From 271daf67443ad2113b425cf279a8678d1d860d76 Mon Sep 17 00:00:00 2001 From: Andrey Zhavoronkov Date: Fri, 15 Sep 2023 15:07:11 +0300 Subject: [PATCH 1/9] Prepare for 2.8.0 --- CHANGELOG.md | 19 +++++++++++++++++++ cvat-cli/requirements/base.txt | 2 +- cvat-cli/src/cvat_cli/version.py | 2 +- cvat-sdk/gen/generate.sh | 2 +- cvat/__init__.py | 2 +- cvat/schema.yml | 2 +- docker-compose.yml | 18 +++++++++--------- helm-chart/values.yaml | 4 ++-- 8 files changed, 35 insertions(+), 16 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 9684a6fd7aef..dd0148f52518 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -5,6 +5,25 @@ All notable changes to this project will be documented in this file. The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## \[Unreleased\] +### Added +- TDB + +### Changed +- TDB + +### Deprecated +- TDB + +### Removed +- TDB + +### Fixed +- TDB + +### Security +- TDB + ## \[2.7.1\] - 2023-09-15 ### Fixed diff --git a/cvat-cli/requirements/base.txt b/cvat-cli/requirements/base.txt index 73d4e06cfc53..eac4427c9d55 100644 --- a/cvat-cli/requirements/base.txt +++ b/cvat-cli/requirements/base.txt @@ -1,3 +1,3 @@ -cvat-sdk~=2.7.1 +cvat-sdk~=2.8.0 Pillow>=6.2.0 setuptools>=65.5.1 # not directly required, pinned by Snyk to avoid a vulnerability diff --git a/cvat-cli/src/cvat_cli/version.py b/cvat-cli/src/cvat_cli/version.py index 61979e596292..7035cc17c429 100644 --- a/cvat-cli/src/cvat_cli/version.py +++ b/cvat-cli/src/cvat_cli/version.py @@ -1 +1 @@ -VERSION = "2.7.1" +VERSION = "2.8.0" diff --git a/cvat-sdk/gen/generate.sh b/cvat-sdk/gen/generate.sh index 41f03c22e958..77f513803a68 100755 --- a/cvat-sdk/gen/generate.sh +++ b/cvat-sdk/gen/generate.sh @@ -8,7 +8,7 @@ set -e GENERATOR_VERSION="v6.0.1" -VERSION="2.7.1" +VERSION="2.8.0" LIB_NAME="cvat_sdk" LAYER1_LIB_NAME="${LIB_NAME}/api_client" DST_DIR="$(cd "$(dirname -- "$0")/.." && pwd)" diff --git a/cvat/__init__.py b/cvat/__init__.py index b53dc921832e..989bc3512008 100644 --- a/cvat/__init__.py +++ b/cvat/__init__.py @@ -4,6 +4,6 @@ from cvat.utils.version import get_version -VERSION = (2, 7, 1, 'final', 0) +VERSION = (2, 8, 0, 'alpha', 0) __version__ = get_version(VERSION) diff --git a/cvat/schema.yml b/cvat/schema.yml index 4e7f68fde8f5..b5952374b922 100644 --- a/cvat/schema.yml +++ b/cvat/schema.yml @@ -1,7 +1,7 @@ openapi: 3.0.3 info: title: CVAT REST API - version: 2.7.1 + version: 2.8.0 description: REST API for Computer Vision Annotation Tool (CVAT) termsOfService: https://www.google.com/policies/terms/ contact: diff --git a/docker-compose.yml b/docker-compose.yml index 6a3fa2842d51..e11b68d2ad46 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -34,7 +34,7 @@ services: cvat_server: container_name: cvat_server - image: cvat/server:${CVAT_VERSION:-v2.7.1} + image: cvat/server:${CVAT_VERSION:-dev} restart: always depends_on: - cvat_redis @@ -73,7 +73,7 @@ services: cvat_utils: container_name: cvat_utils - image: cvat/server:${CVAT_VERSION:-v2.7.1} + image: cvat/server:${CVAT_VERSION:-dev} restart: always depends_on: - cvat_redis @@ -98,7 +98,7 @@ services: cvat_worker_import: container_name: cvat_worker_import - image: cvat/server:${CVAT_VERSION:-v2.7.1} + image: cvat/server:${CVAT_VERSION:-dev} restart: always depends_on: - cvat_redis @@ -121,7 +121,7 @@ services: cvat_worker_export: container_name: cvat_worker_export - image: cvat/server:${CVAT_VERSION:-v2.7.1} + image: cvat/server:${CVAT_VERSION:-dev} restart: always depends_on: - cvat_redis @@ -144,7 +144,7 @@ services: cvat_worker_annotation: container_name: cvat_worker_annotation - image: cvat/server:${CVAT_VERSION:-v2.7.1} + image: cvat/server:${CVAT_VERSION:-dev} restart: always depends_on: - cvat_redis @@ -167,7 +167,7 @@ services: cvat_worker_webhooks: container_name: cvat_worker_webhooks - image: cvat/server:${CVAT_VERSION:-v2.7.1} + image: cvat/server:${CVAT_VERSION:-dev} restart: always depends_on: - cvat_redis @@ -191,7 +191,7 @@ services: cvat_worker_quality_reports: container_name: cvat_worker_quality_reports - image: cvat/server:${CVAT_VERSION:-v2.7.1} + image: cvat/server:${CVAT_VERSION:-dev} restart: always depends_on: - cvat_redis @@ -213,7 +213,7 @@ services: cvat_worker_analytics_reports: container_name: cvat_worker_analytics_reports - image: cvat/server:${CVAT_VERSION:-v2.7.1} + image: cvat/server:${CVAT_VERSION:-dev} restart: always depends_on: - cvat_redis @@ -236,7 +236,7 @@ services: cvat_ui: container_name: cvat_ui - image: cvat/ui:${CVAT_VERSION:-v2.7.1} + image: cvat/ui:${CVAT_VERSION:-dev} restart: always depends_on: - cvat_server diff --git a/helm-chart/values.yaml b/helm-chart/values.yaml index 87bcf36eb71b..3b5685a6d1a4 100644 --- a/helm-chart/values.yaml +++ b/helm-chart/values.yaml @@ -104,7 +104,7 @@ cvat: additionalVolumeMounts: [] replicas: 1 image: cvat/server - tag: v2.7.1 + tag: dev imagePullPolicy: Always permissionFix: enabled: true @@ -128,7 +128,7 @@ cvat: frontend: replicas: 1 image: cvat/ui - tag: v2.7.1 + tag: dev imagePullPolicy: Always labels: {} # test: test From b2957abc667ddb1ed3d3e1ed006ce1031fe8b48c Mon Sep 17 00:00:00 2001 From: Boris Sekachev Date: Fri, 15 Sep 2023 16:55:27 +0300 Subject: [PATCH 2/9] Do not reload the page when changing job state (#6851) --- CHANGELOG.md | 2 +- cvat-core/src/session-implementation.ts | 18 +++++-- cvat-core/src/session.ts | 5 +- cvat-ui/src/actions/annotation-actions.ts | 2 +- cvat-ui/src/actions/jobs-actions.ts | 27 ++++++++++ cvat-ui/src/actions/tasks-actions.ts | 20 ------- .../top-bar/annotation-menu.tsx | 5 +- .../components/job-item/job-actions-menu.tsx | 16 ++---- cvat-ui/src/components/job-item/job-item.tsx | 4 +- cvat-ui/src/components/jobs-page/job-card.tsx | 11 ++-- .../src/components/jobs-page/jobs-content.tsx | 10 +++- .../src/components/jobs-page/jobs-page.tsx | 11 ++-- .../top-bar/annotation-menu.tsx | 54 +++++++++++-------- cvat-ui/src/reducers/annotation-reducer.ts | 15 ++++-- cvat-ui/src/reducers/index.ts | 6 --- cvat-ui/src/reducers/jobs-reducer.ts | 26 +++++++++ cvat-ui/src/reducers/notifications-reducer.ts | 16 ++++++ 17 files changed, 166 insertions(+), 82 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index dd0148f52518..8f2d8faba22e 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -10,7 +10,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 - TDB ### Changed -- TDB +- Do not reload annotation view when renew the job or update job state () ### Deprecated - TDB diff --git a/cvat-core/src/session-implementation.ts b/cvat-core/src/session-implementation.ts index 6a064722aa2e..d21422477744 100644 --- a/cvat-core/src/session-implementation.ts +++ b/cvat-core/src/session-implementation.ts @@ -70,9 +70,21 @@ export function implementJob(Job) { jobData.assignee = jobData.assignee.id; } - const data = await serverProxy.jobs.save(this.id, jobData); - this._updateTrigger.reset(); - return new Job(data); + let updatedJob = null; + try { + const data = await serverProxy.jobs.save(this.id, jobData); + updatedJob = new Job(data); + this._updateTrigger.reset(); + } catch (error) { + updatedJob = new Job(this._initialData); + throw error; + } finally { + this.stage = updatedJob.stage; + this.state = updatedJob.state; + this.assignee = updatedJob.assignee; + } + + return this; } const jobSpec = { diff --git a/cvat-core/src/session.ts b/cvat-core/src/session.ts index 1c9189903868..5fc657fff922 100644 --- a/cvat-core/src/session.ts +++ b/cvat-core/src/session.ts @@ -381,7 +381,7 @@ export class Job extends Session { log: CallableFunction; }; - constructor(initialData: SerializedJob) { + constructor(initialData: Readonly) { super(); const data = { id: undefined, @@ -536,6 +536,9 @@ export class Job extends Session { _updateTrigger: { get: () => updateTrigger, }, + _initialData: { + get: () => initialData, + }, }), ); diff --git a/cvat-ui/src/actions/annotation-actions.ts b/cvat-ui/src/actions/annotation-actions.ts index 414dd911c5e0..076a35f3f04f 100644 --- a/cvat-ui/src/actions/annotation-actions.ts +++ b/cvat-ui/src/actions/annotation-actions.ts @@ -29,7 +29,7 @@ import { ShapeType, Workspace, } from 'reducers'; -import { updateJobAsync } from './tasks-actions'; +import { updateJobAsync } from './jobs-actions'; import { switchToolsBlockerState } from './settings-actions'; interface AnnotationsParameters { diff --git a/cvat-ui/src/actions/jobs-actions.ts b/cvat-ui/src/actions/jobs-actions.ts index 4386f3d8c0b3..37cba5999da7 100644 --- a/cvat-ui/src/actions/jobs-actions.ts +++ b/cvat-ui/src/actions/jobs-actions.ts @@ -19,6 +19,9 @@ export enum JobsActionTypes { GET_JOB_PREVIEW_SUCCESS = 'GET_JOB_PREVIEW_SUCCESS', GET_JOB_PREVIEW_FAILED = 'GET_JOB_PREVIEW_FAILED', CREATE_JOB_FAILED = 'CREATE_JOB_FAILED', + UPDATE_JOB = 'UPDATE_JOB', + UPDATE_JOB_SUCCESS = 'UPDATE_JOB_SUCCESS', + UPDATE_JOB_FAILED = 'UPDATE_JOB_FAILED', DELETE_JOB = 'DELETE_JOB', DELETE_JOB_SUCCESS = 'DELETE_JOB_SUCCESS', DELETE_JOB_FAILED = 'DELETE_JOB_FAILED', @@ -46,6 +49,15 @@ const jobsActions = { createJobFailed: (error: any) => ( createAction(JobsActionTypes.CREATE_JOB_FAILED, { error }) ), + updateJob: () => ( + createAction(JobsActionTypes.UPDATE_JOB) + ), + updateJobSuccess: (job: Job) => ( + createAction(JobsActionTypes.UPDATE_JOB_SUCCESS, { job }) + ), + updateJobFailed: (jobID: number, error: any) => ( + createAction(JobsActionTypes.UPDATE_JOB_FAILED, { jobID, error }) + ), deleteJob: (jobID: number) => ( createAction(JobsActionTypes.DELETE_JOB, { jobID }) ), @@ -93,6 +105,21 @@ export const createJobAsync = (data: JobData): ThunkAction => async (dispatch) = } }; +export function updateJobAsync(jobInstance: Job): ThunkAction> { + return async (dispatch): Promise => { + try { + dispatch(jobsActions.updateJob()); + const updated = await jobInstance.save(); + dispatch(jobsActions.updateJobSuccess(updated)); + } catch (error) { + dispatch(jobsActions.updateJobFailed(jobInstance.id, error)); + return false; + } + + return true; + }; +} + export const deleteJobAsync = (job: Job): ThunkAction => async (dispatch) => { dispatch(jobsActions.deleteJob(job.id)); try { diff --git a/cvat-ui/src/actions/tasks-actions.ts b/cvat-ui/src/actions/tasks-actions.ts index 3ab967e1a458..e5f9e5edcaf8 100644 --- a/cvat-ui/src/actions/tasks-actions.ts +++ b/cvat-ui/src/actions/tasks-actions.ts @@ -22,7 +22,6 @@ export enum TasksActionTypes { DELETE_TASK_SUCCESS = 'DELETE_TASK_SUCCESS', DELETE_TASK_FAILED = 'DELETE_TASK_FAILED', CREATE_TASK_FAILED = 'CREATE_TASK_FAILED', - UPDATE_JOB_FAILED = 'UPDATE_JOB_FAILED', SWITCH_MOVE_TASK_MODAL_VISIBLE = 'SWITCH_MOVE_TASK_MODAL_VISIBLE', GET_TASK_PREVIEW = 'GET_TASK_PREVIEW', GET_TASK_PREVIEW_SUCCESS = 'GET_TASK_PREVIEW_SUCCESS', @@ -294,25 +293,6 @@ ThunkAction, {}, {}, AnyAction> { }; } -function updateJobFailed(jobID: