zhavoronkov
zhiltsov-max
Ben Hoff
Seungwon Jeong
dependabot[bot]
himalayanZephyr
a-andre