number, error: any): AnyAction { - const action = { - type: TasksActionTypes.UPDATE_JOB_FAILED, - payload: { jobID, error }, - }; - - return action; -} - -export function updateJobAsync(jobInstance: any): ThunkAction, {}, {}, AnyAction> { - return async (dispatch: ActionCreator): Promise => { - try { - await jobInstance.save(); - } catch (error) { - dispatch(updateJobFailed(jobInstance.id, error)); - } - }; -} - export function switchMoveTaskModalVisible(visible: boolean, taskId: number | null = null): AnyAction { const action = { type: TasksActionTypes.SWITCH_MOVE_TASK_MODAL_VISIBLE, diff --git a/cvat-ui/src/components/annotation-page/top-bar/annotation-menu.tsx b/cvat-ui/src/components/annotation-page/top-bar/annotation-menu.tsx index 75d608140161..d187f78e7b4b 100644 --- a/cvat-ui/src/components/annotation-page/top-bar/annotation-menu.tsx +++ b/cvat-ui/src/components/annotation-page/top-bar/annotation-menu.tsx @@ -16,8 +16,7 @@ import Collapse from 'antd/lib/collapse'; // eslint-disable-next-line import/no-extraneous-dependencies import { MenuInfo } from 'rc-menu/lib/interface'; import CVATTooltip from 'components/common/cvat-tooltip'; -import { getCore } from 'cvat-core-wrapper'; -import { JobStage } from 'reducers'; +import { getCore, JobStage } from 'cvat-core-wrapper'; const core = getCore(); @@ -213,7 +212,7 @@ function AnnotationMenuComponent(props: Props & RouteComponentProps): JSX.Elemen {JobState.COMPLETED} - {[JobStage.ANNOTATION, JobStage.REVIEW].includes(jobStage) ? + {[JobStage.ANNOTATION, JobStage.VALIDATION].includes(jobStage) ? Finish the job : null} {jobStage === JobStage.ACCEPTANCE ? Renew the job : null} diff --git a/cvat-ui/src/components/job-item/job-actions-menu.tsx b/cvat-ui/src/components/job-item/job-actions-menu.tsx index e7911dd05541..ed5646f3038a 100644 --- a/cvat-ui/src/components/job-item/job-actions-menu.tsx +++ b/cvat-ui/src/components/job-item/job-actions-menu.tsx @@ -1,6 +1,7 @@ // Copyright (C) 2023 CVAT.ai Corporation // // SPDX-License-Identifier: MIT + import React, { useCallback } from 'react'; import { useDispatch } from 'react-redux'; import { useHistory } from 'react-router'; @@ -15,13 +16,12 @@ import { } from 'cvat-core-wrapper'; import { deleteJobAsync } from 'actions/jobs-actions'; import { importActions } from 'actions/import-actions'; -import { updateJobAsync } from 'actions/tasks-actions'; const core = getCore(); interface Props { job: Job; - onJobUpdate?: (job: Job) => void; + onJobUpdate: (job: Job) => void; } function JobActionsMenu(props: Props): JSX.Element { @@ -62,19 +62,11 @@ function JobActionsMenu(props: Props): JSX.Element { } else if (action.key === 'renew_job') { job.state = core.enums.JobState.NEW; job.stage = JobStage.ANNOTATION; - if (onJobUpdate) { - onJobUpdate(job); - } else { - dispatch(updateJobAsync(job)); - } + onJobUpdate(job); } else if (action.key === 'finish_job') { job.stage = JobStage.ACCEPTANCE; job.state = core.enums.JobState.COMPLETED; - if (onJobUpdate) { - onJobUpdate(job); - } else { - dispatch(updateJobAsync(job)); - } + onJobUpdate(job); } }} > diff --git a/cvat-ui/src/components/job-item/job-item.tsx b/cvat-ui/src/components/job-item/job-item.tsx index 614d058d3426..312e65aa2b56 100644 --- a/cvat-ui/src/components/job-item/job-item.tsx +++ b/cvat-ui/src/components/job-item/job-item.tsx @@ -30,8 +30,8 @@ import CVATTooltip from 'components/common/cvat-tooltip'; import JobActionsMenu from './job-actions-menu'; interface Props { - job: Job, - task: Task, + job: Job; + task: Task; onJobUpdate: (job: Job) => void; } diff --git a/cvat-ui/src/components/jobs-page/job-card.tsx b/cvat-ui/src/components/jobs-page/job-card.tsx index 112662aa6706..7177a33e2858 100644 --- a/cvat-ui/src/components/jobs-page/job-card.tsx +++ b/cvat-ui/src/components/jobs-page/job-card.tsx @@ -1,5 +1,5 @@ // Copyright (C) 2022 Intel Corporation -// Copyright (C) 2022 CVAT.ai Corporation +// Copyright (C) 2022-2023 CVAT.ai Corporation // // SPDX-License-Identifier: MIT @@ -9,6 +9,8 @@ import Card from 'antd/lib/card'; import Descriptions from 'antd/lib/descriptions'; import { MoreOutlined } from '@ant-design/icons'; import Dropdown from 'antd/lib/dropdown'; + +import { Job } from 'cvat-core-wrapper'; import { useCardHeightHOC } from 'utils/hooks'; import Preview from 'components/common/preview'; import JobActionsMenu from 'components/job-item/job-actions-menu'; @@ -22,11 +24,12 @@ const useCardHeight = useCardHeightHOC({ }); interface Props { - job: any; + job: Job; + onJobUpdate: (job: Job) => void; } function JobCardComponent(props: Props): JSX.Element { - const { job } = props; + const { job, onJobUpdate } = props; const [expanded, setExpanded] = useState(false); const history = useHistory(); const height = useCardHeight(); @@ -73,7 +76,7 @@ function JobCardComponent(props: Props): JSX.Element { {job.assignee.username} ) : null} - }> + }> diff --git a/cvat-ui/src/components/jobs-page/jobs-content.tsx b/cvat-ui/src/components/jobs-page/jobs-content.tsx index db34eece8cfd..e9a4e266dab3 100644 --- a/cvat-ui/src/components/jobs-page/jobs-content.tsx +++ b/cvat-ui/src/components/jobs-page/jobs-content.tsx @@ -1,4 +1,5 @@ // Copyright (C) 2022 Intel Corporation +// Copyright (C) 2023 CVAT.ai Corporation // // SPDX-License-Identifier: MIT @@ -9,7 +10,12 @@ import { CombinedState } from 'reducers'; import { Job, JobType } from 'cvat-core-wrapper'; import JobCard from './job-card'; -function JobsContentComponent(): JSX.Element { +interface Props { + onJobUpdate(job: Job): void; +} + +function JobsContentComponent(props: Props): JSX.Element { + const { onJobUpdate } = props; const jobs = useSelector((state: CombinedState) => state.jobs.current); const dimensions = { md: 22, @@ -22,7 +28,7 @@ function JobsContentComponent(): JSX.Element { {jobs.filter((job: Job) => job.type === JobType.ANNOTATION).map((job: Job): JSX.Element => ( - + ))} diff --git a/cvat-ui/src/components/jobs-page/jobs-page.tsx b/cvat-ui/src/components/jobs-page/jobs-page.tsx index 0a6dea86241e..899075163d38 100644 --- a/cvat-ui/src/components/jobs-page/jobs-page.tsx +++ b/cvat-ui/src/components/jobs-page/jobs-page.tsx @@ -1,9 +1,10 @@ // Copyright (C) 2022 Intel Corporation +// Copyright (C) 2023 CVAT.ai Corporation // // SPDX-License-Identifier: MIT import './styles.scss'; -import React, { useEffect, useState } from 'react'; +import React, { useCallback, useEffect, useState } from 'react'; import { useHistory } from 'react-router'; import { useDispatch, useSelector } from 'react-redux'; import Spin from 'antd/lib/spin'; @@ -12,9 +13,10 @@ import Pagination from 'antd/lib/pagination'; import Empty from 'antd/lib/empty'; import Text from 'antd/lib/typography/Text'; +import { Job } from 'cvat-core-wrapper'; import { updateHistoryFromQuery } from 'components/resource-sorting-filtering'; import { CombinedState, Indexable } from 'reducers'; -import { getJobsAsync } from 'actions/jobs-actions'; +import { getJobsAsync, updateJobAsync } from 'actions/jobs-actions'; import TopBarComponent from './top-bar'; import JobsContentComponent from './jobs-content'; @@ -26,6 +28,9 @@ function JobsPageComponent(): JSX.Element { const query = useSelector((state: CombinedState) => state.jobs.query); const fetching = useSelector((state: CombinedState) => state.jobs.fetching); const count = useSelector((state: CombinedState) => state.jobs.count); + const onJobUpdate = useCallback((job: Job) => { + dispatch(updateJobAsync(job)); + }, []); const queryParams = new URLSearchParams(history.location.search); const updatedQuery = { ...query }; @@ -51,7 +56,7 @@ function JobsPageComponent(): JSX.Element { const content = count ? ( <> - + void; - showImportModal: (jobInstance: any) => void; + showExportModal: (jobInstance: Job) => void; + showImportModal: (jobInstance: Job) => void; removeAnnotations(startnumber: number, endnumber: number, delTrackKeyframesOnly: boolean): void; setForceExitAnnotationFlag(forceExit: boolean): void; - saveAnnotations(jobInstance: any, afterSave?: () => void): void; - updateJob(jobInstance: any): void; + saveAnnotations(jobInstance: Job, afterSave?: () => void): void; + updateJob(jobInstance: Job): Promise; } function mapStateToProps(state: CombinedState): StateToProps { @@ -55,10 +58,10 @@ function mapStateToProps(state: CombinedState): StateToProps { function mapDispatchToProps(dispatch: any): DispatchToProps { return { - showExportModal(jobInstance: any): void { + showExportModal(jobInstance: Job): void { dispatch(exportActions.openExportDatasetModal(jobInstance)); }, - showImportModal(jobInstance: any): void { + showImportModal(jobInstance: Job): void { dispatch(importActions.openImportDatasetModal(jobInstance)); }, removeAnnotations(startnumber: number, endnumber: number, delTrackKeyframesOnly:boolean) { @@ -67,11 +70,11 @@ function mapDispatchToProps(dispatch: any): DispatchToProps { setForceExitAnnotationFlag(forceExit: boolean): void { dispatch(setForceExitAnnotationFlagAction(forceExit)); }, - saveAnnotations(jobInstance: any, afterSave?: () => void): void { + saveAnnotations(jobInstance: Job, afterSave?: () => void): void { dispatch(saveAnnotationsAsync(jobInstance, afterSave)); }, - updateJob(jobInstance: any): void { - dispatch(updateJobAsync(jobInstance)); + updateJob(jobInstance: Job): Promise { + return dispatch(updateJobAsync(jobInstance)); }, }; } @@ -98,19 +101,28 @@ function AnnotationMenuContainer(props: Props): JSX.Element { } else if (action === Actions.RENEW_JOB) { jobInstance.state = core.enums.JobState.NEW; jobInstance.stage = JobStage.ANNOTATION; - updateJob(jobInstance); - window.location.reload(); + updateJob(jobInstance).then((success) => { + if (success) { + message.info('Job renewed', 2); + } + }); } else if (action === Actions.FINISH_JOB) { jobInstance.stage = JobStage.ACCEPTANCE; jobInstance.state = core.enums.JobState.COMPLETED; - updateJob(jobInstance); - history.push(`/tasks/${jobInstance.taskId}`); + updateJob(jobInstance).then((success) => { + if (success) { + history.push(`/tasks/${jobInstance.taskId}`); + } + }); } else if (action === Actions.OPEN_TASK) { history.push(`/tasks/${jobInstance.taskId}`); } else if (action.startsWith('state:')) { - [, jobInstance.state] = action.split(':'); - updateJob(jobInstance); - window.location.reload(); + [, jobInstance.state] = action.split(':') as [string, JobState]; + updateJob(jobInstance).then((success) => { + if (success) { + message.info('Job state updated', 2); + } + }); } else if (action === Actions.LOAD_JOB_ANNO) { showImportModal(jobInstance); } diff --git a/cvat-ui/src/reducers/annotation-reducer.ts b/cvat-ui/src/reducers/annotation-reducer.ts index d7d395adb6f1..ebe4c833d8da 100644 --- a/cvat-ui/src/reducers/annotation-reducer.ts +++ b/cvat-ui/src/reducers/annotation-reducer.ts @@ -5,11 +5,12 @@ import { AnyAction } from 'redux'; import { AnnotationActionTypes } from 'actions/annotation-actions'; +import { JobsActionTypes } from 'actions/jobs-actions'; import { AuthActionTypes } from 'actions/auth-actions'; import { BoundariesActionTypes } from 'actions/boundaries-actions'; import { Canvas, CanvasMode } from 'cvat-canvas-wrapper'; import { Canvas3d } from 'cvat-canvas3d-wrapper'; -import { DimensionType } from 'cvat-core-wrapper'; +import { DimensionType, JobStage } from 'cvat-core-wrapper'; import { clamp } from 'utils/math'; import { SettingsActionTypes } from 'actions/settings-actions'; @@ -17,7 +18,6 @@ import { ActiveControl, AnnotationState, ContextMenuType, - JobStage, ObjectType, ShapeType, Workspace, @@ -158,7 +158,7 @@ export default (state = defaultState, action: AnyAction): AnnotationState => { groundTruthJobFramesMeta, } = action.payload; - const isReview = job.stage === JobStage.REVIEW; + const isReview = job.stage === JobStage.VALIDATION; let workspaceSelected = Workspace.STANDARD; const defaultLabel = job.labels.length ? job.labels[0] : null; @@ -237,6 +237,15 @@ export default (state = defaultState, action: AnyAction): AnnotationState => { }, }; } + case JobsActionTypes.UPDATE_JOB_SUCCESS: { + return { + ...state, + job: { + ...state.job, + instance: action.payload.job, + }, + }; + } case AnnotationActionTypes.GET_DATA_FAILED: { return { ...state, diff --git a/cvat-ui/src/reducers/index.ts b/cvat-ui/src/reducers/index.ts index e542c31e57b6..ea91619f8aa3 100644 --- a/cvat-ui/src/reducers/index.ts +++ b/cvat-ui/src/reducers/index.ts @@ -375,12 +375,6 @@ export enum TaskStatus { COMPLETED = 'completed', } -export enum JobStage { - ANNOTATION = 'annotation', - REVIEW = 'validation', - ACCEPTANCE = 'acceptance', -} - export interface ActiveInference { status: RQStatus; progress: number; diff --git a/cvat-ui/src/reducers/jobs-reducer.ts b/cvat-ui/src/reducers/jobs-reducer.ts index 5be1f05ddc70..c7b07fc1fa30 100644 --- a/cvat-ui/src/reducers/jobs-reducer.ts +++ b/cvat-ui/src/reducers/jobs-reducer.ts @@ -135,6 +135,32 @@ export default (state: JobsState = defaultState, action: JobsActions): JobsState }, }; } + case JobsActionTypes.UPDATE_JOB: { + return { + ...state, + fetching: true, + }; + } + case JobsActionTypes.UPDATE_JOB_SUCCESS: { + return { + ...state, + current: state.current.includes(action.payload.job) ? ( + state.current.map((job) => { + if (job === action.payload.job) { + return action.payload.job; + } + return job; + }) + ) : state.current, + fetching: false, + }; + } + case JobsActionTypes.UPDATE_JOB_FAILED: { + return { + ...state, + fetching: false, + }; + } default: { return state; } diff --git a/cvat-ui/src/reducers/notifications-reducer.ts b/cvat-ui/src/reducers/notifications-reducer.ts index 727ccd140f54..71e3ed368bce 100644 --- a/cvat-ui/src/reducers/notifications-reducer.ts +++ b/cvat-ui/src/reducers/notifications-reducer.ts @@ -1638,6 +1638,22 @@ export default function (state = defaultState, action: AnyAction): Notifications }, }; } + case JobsActionTypes.UPDATE_JOB_FAILED: { + return { + ...state, + errors: { + ...state.errors, + jobs: { + ...state.errors.jobs, + updating: { + message: 'Could not update job', + reason: action.payload.error.toString(), + className: 'cvat-notification-notice-update-job-failed', + }, + }, + }, + }; + } case JobsActionTypes.DELETE_JOB_FAILED: { const { jobID } = action.payload; return { From 657e361227e8c2072b74af6821f12909a158a174 Mon Sep 17 00:00:00 2001 From: Boris Sekachev Date: Fri, 15 Sep 2023 16:56:21 +0300 Subject: [PATCH 3/9] [Refactoring] Removed custom exif rotation method (#6835) --- cvat/apps/engine/frame_provider.py | 5 +- cvat/apps/engine/media_extractors.py | 80 ++++++++++++++-------------- 2 files changed, 41 insertions(+), 44 deletions(-) diff --git a/cvat/apps/engine/frame_provider.py b/cvat/apps/engine/frame_provider.py index d37cedd27c57..eaa3ca6d848a 100644 --- a/cvat/apps/engine/frame_provider.py +++ b/cvat/apps/engine/frame_provider.py @@ -10,13 +10,12 @@ import cv2 import numpy as np -from PIL import Image +from PIL import Image, ImageOps from cvat.apps.engine.cache import MediaCache from cvat.apps.engine.media_extractors import VideoReader, ZipReader from cvat.apps.engine.mime_types import mimetypes from cvat.apps.engine.models import DataChoice, StorageMethodChoice, DimensionType -from cvat.apps.engine.media_extractors import rotate_within_exif from rest_framework.exceptions import ValidationError class RandomAccessIterator: @@ -175,7 +174,7 @@ def get_preview(self, frame_number): else: preview, _ = self.get_frame(frame_number, self.Quality.COMPRESSED, self.Type.PIL) - preview = rotate_within_exif(preview) + preview = ImageOps.exif_transpose(preview) preview.thumbnail(PREVIEW_SIZE) output_buf = BytesIO() diff --git a/cvat/apps/engine/media_extractors.py b/cvat/apps/engine/media_extractors.py index c81efc82b145..0db53e6c9f0a 100644 --- a/cvat/apps/engine/media_extractors.py +++ b/cvat/apps/engine/media_extractors.py @@ -83,22 +83,6 @@ def image_size_within_orientation(img: Image): def has_exif_rotation(img: Image): return img.getexif().get(ORIENTATION_EXIF_TAG, ORIENTATION.NORMAL_HORIZONTAL) != ORIENTATION.NORMAL_HORIZONTAL -def rotate_within_exif(img: Image): - orientation = img.getexif().get(ORIENTATION_EXIF_TAG, ORIENTATION.NORMAL_HORIZONTAL) - if orientation in [ORIENTATION.NORMAL_180_ROTATED, ORIENTATION.MIRROR_VERTICAL]: - img = img.rotate(180, expand=True) - elif orientation in [ORIENTATION.NORMAL_270_ROTATED, ORIENTATION.MIRROR_HORIZONTAL_90_ROTATED]: - img = img.rotate(90, expand=True) - elif orientation in [ORIENTATION.NORMAL_90_ROTATED, ORIENTATION.MIRROR_HORIZONTAL_270_ROTATED]: - img = img.rotate(270, expand=True) - if orientation in [ - ORIENTATION.MIRROR_HORIZONTAL, ORIENTATION.MIRROR_VERTICAL, - ORIENTATION.MIRROR_HORIZONTAL_270_ROTATED ,ORIENTATION.MIRROR_HORIZONTAL_90_ROTATED, - ]: - img = img.transpose(Image.FLIP_LEFT_RIGHT) - - return img - class IMediaReader(ABC): def __init__(self, source_path, step, start, stop, dimension): self._source_path = source_path @@ -127,7 +111,7 @@ def _get_preview(obj): preview = Image.open(obj) else: preview = obj - preview = rotate_within_exif(preview) + preview = ImageOps.exif_transpose(preview) # TODO - Check if the other formats work. I'm only interested in I;16 for now. Sorry @:-| # Summary: # Images in the Format I;16 definitely don't work. Most likely I;16B/L/N won't work as well. @@ -227,8 +211,8 @@ def get_image_size(self, i): with open(self.get_path(i), 'rb') as f: properties = ValidateDimension.get_pcd_properties(f) return int(properties["WIDTH"]), int(properties["HEIGHT"]) - img = Image.open(self._source_path[i]) - return image_size_within_orientation(img) + with Image.open(self._source_path[i]) as img: + return image_size_within_orientation(img) def reconcile(self, source_files, step=1, start=0, stop=None, dimension=DimensionType.DIM_2D, sorting_method=None): # FIXME @@ -369,8 +353,8 @@ def get_image_size(self, i): with open(self.get_path(i), 'rb') as f: properties = ValidateDimension.get_pcd_properties(f) return int(properties["WIDTH"]), int(properties["HEIGHT"]) - img = Image.open(io.BytesIO(self._zip_source.read(self._source_path[i]))) - return image_size_within_orientation(img) + with Image.open(io.BytesIO(self._zip_source.read(self._source_path[i]))) as img: + return image_size_within_orientation(img) def get_image(self, i): if self._dimension == DimensionType.DIM_3D: @@ -604,8 +588,12 @@ def __init__(self, quality, dimension=DimensionType.DIM_2D): @staticmethod def _compress_image(image_path, quality): - image = image_path.to_image() if isinstance(image_path, av.VideoFrame) else Image.open(image_path) - image = rotate_within_exif(image) + if isinstance(image_path, av.VideoFrame): + image = image_path.to_image() + else: + with Image.open(image_path) as source_image: + image = ImageOps.exif_transpose(source_image) + # Ensure image data fits into 8bit per pixel before RGB conversion as PIL clips values on conversion if image.mode == "I": # Image mode is 32bit integer pixels. @@ -632,12 +620,14 @@ def _compress_image(image_path, quality): converted_image = image.convert('RGB') image.close() - buf = io.BytesIO() - converted_image.save(buf, format='JPEG', quality=quality, optimize=True) - buf.seek(0) - width, height = converted_image.size - converted_image.close() - return width, height, buf + try: + buf = io.BytesIO() + converted_image.save(buf, format='JPEG', quality=quality, optimize=True) + buf.seek(0) + width, height = converted_image.size + return width, height, buf + finally: + converted_image.close() @abstractmethod def save_as_chunk(self, images, chunk_path): @@ -664,17 +654,25 @@ def save_as_chunk(self, images, chunk_path): ext = os.path.splitext(path)[1].replace('.', '') output = io.BytesIO() if self._dimension == DimensionType.DIM_2D: - pil_image = Image.open(image) - if has_exif_rotation(pil_image): - rot_image = rotate_within_exif(pil_image) - if rot_image.format == 'TIFF': - # https://pillow.readthedocs.io/en/stable/handbook/image-file-formats.html - # use loseless lzw compression for tiff images - rot_image.save(output, format='TIFF', compression='tiff_lzw') + with Image.open(image) as pil_image: + if has_exif_rotation(pil_image): + rot_image = ImageOps.exif_transpose(pil_image) + try: + if rot_image.format == 'TIFF': + # https://pillow.readthedocs.io/en/stable/handbook/image-file-formats.html + # use loseless lzw compression for tiff images + rot_image.save(output, format='TIFF', compression='tiff_lzw') + else: + rot_image.save( + output, + format=rot_image.format if rot_image.format else self.IMAGE_EXT, + quality=100, + subsampling=0 + ) + finally: + rot_image.close() else: - rot_image.save(output, format=rot_image.format if rot_image.format else self.IMAGE_EXT, quality=100, subsampling=0) - else: - output = image + output = image else: output, ext = self._write_pcd_file(image)[0:2] arcname = '{:06d}.{}'.format(idx, ext) @@ -700,8 +698,8 @@ def save_as_chunk( else: assert isinstance(image, io.IOBase) image_buf = io.BytesIO(image.read()) - w, h = Image.open(image_buf).size - + with Image.open(image_buf) as img: + w, h = img.size extension = self.IMAGE_EXT else: image_buf, extension, w, h = self._write_pcd_file(image) From 26693dda9d7fc6f201d1c06c0e26fe95852dbd26 Mon Sep 17 00:00:00 2001 From: Andrey Zhavoronkov Date: Thu, 21 Sep 2023 18:40:41 +0300 Subject: [PATCH 4/9] =?UTF-8?q?Do=20not=20copy=20extra=20files=20if=20both?= =?UTF-8?q?=20server=5Ffiles=20and=20job=5Ffile=5Fmapping=20are=E2=80=A6?= =?UTF-8?q?=20(#6879)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .github/workflows/main.yml | 2 +- CHANGELOG.md | 3 +- cvat/apps/engine/serializers.py | 27 ++++-- cvat/apps/engine/task.py | 9 ++ cvat/schema.yml | 28 ++++-- tests/package.json | 2 +- tests/yarn.lock | 163 ++++++++++++++++++++++++-------- 7 files changed, 180 insertions(+), 54 deletions(-) diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml index 7d0651c3dc0d..396681dbec08 100644 --- a/.github/workflows/main.yml +++ b/.github/workflows/main.yml @@ -279,7 +279,7 @@ jobs: - uses: actions/setup-node@v3 with: - node-version: '16.x' + node-version: '18.x' - name: Download CVAT server image uses: actions/download-artifact@v3 diff --git a/CHANGELOG.md b/CHANGELOG.md index 8f2d8faba22e..196fd36a0e8c 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -19,7 +19,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 - TDB ### Fixed -- TDB +- Downloading additional data from cloud storage if use_cache=true and job_file_mapping are specified + () ### Security - TDB diff --git a/cvat/apps/engine/serializers.py b/cvat/apps/engine/serializers.py index 74a2c76460e4..d29c98f49129 100644 --- a/cvat/apps/engine/serializers.py +++ b/cvat/apps/engine/serializers.py @@ -791,12 +791,18 @@ def __init__(self, *args, **kwargs): class JobFileMapping(serializers.ListField): """ - Represents a file-to-job mapping. Useful to specify a custom job - configuration during task creation. This option is not compatible with - most other job split-related options. Files in the jobs must not overlap or repeat. + Represents a file-to-job mapping. + Useful to specify a custom job configuration during task creation. + This option is not compatible with most other job split-related options. + Files in the jobs must not overlap or repeat. + Job file mapping files must be a subset of the input files. + If directories are specified in server_files, all files obtained by recursive search + in the specified directories will be used as input files. + In case of missing items in the input files, an error will be raised. Example: [ + ["file1.jpg", "file2.jpg"], # job #1 files ["file3.png"], # job #2 files ["file4.jpg", "file5.png", "file6.bmp"], # job #3 files @@ -824,9 +830,15 @@ class DataSerializer(serializers.ModelSerializer): When false, video chunks are represented as video segments """)) client_files = ClientFileSerializer(many=True, default=[], - help_text="Uploaded files") + help_text=textwrap.dedent(""" + Uploaded files. + Must contain all files from job_file_mapping if job_file_mapping is not empty. + """)) server_files = ServerFileSerializer(many=True, default=[], - help_text="Paths to files from a file share mounted on the server, or from a cloud storage") + help_text=textwrap.dedent(""" + Paths to files from a file share mounted on the server, or from a cloud storage. + Must contain all files from job_file_mapping if job_file_mapping is not empty. + """)) server_files_exclude = serializers.ListField(required=False, default=[], child=serializers.CharField(max_length=1024), help_text=textwrap.dedent("""\ @@ -845,7 +857,10 @@ class DataSerializer(serializers.ModelSerializer): """) ) remote_files = RemoteFileSerializer(many=True, default=[], - help_text="Direct download URLs for files") + help_text=textwrap.dedent(""" + Direct download URLs for files. + Must contain all files from job_file_mapping if job_file_mapping is not empty. + """)) use_cache = serializers.BooleanField(default=False, help_text=textwrap.dedent("""\ Enable or disable task data chunk caching for the task. diff --git a/cvat/apps/engine/task.py b/cvat/apps/engine/task.py index 14692f5a7ed7..98c35de7568f 100644 --- a/cvat/apps/engine/task.py +++ b/cvat/apps/engine/task.py @@ -623,6 +623,15 @@ def _create_thread( data['server_files'].extend(additional_files) + # We only need to process the files specified in job_file_mapping + if job_file_mapping is not None: + filtered_files = [] + for f in itertools.chain.from_iterable(job_file_mapping): + if f not in data['server_files']: + raise ValidationError(f"Job mapping file {f} is not specified in input files") + filtered_files.append(f) + data['server_files'] = filtered_files + if db_data.storage_method == models.StorageMethodChoice.FILE_SYSTEM or not settings.USE_CACHE: _download_data_from_cloud_storage(db_data.cloud_storage, data['server_files'], upload_dir) is_data_in_cloud = False diff --git a/cvat/schema.yml b/cvat/schema.yml index b5952374b922..19dfcc4b2535 100644 --- a/cvat/schema.yml +++ b/cvat/schema.yml @@ -6733,7 +6733,10 @@ components: type: string format: binary default: [] - description: Uploaded files + description: |2 + + Uploaded files. + Must contain all files from job_file_mapping if job_file_mapping is not empty. server_files: type: array items: @@ -6741,8 +6744,10 @@ components: minLength: 1 maxLength: 1024 default: [] - description: Paths to files from a file share mounted on the server, or - from a cloud storage + description: |2 + + Paths to files from a file share mounted on the server, or from a cloud storage. + Must contain all files from job_file_mapping if job_file_mapping is not empty. remote_files: type: array items: @@ -6750,7 +6755,10 @@ components: minLength: 1 maxLength: 1024 default: [] - description: Direct download URLs for files + description: |2 + + Direct download URLs for files. + Must contain all files from job_file_mapping if job_file_mapping is not empty. use_zip_chunks: type: boolean default: false @@ -6825,12 +6833,18 @@ components: writeOnly: true description: |2 - Represents a file-to-job mapping. Useful to specify a custom job - configuration during task creation. This option is not compatible with - most other job split-related options. Files in the jobs must not overlap or repeat. + Represents a file-to-job mapping. + Useful to specify a custom job configuration during task creation. + This option is not compatible with most other job split-related options. + Files in the jobs must not overlap or repeat. + Job file mapping files must be a subset of the input files. + If directories are specified in server_files, all files obtained by recursive search + in the specified directories will be used as input files. + In case of missing items in the input files, an error will be raised. Example: [ + ["file1.jpg", "file2.jpg"], # job #1 files ["file3.png"], # job #2 files ["file4.jpg", "file5.png", "file6.bmp"], # job #3 files diff --git a/tests/package.json b/tests/package.json index 29586a06329e..5d037c1189d5 100644 --- a/tests/package.json +++ b/tests/package.json @@ -8,7 +8,7 @@ "@cypress/code-coverage": "^3.9.10", "archiver": "^5.3.0", "cy-verify-downloads": "^0.0.5", - "cypress": "^12.5.1", + "cypress": "^12.17.4", "cypress-file-upload": "^5.0.8", "cypress-localstorage-commands": "^1.7.0", "cypress-real-events": "^1.6.0", diff --git a/tests/yarn.lock b/tests/yarn.lock index 5dbecc67369b..63eb1616ce65 100644 --- a/tests/yarn.lock +++ b/tests/yarn.lock @@ -209,10 +209,10 @@ js-yaml "3.14.1" nyc "15.1.0" -"@cypress/request@^2.88.10": - version "2.88.10" - resolved "https://registry.npmjs.org/@cypress/request/-/request-2.88.10.tgz" - integrity sha512-Zp7F+R93N0yZyG34GutyTNr+okam7s/Fzc1+i3kcqOP8vk6OuajuE9qZJ6Rs+10/1JFtXFYMdyarnU1rZuJesg== +"@cypress/request@2.88.12": + version "2.88.12" + resolved "https://registry.yarnpkg.com/@cypress/request/-/request-2.88.12.tgz#ba4911431738494a85e93fb04498cb38bc55d590" + integrity sha512-tOn+0mDZxASFM+cuAP9szGUGPI1HwWVSvdzm7V4cCsPdFTx6qMj29CwaQmRAMIEhORIUBFBsYROYJcveK4uOjA== dependencies: aws-sign2 "~0.7.0" aws4 "^1.8.0" @@ -227,9 +227,9 @@ json-stringify-safe "~5.0.1" mime-types "~2.1.19" performance-now "^2.1.0" - qs "~6.5.2" + qs "~6.10.3" safe-buffer "^5.1.2" - tough-cookie "~2.5.0" + tough-cookie "^4.1.3" tunnel-agent "^0.6.0" uuid "^8.3.2" @@ -589,7 +589,7 @@ resolved "https://registry.yarnpkg.com/@tokenizer/token/-/token-0.3.0.tgz#fe98a93fe789247e998c75e74e9c7c63217aa276" integrity sha512-OvjF+z51L3ov0OyAU0duzsYuvO01PH7x4t6DJx+guahgTnBHkhJdG7soQeTSFLWN3efnHyibZ4Z8l2EuWwJN3A== -"@types/node@*", "@types/node@^14.14.31": +"@types/node@*": version "14.18.21" resolved "https://registry.npmjs.org/@types/node/-/node-14.18.21.tgz" integrity sha512-x5W9s+8P4XteaxT/jKF0PSb7XEvo5VmqEWgsMlyeY4ZlLK8I6aH6g5TPPyDlLAep+GYf4kefb7HFyc7PAO3m+Q== @@ -599,6 +599,11 @@ resolved "https://registry.npmjs.org/@types/node/-/node-16.9.1.tgz" integrity sha512-QpLcX9ZSsq3YYUUnD3nFDY8H7wctAhQj/TFKL8Ya8v5fMm3CFXxo8zStsLAl780ltoYoo1WvKUVGBQK+1ifr7g== +"@types/node@^16.18.39": + version "16.18.53" + resolved "https://registry.yarnpkg.com/@types/node/-/node-16.18.53.tgz#21820fe4d5968aaf8071dabd1ee13d24ada1350a" + integrity sha512-vVmHeo4tpF8zsknALU90Hh24VueYdu45ZlXzYWFbom61YR4avJqTFDC3QlWzjuTdAv6/3xHaxiO9NrtVZXrkmw== + "@types/sinonjs__fake-timers@8.1.1": version "8.1.1" resolved "https://registry.npmjs.org/@types/sinonjs__fake-timers/-/sinonjs__fake-timers-8.1.1.tgz" @@ -871,6 +876,14 @@ caching-transform@^4.0.0: package-hash "^4.0.0" write-file-atomic "^3.0.0" +call-bind@^1.0.0: + version "1.0.2" + resolved "https://registry.yarnpkg.com/call-bind/-/call-bind-1.0.2.tgz#b1d4e89e688119c3c9a903ad30abb2f6a919be3c" + integrity sha512-7O+FbCihrB5WGbFYesctwmTKae6rOiIzmz1icreWJ+0aA7LJfuqhEso2T9ncpcFtzMQtzXf2QGGueWJGTYsqrA== + dependencies: + function-bind "^1.1.1" + get-intrinsic "^1.0.2" + camelcase@^5.0.0, camelcase@^5.3.1: version "5.3.1" resolved "https://registry.npmjs.org/camelcase/-/camelcase-5.3.1.tgz" @@ -987,10 +1000,10 @@ combined-stream@^1.0.6, combined-stream@~1.0.6: dependencies: delayed-stream "~1.0.0" -commander@^5.1.0: - 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-- [CVAT](format-cvat) -- [Datumaro](format-datumaro) -- [LabelMe](format-labelme) -- [MOT](format-mot) -- [MOTS](format-mots) -- [COCO](format-coco) -- [PASCAL VOC and mask](format-voc) -- [YOLO](format-yolo) -- [TF detection API](format-tfrecord) -- [ImageNet](format-imagenet) -- [CamVid](format-camvid) -- [WIDER Face](format-widerface) -- [VGGFace2](format-vggface2) -- [Market-1501](format-market1501) -- [ICDAR13/15](format-icdar) -- [Open Images](format-openimages) -- [Cityscapes](format-cityscapes) -- [KITTI](format-kitti) -- [LFW](format-lfw) +In CVAT, you have the option to export data in various formats. +The choice of export format depends on the type of annotation as +well as the intended future use of the dataset. + +See: + +- [Data export formats](#data-export-formats) +- [Exporting dataset in CVAT](#exporting-dataset-in-cvat) + - [Exporting dataset from Task](#exporting-dataset-from-task) + - [Exporting dataset from Job](#exporting-dataset-from-job) +- [Data export video tutorial](#data-export-video-tutorial) + +## Data export formats + +The table below outlines the available formats for data export in CVAT. + + + +| Format | Type | Annotation Type | Models | Shapes | Attributes | Video Tracks | +| ----------------------------------------------------------------------------------------------------------------------------------- | ------------- | ----------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------- | -------------------- | ------------- | +| [CamVid 1.0](format-camvid) | .txt
.png | Semantic
Segmentation | U-Net, SegNet, DeepLab,
PSPNet, FCN, Mask R-CNN,
ICNet, ERFNet, HRNet,
V-Net, and others. | Polygons | Not supported | Not supported | +| [Cityscapes 1.0](format-cityscapes) | .txt
.png | Semantic
Segmentation | U-Net, SegNet, DeepLab,
PSPNet, FCN, ERFNet,
ICNet, Mask R-CNN, HRNet,
ENet, and others. | Polygons | Specific attributes | Not supported | +| [COCO 1.0](format-coco) | JSON | Detection, Semantic
Segmentation | YOLO (You Only Look Once),
Faster R-CNN, Mask R-CNN, SSD (Single Shot MultiBox Detector),
RetinaNet, EfficientDet, UNet,
DeepLabv3+, CenterNet, Cascade R-CNN, and others. | Bounding Boxes, Polygons | Specific attributes | Not supported | +| [COCO Keypoings 1.0](coco-keypoints) | .xml | Keypoints | OpenPose, PoseNet, AlphaPose,
SPM (Single Person Model),
Mask R-CNN with Keypoint Detection:, and others. | Skeletons | Specific attributes | Not supported | +| [CVAT for images 1.1](/docs/manual/advanced/formats/format-cvat/#cvat-for-videos-export) | .xml | Universal format
for all types of
annotations. | Universal format
for all types of
models. | Bounding Boxes, Polygons,
Polylines, Points, Cuboids,
Skeletons, Tags. | All attributes | Not supported | +| [CVAT for video 1.1](/docs/manual/advanced/formats/format-cvat/#cvat-for-videos-export) | .xml | Universal format
for all types of
annotations. | Universal format
for all types of
annotations. | Bounding Boxes, Polygons,
Polylines, Points, Cuboids,
Skeletons, Tags, Tracks. | All attributes | Supported | +| [Datumaro 1.0](format-datumaro) | JSON | Universal format
for all types of
annotations. | Universal format
for all types of
models. | Bounding Boxes, Polygons,
Polylines, Points, Cuboids,
Skeletons, Tags, Tracks. | All attributes | Supported | +| [ICDAR](format-icdar)
Includes ICDAR Recognition 1.0,
ICDAR Detection 1.0,
and ICDAR Segmentation 1.0
descriptions. | .txt | Text recognition,
Text detection,
Text segmentation | EAST: Efficient and Accurate
Scene Text Detector, CRNN, Mask TextSpotter, TextSnake,
and others. | Tag, Bounding Boxes, Polygons | Specific attributes | Not supported | +| [ImageNet 1.0](format-imagenet) | .jpg
.txt | Semantic Segmentation,
Classification,
Detection | VGG (VGG16, VGG19), Inception, YOLO, Faster R-CNN , U-Net, and others | Tags | No attributes | Not supported | +| [KITTI 1.0](format-kitti) | .txt
.png | Semantic Segmentation, Detection, 3D | PointPillars, SECOND, AVOD, YOLO, DeepSORT, PWC-Net, ORB-SLAM, and others. | Bounding Boxes, Polygons | Specific attributes | Not supported | +| [LabelMe 3.0](format-labelme) | .xml | Compatibility,
Semantic Segmentation | U-Net, Mask R-CNN, Fast R-CNN,
Faster R-CNN, DeepLab, YOLO,
and others. | Bounding Boxes, Polygons | Supported (Polygons) | Not supported | +| [LFW 1.0](format-lfw) | .txt | Verification,
Face recognition | OpenFace, VGGFace & VGGFace2,
FaceNet, ArcFace,
and others. | Tags, Skeletons | Specific attributes | Not supported | +| [Market-1501 1.0](format-market1501) | .txt | Re-identification | Triplet Loss Networks,
Deep ReID models, and others. | Bounding Boxes | Specific attributes | Not supported | +| [MOT 1.0](format-mot) | .txt | Video Tracking,
Detection | SORT, MOT-Net, IOU Tracker,
and others. | Bounding Boxes, Tracks | Specific attributes | Supported | +| [MOTS PNG 1.0](format-mots) | .png
.txt | Video Tracking,
Detection | SORT, MOT-Net, IOU Tracker,
and others. | Bounding Boxes, Tracks, Masks | Specific attributes | Supported | +| [Open Images 1.0](format-openimages) | .csv | Detection,
Classification,
Semantic Segmentaion | Faster R-CNN, YOLO, U-Net,
CornerNet, and others. | Bounding Boxes, Tags, Polygons | Specific attributes | Not supported | +| [PASCAL VOC 1.0](format-voc) | .xml | Classification, Detection | Faster R-CNN, SSD, YOLO,
AlexNet, and others. | Bounding Boxes, Tags, Polygons | Specific attributes | Not supported | +| [Segmentation Mask 1.0](format-smask) | .txt | Semantic Segmentation | Faster R-CNN, SSD, YOLO,
AlexNet, and others. | Polygons | No attributes | Not supported | +| [TFRecord 1.0](format-tfrecord) | .pbtxt | Detection
Classification | SSD, Faster R-CNN, YOLO,
GG16, ResNet, Inception, MobileNet,
and others. | Bounding Boxes, Polygons | No attributes | Not supported | +| [VGGFace2 1.0](format-vggface2) | .csv | Face recognition | VGGFace, ResNet, Inception,
and others. | Bounding Boxes, Points | No attributes | Not supported | +| [WIDER Face 1.0](format-widerface) | .txt | Detection | SSD (Single Shot MultiBox Detector), Faster R-CNN, YOLO,
and others. | Bounding Boxes, Tags | Specific attributes | Not supported | +| [YOLO 1.0](format-yolo) | .txt | Detection | YOLOv1, YOLOv2 (YOLO9000),
YOLOv3, YOLOv4, and others. | Bounding Boxes | No attributes | Not supported | + + + +## Exporting dataset in CVAT + +### Exporting dataset from Task + +To export the dataset from the task, follow these steps: + +1. Open Task. +2. Go to **Actions** > **Export task dataset.** +3. Choose the desired format from the list of available options. + +4. (Optional) Toggle the **Save images** switch if you + wish to include images in the export. + + > **Note**: The **Save images** option is a **paid feature**. + + ![Save images option](/images/export_job_as_dataset_dialog.png) + +5. Input a name for the resulting `.zip` archive. + +6. Click **OK** to initiate the export. + +### Exporting dataset from Job + +To export a dataset from Job follow these steps: + +1. Navigate to **Menu** > **Export job dataset**. + + ![Export dataset](/images/export_job_as_dataset_menu.png) + +2. Choose the desired format from the list of available options. + +3. (Optional) Toggle the **Save images** switch + if you wish to include images in the export. + + > **Note**: The **Save images** option is a **paid feature**. + + ![Save images option](/images/export_job_as_dataset_dialog.png) + +4. Input a name for the resulting `.zip` archive. + +5. Click **OK** to initiate the export. + +## Data export video tutorial + +For more information on the process, see the following tutorial: + + + + + + diff --git a/site/content/en/docs/manual/advanced/formats/coco-keypoints.md b/site/content/en/docs/manual/advanced/formats/coco-keypoints.md new file mode 100644 index 000000000000..922067d3aa92 --- /dev/null +++ b/site/content/en/docs/manual/advanced/formats/coco-keypoints.md @@ -0,0 +1,65 @@ +--- +linkTitle: 'COCO Keypoints' +weight: 5 +--- + +The COCO Keypoints format is designed specifically for human pose estimation tasks, where the objective +is to identify and localize body joints (keypoints) on a human figure within an image. + +This specialized format is used with a variety of state-of-the-art models focused on pose estimation. + +For more information, see: + +- [COCO Keypoint site](https://cocodataset.org/#keypoints-2020) +- [Format specification](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html) +- [Example of the archive](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#import-coco-dataset) + +## COCO Keypoints export + +For export of images: + +- Supported annotations: Skeletons +- Attributes: + - `is_crowd` This can either be a checkbox or an integer + (with values of 0 or 1). It indicates that the instance + (or group of objects) should include an RLE-encoded mask in the `segmentation` field. + All shapes within the group coalesce into a single, overarching mask, + with the largest shape setting the properties for the entire object group. + - `score`: This numerical field represents the annotation `score`. + - Arbitrary attributes: These will be stored within the `attributes` + section of the annotation. +- Tracks: Not supported. + +Downloaded file is a .zip archive with the following structure: + +``` +archive.zip/ +├── images/ +│ +│ ├── +│ ├── +│ └── ... +├──.xml +``` + +## COCO import + +Uploaded file: a single unpacked `*.json` or a zip archive with the structure described +[here](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#import-coco-dataset) +(without images). + +- supported annotations: Skeletons + +`person_keypoints`, + +Support for COCO tasks via Datumaro is described [here](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#export-to-other-formats) +For example, [support for COCO keypoints over Datumaro](https://github.com/openvinotoolkit/cvat/issues/2910#issuecomment-726077582): + +1. Install [Datumaro](https://github.com/openvinotoolkit/datumaro) + `pip install datumaro` +2. Export the task in the `Datumaro` format, unzip +3. Export the Datumaro project in `coco` / `coco_person_keypoints` formats + `datum export -f coco -p path/to/project [-- --save-images]` + +This way, one can export CVAT points as single keypoints or +keypoint lists (without the `visibility` COCO flag). diff --git a/site/content/en/docs/manual/advanced/formats/format-camvid.md b/site/content/en/docs/manual/advanced/formats/format-camvid.md index 301d32b8fcdb..883662001523 100644 --- a/site/content/en/docs/manual/advanced/formats/format-camvid.md +++ b/site/content/en/docs/manual/advanced/formats/format-camvid.md @@ -3,13 +3,25 @@ linkTitle: 'CamVid' weight: 10 --- -# [CamVid](http://mi.eng.cam.ac.uk/research/projects/VideoRec/CamVid/) +The CamVid (Cambridge-driving Labeled Video Database) format is most commonly used +in the realm of semantic segmentation tasks. It is particularly useful for training +and evaluating models for autonomous driving and other vision-based robotics +applications. +For more information, see: + +- [CamVid Specification](http://mi.eng.cam.ac.uk/research/projects/VideoRec/CamVid/) - [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/camvid_dataset) ## CamVid export -Downloaded file: a zip archive of the following structure: +For export of images and videos: + +- Supported annotations: Bounding Boxes, Polygons. +- Attributes: Not supported. +- Tracks: Not supported. + +The downloaded file is a .zip archive with the following structure: ```bash taskname.zip/ @@ -41,14 +53,18 @@ Bicyclist Bridge ``` -Mask is a `png` image with 1 or 3 channels where each pixel -has own color which corresponds to a label. -`(0, 0, 0)` is used for background by default. +A mask in the CamVid dataset is typically a **.png** +image with either one or three channels. + +In this image, each pixel is assigned a specific color +that corresponds to a particular label. -- supported annotations: Rectangles, Polygons +By default, the color `(0, 0, 0)`—or `black`—is used +to represent the background. ## CamVid import -Uploaded file: a zip archive of the structure above +For import of images: +- Uploaded file: a _.zip_ archive of the structure above - supported annotations: Polygons diff --git a/site/content/en/docs/manual/advanced/formats/format-cityscapes.md b/site/content/en/docs/manual/advanced/formats/format-cityscapes.md index 28f51801e694..ae055d2a5ff6 100644 --- a/site/content/en/docs/manual/advanced/formats/format-cityscapes.md +++ b/site/content/en/docs/manual/advanced/formats/format-cityscapes.md @@ -3,23 +3,37 @@ linkTitle: 'Cityscapes' weight: 16 --- -# [Cityscapes](https://www.cityscapes-dataset.com/login/) +The Cityscapes format is a widely-used standard in the field of computer vision, +particularly for tasks involving semantic and instance segmentation in urban scenes. +This dataset format typically comprises high-resolution images of +cityscapes along with detailed pixel-level annotations. -- [Format specification](https://github.com/mcordts/cityscapesScripts#the-cityscapes-dataset) -- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/cityscapes_dataset) +Each pixel is labeled with a category such as "road," "pedestrian," or "vehicle," making +it a valuable resource for training and validating machine learning +models aimed at understanding urban environments. It's a go-to choice +for researchers and professionals working on autonomous vehicles, +robotics, and smart cities. -- Supported annotations +For more information, see: - - Polygons (segmentation task) +- [Cityscapes site](https://www.cityscapes-dataset.com/login/) +- [Cityscapes format specification](https://github.com/mcordts/cityscapesScripts#the-cityscapes-dataset) +- [Cityscapes dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/cityscapes_dataset) -- Supported attributes - - 'is_crowd' (boolean, should be defined for labels as `checkbox` -es) + +# Cityscapes export + +For export of images: + +- Supported annotations: Polygons (segmentation), Bounding Boxes. +- Attributes: + - `is_crowd` boolean, should be defined for labels as `checkbox`. Specifies if the annotation label can distinguish between different instances. If False, the annotation id field encodes the instance id. +- Tracks: Not supported. -# Cityscapes export -Downloaded file: a zip archive of the following structure: +The downloaded file is a .zip archive with the following structure: ``` . diff --git a/site/content/en/docs/manual/advanced/formats/format-coco.md b/site/content/en/docs/manual/advanced/formats/format-coco.md index fc37f8b778d4..e49090baa7a2 100644 --- a/site/content/en/docs/manual/advanced/formats/format-coco.md +++ b/site/content/en/docs/manual/advanced/formats/format-coco.md @@ -1,16 +1,36 @@ --- -linkTitle: 'MS COCO' +linkTitle: 'COCO' weight: 5 --- -# [MS COCO Object Detection](http://cocodataset.org/#format-data) +A widely-used machine learning structure, the COCO dataset is instrumental +for tasks involving object identification and image segmentation. +This format is compatible with projects that employ bounding boxes or +polygonal image annotations. -- [Format specification](https://openvinotoolkit.github.io/datumaro/docs/formats/coco/) +For more information, see: + +- [COCO Object Detection site](http://cocodataset.org/#format-data) +- [Format specification](https://openvinotoolkit.github.io/datumaro/stable/docs/data-formats/formats/coco.html) - [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/coco_dataset) ## COCO export -Downloaded file: a zip archive with the structure described [here](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#import-coco-dataset) +For export of images and videos: + +- Supported annotations: Bounding Boxes, Polygons. +- Attributes: + - `is_crowd` This can either be a checkbox or an integer + (with values of 0 or 1). It indicates that the instance + (or group of objects) should include an RLE-encoded mask in the `segmentation` field. + All shapes within the group coalesce into a single, overarching mask, + with the largest shape setting the properties for the entire object group. + - `score`: This numerical field represents the annotation `score`. + - Arbitrary attributes: These will be stored within the `attributes` + section of the annotation. +- Tracks: Not supported. + +The downloaded file is a .zip archive with the following structure: ``` archive.zip/ @@ -28,69 +48,20 @@ archive.zip/ └── ... ``` -If the dataset is exported from a Project, the subsets are named the same way as they are named -in the project. In other cases there will be a single `default` subset, containing all the data. -The `` part corresponds to one of the COCO tasks: `instances`, `person_keypoints`, -`panoptic`, `image_info`, `labels`, `captions`, `stuff`. There can be several annotation -files in the archive. - -- supported annotations: Polygons, Rectangles -- supported attributes: - - `is_crowd` (checkbox or integer with values 0 and 1) - - specifies that the instance (an object group) should have an - RLE-encoded mask in the `segmentation` field. All the grouped shapes - are merged into a single mask, the largest one defines all - the object properties - - `score` (number) - the annotation `score` field - - arbitrary attributes - will be stored in the `attributes` annotation section - -Support for COCO tasks via Datumaro is described [here](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#export-to-other-formats) -For example, [support for COCO keypoints over Datumaro](https://github.com/openvinotoolkit/cvat/issues/2910#issuecomment-726077582): - -1. Install [Datumaro](https://github.com/openvinotoolkit/datumaro) - `pip install datumaro` -2. Export the task in the `Datumaro` format, unzip -3. Export the Datumaro project in `coco` / `coco_person_keypoints` formats - `datum export -f coco -p path/to/project [-- --save-images]` - -This way, one can export CVAT points as single keypoints or -keypoint lists (without the `visibility` COCO flag). +When exporting a dataset from a Project, subset names will mirror those used within the project itself. +Otherwise, a singular default subset will be created to house all the dataset information. +The section aligns with one of the specific COCO tasks, +such as `instances`, `panoptic`, `image_info`, `labels`, `captions`, or `stuff`. ## COCO import -Uploaded file: a single unpacked `*.json` or a zip archive with the structure described above or +Uplod format: a single unpacked `*.json` or a zip archive with the structure described above or [here](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#import-coco-dataset) (without images). - supported annotations: Polygons, Rectangles (if the `segmentation` field is empty) - supported tasks: `instances`, `person_keypoints` (only segmentations will be imported), `panoptic` -# [MS COCO Keypoint Detection](https://cocodataset.org/#keypoints-2020) - -- [Format specification](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html) - -## COCO export - -Downloaded file: a zip archive with the structure described [here](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#import-coco-dataset) - -- supported annotations: Skeletons -- supported attributes: - - `is_crowd` (checkbox or integer with values 0 and 1) - - specifies that the instance (an object group) should have an - RLE-encoded mask in the `segmentation` field. All the grouped shapes - are merged into a single mask, the largest one defines all - the object properties - - `score` (number) - the annotation `score` field - - arbitrary attributes - will be stored in the `attributes` annotation section - -## COCO import - -Uploaded file: a single unpacked `*.json` or a zip archive with the structure described -[here](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#import-coco-dataset) -(without images). - -- supported annotations: Skeletons - ## How to create a task from MS COCO dataset 1. Download the [MS COCO dataset](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#import-coco-dataset). diff --git a/site/content/en/docs/manual/advanced/formats/format-cvat.md b/site/content/en/docs/manual/advanced/formats/format-cvat.md index e91e89b3b2d3..7cf51e55676f 100644 --- a/site/content/en/docs/manual/advanced/formats/format-cvat.md +++ b/site/content/en/docs/manual/advanced/formats/format-cvat.md @@ -1,27 +1,27 @@ --- -linkTitle: "CVAT" +linkTitle: 'CVAT' weight: 1 --- -# CVAT +This is CVAT's native annotation format, +which fully supports all of CVAT's annotation features. +It is ideal for creating data backups. + +For more information, see: - [Format specification](/docs/manual/advanced/xml_format/) - [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/cvat_dataset) -This is the native CVAT annotation format. It supports all CVAT annotations -features, so it can be used to make data backups. - -- supported annotations CVAT for Images: Rectangles, Polygons, Polylines, - Points, Cuboids, Skeletons, Tags, Tracks - -- supported annotations CVAT for Videos: Rectangles, Polygons, Polylines, - Points, Cuboids, Skeletons, Tracks +## CVAT for image export -- attributes are supported +For export of images: -## CVAT for images export +- Supported annotations: Bounding Boxes, Polygons, Polylines, + Points, Cuboids, Skeletons, Tags, Tracks +- Attributes: Supported. +- Tracks: Supported (tracks are split by frames). -Downloaded file: a ZIP file of the following structure: +The downloaded file is a zip archive with following structure: ```bash taskname.zip/ @@ -31,11 +31,17 @@ taskname.zip/ └── annotations.xml ``` -- tracks are split by frames +## CVAT for video export + +For export of images: -## CVAT for videos export +- Supported annotations: Bounding Boxes, Polygons, Polylines, + Points, Cuboids, Skeletons, Tags, Tracks +- Attributes: Supported. +- Tracks: Supported (tracks are split by frames). +- Shapes are exported as single-frame tracks -Downloaded file: a ZIP file of the following structure: +Downloaded file is a zip archive with following structure: ```bash taskname.zip/ @@ -45,8 +51,7 @@ taskname.zip/ └── annotations.xml ``` -- shapes are exported as single-frame tracks - ## CVAT loader -Uploaded file: an XML file or a ZIP file of the structures above +Uploaded file: either an XML file or a +.zip file containing the aforementioned structures. diff --git a/site/content/en/docs/manual/advanced/formats/format-datumaro.md b/site/content/en/docs/manual/advanced/formats/format-datumaro.md index 2b049ed9b38f..a5587d551972 100644 --- a/site/content/en/docs/manual/advanced/formats/format-datumaro.md +++ b/site/content/en/docs/manual/advanced/formats/format-datumaro.md @@ -3,19 +3,43 @@ linkTitle: 'Datumaro' weight: 1.5 --- -# Datumaro format +Datumaro serves as a versatile format capable of handling complex +dataset and annotation transformations, +format conversions, dataset statistics, and merging, among other features. +It functions as the dataset support provider within CVAT. +Essentially, anything you can do in CVAT, you can also achieve +in Datumaro, but with the added benefit of specialized dataset operations. -[Datumaro](https://github.com/cvat-ai/datumaro/) is a tool, which can -help with complex dataset and annotation transformations, format conversions, -dataset statistics, merging, custom formats etc. It is used as a provider -of dataset support in CVAT, so basically, everything possible in CVAT -is possible in Datumaro too, but Datumaro can offer dataset operations. +For more information, see: -- supported annotations: any 2D shapes, labels -- supported attributes: any +- [Datumaro specification](https://github.com/cvat-ai/datumaro/) + +# Export annotations in Datumaro format + +For export of images: any 2D shapes, tags + +- Supported annotations: Bounding Boxes, Polygons. +- Attributes: Supported. +- Tracks: Supported. + +The downloaded file is a zip archive with the following structure: + +```bash +taskname.zip/ +├── annotations/ +│ └── default.json # fully description of classes and all dataset items +└── images/ # if the option `save images` was selected + └── default + ├── image1.jpg + ├── image2.jpg + ├── ... +``` # Import annotations in Datumaro format +- supported annotations: any 2D shapes, labels +- supported attributes: any + Uploaded file: a zip archive of the following structure: ```bash @@ -86,18 +110,3 @@ JSON annotations files in the `annotations` directory should have similar struct ] } ``` - -# Export annotations in Datumaro format - -Downloaded file: a zip archive of the following structure: - -```bash -taskname.zip/ -├── annotations/ -│ └── default.json # fully description of classes and all dataset items -└── images/ # if the option `save images` was selected - └── default - ├── image1.jpg - ├── image2.jpg - ├── ... -``` diff --git a/site/content/en/docs/manual/advanced/formats/format-icdar.md b/site/content/en/docs/manual/advanced/formats/format-icdar.md index c558ba76805b..4a4f338cdfc7 100644 --- a/site/content/en/docs/manual/advanced/formats/format-icdar.md +++ b/site/content/en/docs/manual/advanced/formats/format-icdar.md @@ -3,16 +3,37 @@ linkTitle: 'ICDAR13/15' weight: 14 --- -# [ICDAR13/15](https://rrc.cvc.uab.es/?ch=2) +ICDAR 13/15 formats are typically used for text detection and recognition tasks +and OCR (Optical Character Recognition). +These formats are usually paired with specialized text detection and recognition models. + +For more information, see: + +- [ICDAR13/15](https://rrc.cvc.uab.es/?ch=2) - [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/icdar_dataset) ## ICDAR13/15 export -Downloaded file: a zip archive of the following structure: +For export of images: + +- **ICDAR Recognition 1.0** (Text recognition): + - Supported annotations: Tag `icdar` + - Attributes: `caption`. +- **ICDAR Detection 1.0** (Text detection): + - Supported annotations: Bounding Boxes, Polygons with lavel `icdar` + added in constructor. + - Attributes: `text`. +- **ICDAR Segmentation 1.0** (Text segmentation): + - Supported annotations: Bounding Boxes, Polygons with label `icdar` + added in constructor. + - Attributes: `index`, `text`, `color`, `center` +- Tracks: Not supported. + +The downloaded file is a .zip archive with the following structure: ```bash -# word recognition task +# text recognition task taskname.zip/ └── word_recognition/ └── / @@ -42,20 +63,6 @@ taskname.zip/ └── 2_GT.txt ``` -**Word recognition task**: - -- supported annotations: Label `icdar` with attribute `caption` - -**Text localization task**: - -- supported annotations: Rectangles and Polygons with label `icdar` - and attribute `text` - -**Text segmentation task**: - -- supported annotations: Rectangles and Polygons with label `icdar` - and attributes `index`, `text`, `color`, `center` - ## ICDAR13/15 import Uploaded file: a zip archive of the structure above diff --git a/site/content/en/docs/manual/advanced/formats/format-imagenet.md b/site/content/en/docs/manual/advanced/formats/format-imagenet.md index 85d7533d8f00..79539c1ab57c 100644 --- a/site/content/en/docs/manual/advanced/formats/format-imagenet.md +++ b/site/content/en/docs/manual/advanced/formats/format-imagenet.md @@ -3,13 +3,27 @@ linkTitle: 'ImageNet' weight: 9 --- -# [ImageNet](http://www.image-net.org) +The ImageNet is typically used for a variety of computer vision tasks, +including but not limited to image classification, object detection, +and segmentation. +It is widely recognized and used in the training and +benchmarking of various machine learning models. + +For more information, see: + +- [ImageNet site](http://www.image-net.org) - [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/imagenet_dataset) ## ImageNet export -Downloaded file: a zip archive of the following structure: +For export of images: + +- Supported annotations: Tags. +- Attributes: Not supported. +- Tracks: Not supported. + +The downloaded file is a .zip archive with the following structure: ```bash # if we save images: @@ -29,8 +43,6 @@ taskname.zip/ ``` -- supported annotations: Labels - ## ImageNet import Uploaded file: a zip archive of the structure above diff --git a/site/content/en/docs/manual/advanced/formats/format-kitti.md b/site/content/en/docs/manual/advanced/formats/format-kitti.md index 06ace2998232..a157e2533c59 100644 --- a/site/content/en/docs/manual/advanced/formats/format-kitti.md +++ b/site/content/en/docs/manual/advanced/formats/format-kitti.md @@ -3,33 +3,40 @@ linkTitle: 'KITTI' weight: 17 --- -# [KITTI](http://www.cvlibs.net/datasets/kitti/) +The KITTI format is widely used for a range of computer +vision tasks related to autonomous driving, including +but not limited to 3D object detection, multi-object tracking, +and scene flow estimation. Given its special focus on +automotive scenes, the KITTI format is generally +used with models that are designed or adapted for these types of tasks. +For more information, see: + +- [KITTI site](http://www.cvlibs.net/datasets/kitti/) - [Format specification for KITTI detection](https://s3.eu-central-1.amazonaws.com/avg-kitti/devkit_object.zip) - [Format specification for KITTI segmentation](https://s3.eu-central-1.amazonaws.com/avg-kitti/devkit_semantics.zip) - [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/kitti_dataset) -- supported annotations: - - - Rectangles (detection task) - - Polygon (segmentation task) - -- supported attributes: - - - `occluded` (both UI option and a separate attribute). - Indicates that a significant portion of the object within - the bounding box is occluded by another object - - `truncated` supported only for rectangles - (should be defined for labels as `checkbox` -es). - Indicates that the bounding box specified for the object - does not correspond to the full extent of the object - - 'is_crowd' supported only for polygons - (should be defined for labels as `checkbox` -es). - Indicates that the annotation covers multiple instances of the same class - ## KITTI annotations export -Downloaded file: a zip archive of the following structure: +For export of images: + +- Supported annotations: Bounding Boxes (detection), Polygons (segmentation). +- Supported attributes: + - `occluded` (Available both as a UI option and a separate attribute) + Denotes that a major portion of the object within + the bounding box is obstructed by another object. + - `truncated` (Only applicable to bounding boxes) + Must be represented as `checkboxes` for labels. + Suggests that the bounding box does not + encompass the entire object; some part is cut off. + - `is_crowd` (Only valid for polygons). Should be indicated + using `checkboxes` for labels. + Signifies that the annotation encapsulates + multiple instances of the same object class. +- Tracks: Not supported. + +The downloaded file is a .zip archive with the following structure: ``` └─ annotations.zip/ diff --git a/site/content/en/docs/manual/advanced/formats/format-labelme.md b/site/content/en/docs/manual/advanced/formats/format-labelme.md index 42a0a699e718..2d5b82927d7f 100644 --- a/site/content/en/docs/manual/advanced/formats/format-labelme.md +++ b/site/content/en/docs/manual/advanced/formats/format-labelme.md @@ -3,13 +3,25 @@ linkTitle: 'LabelMe' weight: 2 --- -# [LabelMe](http://labelme.csail.mit.edu/Release3.0) +The LabelMe format is often used for image segmentation tasks in computer vision. +While it may not be specifically tied to any particular models, +it's designed to be versatile and can be easily converted to formats +that are compatible with popular frameworks like TensorFlow or PyTorch. +For more information, see: + +- [LabelMe](http://labelme.csail.mit.edu/Release3.0) - [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/labelme_dataset) ## LabelMe export -Downloaded file: a zip archive of the following structure: +For export of images: + +- Supported annotations: Bounding Boxes, Polygons. +- Attributes: Supported for Polygons. +- Tracks: Not supported. + +The downloaded file is a .zip archive with the following structure: ```bash taskname.zip/ @@ -17,8 +29,6 @@ taskname.zip/ └── img1.xml ``` -- supported annotations: Rectangles, Polygons (with attributes) - ## LabelMe import Uploaded file: a zip archive of the following structure: diff --git a/site/content/en/docs/manual/advanced/formats/format-lfw.md b/site/content/en/docs/manual/advanced/formats/format-lfw.md index 9e2b44fd0243..094e4b093c2f 100644 --- a/site/content/en/docs/manual/advanced/formats/format-lfw.md +++ b/site/content/en/docs/manual/advanced/formats/format-lfw.md @@ -3,38 +3,31 @@ linkTitle: 'LFW' weight: 17 --- -# [LFW](http://vis-www.cs.umass.edu/lfw/) +The Labeled Faces in the Wild (LFW) format +is primarily used for face verification and face recognition tasks. +The LFW format is designed to be straightforward and +is compatible with a variety of machine learning and deep learning frameworks. +For more information, see: + +- [LFW site](http://vis-www.cs.umass.edu/lfw/) - [Format specification](http://vis-www.cs.umass.edu/lfw/README.txt) - [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/lfw_dataset) -- Supported annotations: tags, points. +# Export LFW annotation + +For export of images: -- Supported attributes: +- Supported annotations: Tags, Skeletons. +- Attributes: - `negative_pairs` (should be defined for labels as `text`): list of image names with mismatched persons. - `positive_pairs` (should be defined for labels as `text`): list of image names with matched persons. +- Tracks: Not supported. -# Import LFW annotation - -The uploaded annotations file should be a zip file with the following structure: - -```bash -.zip/ - └── annotations/ - ├── landmarks.txt # list with landmark points for each image - ├── pairs.txt # list of matched and mismatched pairs of person - └── people.txt # optional file with a list of persons name -``` - -Full information about the content of annotation files is available -[here](http://vis-www.cs.umass.edu/lfw/README.txt) - -# Export LFW annotation - -Downloaded file: a zip archive of the following structure: +The downloaded file is a .zip archive with the following structure: ```bash .zip/ @@ -53,6 +46,21 @@ Downloaded file: a zip archive of the following structure: └── people.txt ``` +# Import LFW annotation + +The uploaded annotations file should be a zip file with the following structure: + +```bash +.zip/ + └── annotations/ + ├── landmarks.txt # list with landmark points for each image + ├── pairs.txt # list of matched and mismatched pairs of person + └── people.txt # optional file with a list of persons name +``` + +Full information about the content of annotation files is available +[here](http://vis-www.cs.umass.edu/lfw/README.txt) + # Example: create task with images and upload LFW annotations into it This is one of the possible ways to create a task and add LFW annotations for it. diff --git a/site/content/en/docs/manual/advanced/formats/format-market1501.md b/site/content/en/docs/manual/advanced/formats/format-market1501.md index 241f248b663a..bf26d627a1d4 100644 --- a/site/content/en/docs/manual/advanced/formats/format-market1501.md +++ b/site/content/en/docs/manual/advanced/formats/format-market1501.md @@ -3,13 +3,24 @@ linkTitle: 'Market-1501' weight: 13 --- -# [Market-1501](https://www.aitribune.com/dataset/2018051063) +The Market-1501 dataset is widely used for person re-identification tasks. +It is a challenging dataset that has gained significant attention +in the computer vision community. +For more information, see: + +- [Market-1501](https://www.aitribune.com/dataset/2018051063) - [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/market1501_dataset) ## Market-1501 export -Downloaded file: a zip archive of the following structure: +For export of images: + +- Supported annotations: Bounding Boxes +- Attributes: `query` (checkbox), `person_id` (number), `camera_id`(number). +- Tracks: Not supported. + +Th downloaded file is a .zip archive with the following structure: ```bash taskname.zip/ @@ -33,8 +44,6 @@ s1 - sequence 00 - means that this bounding box is the first one among the several ``` -- supported annotations: Label `market-1501` with attributes (`query`, `person_id`, `camera_id`) - ## Market-1501 import Uploaded file: a zip archive of the structure above diff --git a/site/content/en/docs/manual/advanced/formats/format-mot.md b/site/content/en/docs/manual/advanced/formats/format-mot.md index 58524375b63d..e7afd8f2d3d3 100644 --- a/site/content/en/docs/manual/advanced/formats/format-mot.md +++ b/site/content/en/docs/manual/advanced/formats/format-mot.md @@ -3,13 +3,26 @@ linkTitle: 'MOT' weight: 3 --- -# [MOT sequence](https://arxiv.org/pdf/1906.04567.pdf) +The MOT (Multiple Object Tracking) sequence format is widely +used for evaluating multi-object tracking algorithms, particularly in +the domains of pedestrian tracking, vehicle tracking, and more. +The MOT sequence format essentially contains frames of video +along with annotations that specify object locations and identities over time. +For more information, see: + +- [MOT sequence paper](https://arxiv.org/pdf/1906.04567.pdf) - [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/mot_dataset) ## MOT export -Downloaded file: a zip archive of the following structure: +For export of images and videos: + +- Supported annotations: Bounding Boxes, Tracks. +- Attributes: `visibility` (number), `ignored` (checkbox) +- Tracks: Supported. + +The downloaded file is a .zip archive with the following structure: ```bash taskname.zip/ @@ -33,9 +46,6 @@ person ``` -- supported annotations: Rectangle shapes and tracks -- supported attributes: `visibility` (number), `ignored` (checkbox) - ## MOT import Uploaded file: a zip archive of the structure above or: diff --git a/site/content/en/docs/manual/advanced/formats/format-mots.md b/site/content/en/docs/manual/advanced/formats/format-mots.md index 9a4952bdfbb3..61cafed5bd9f 100644 --- a/site/content/en/docs/manual/advanced/formats/format-mots.md +++ b/site/content/en/docs/manual/advanced/formats/format-mots.md @@ -3,13 +3,28 @@ linkTitle: 'MOTS' weight: 4 --- -# [MOTS PNG](https://www.vision.rwth-aachen.de/page/mots) +The MOT (Multiple Object Tracking) sequence format is widely +used for evaluating multi-object tracking algorithms, particularly in +the domains of pedestrian tracking, vehicle tracking, and more. +The MOT sequence format essentially contains frames of video +along with annotations that specify object locations and identities over time. +This version encoded as .png. Supports masks. + +For more information, see: + +- [MOTS PNG Specification](https://www.vision.rwth-aachen.de/page/mots) - [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/mots_dataset) ## MOTS PNG export -Downloaded file: a zip archive of the following structure: +For export of images and videos: + +- Supported annotations: Bounding Boxes, Tracks. +- Attributes: `visibility` (number), `ignored` (checkbox). +- Tracks: Supported. + +The downloaded file is a .zip archive with the following structure: ```bash taskname.zip/ diff --git a/site/content/en/docs/manual/advanced/formats/format-openimages.md b/site/content/en/docs/manual/advanced/formats/format-openimages.md index b80494dca122..2855ce0e61fc 100644 --- a/site/content/en/docs/manual/advanced/formats/format-openimages.md +++ b/site/content/en/docs/manual/advanced/formats/format-openimages.md @@ -3,49 +3,45 @@ linkTitle: 'Open Images V6' weight: 15 --- -# [Open Images](https://storage.googleapis.com/openimages/web/index.html) +The Open Images format is based on a large-scale, diverse dataset +that contains object detection, object segmentation, visual relationship, +and localized narratives annotations. -- [Format specification](https://storage.googleapis.com/openimages/web/download.html) -- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/open_images_dataset) - -- Supported annotations: - - - Rectangles (detection task) - - Tags (classification task) - - Polygons (segmentation task) - -- Supported attributes: +Its export data format is compatible with many object detection and segmentation models. - - Labels +For more information, see: - - `score` (should be defined for labels as `text` or `number`). - The confidence level from 0 to 1. - - - Bounding boxes +- [Open Images site](https://storage.googleapis.com/openimages/web/index.html) +- [Format specification](https://storage.googleapis.com/openimages/web/download.html) +- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/open_images_dataset) - - `score` (should be defined for labels as `text` or `number`). - The confidence level from 0 to 1. - - `occluded` (both UI option and a separate attribute). - Whether the object is occluded by another object. - - `truncated` (should be defined for labels as `checkbox` -es). - Whether the object extends beyond the boundary of the image. - - `is_group_of` (should be defined for labels as `checkbox` -es). - Whether the object represents a group of objects of the same class. - - `is_depiction` (should be defined for labels as `checkbox` -es). - Whether the object is a depiction (such as a drawing) - rather than a real object. - - `is_inside` (should be defined for labels as `checkbox` -es). - Whether the object is seen from the inside. +## Open Images export - - Masks - - `box_id` (should be defined for labels as `text`). - An identifier for the bounding box associated with the mask. - - `predicted_iou` (should be defined for labels as `text` or `number`). - Predicted IoU value with respect to the ground truth. +For export of images: -## Open Images export +- Supported annotations: Bounding Boxes (detection), + Tags (classification), Polygons (segmentation). -Downloaded file: a zip archive of the following structure: +- Supported attributes: + - Tags: `score` must be defined for labels as `text` or `number`. + The confidence level from 0 to 1. + - Bounding boxes:
`score` must be defined for labels as `text` or `number`. + The confidence level from 0 to 1.
`occluded` as both UI option + and a separate attribute. Whether the object is occluded by another object.
`truncated` + must be defined for labels as `checkbox`. Whether the object extends beyond the boundary of the image. +
`is_group_of` must be defined for labels as `checkbox`. Whether the object + represents a group of objects of the same class.
`is_depiction` must be + defined for labels as `checkbox`. Whether the object is a depiction (such as a drawing) + rather than a real object.
`is_inside` must be defined + for labels as `checkbox`. Whether the object is seen from the inside. + - Masks: +
`box_id` must be defined for labels as `text`. An identifier for + the bounding box associated with the mask. +
`predicted_iou` must be defined for labels as `text` or `number`. + Predicted IoU value with respect to the ground truth. +- Tracks: Not supported. + +The downloaded file is a .zip archive with the following structure: ``` └─ taskname.zip/ diff --git a/site/content/en/docs/manual/advanced/formats/format-smask.md b/site/content/en/docs/manual/advanced/formats/format-smask.md new file mode 100644 index 000000000000..b7825f833c78 --- /dev/null +++ b/site/content/en/docs/manual/advanced/formats/format-smask.md @@ -0,0 +1,92 @@ +--- +linkTitle: 'Segmentation Mask' +weight: 6 +--- + +Segmentation masks format is often used in the training of models for tasks +like semantic segmentation, instance segmentation, and panoptic segmentation. + +Segmentation Mask in CVAT is +a format created by CVAT engineers +inside the [Pascal VOC](docs/manual/advanced/formats/format-voc/) + +## Segmentation mask export + +For export of images: + +- Supported annotations: Bounding Boxes, Polygons. +- Attributes: Not supported. +- Tracks: Not supported. + +The downloaded file is a .zip archive with the following structure: + +```bash +taskname.zip/ +├── labelmap.txt # optional, required for non-VOC labels +├── ImageSets/ +│ └── Segmentation/ +│ └── default.txt # list of image names without extension +├── SegmentationClass/ # merged class masks +│ ├── image1.png +│ └── image2.png +└── SegmentationObject/ # merged instance masks + ├── image1.png + └── image2.png + +# labelmap.txt +# label : color (RGB) : 'body' parts : actions +background:0,128,0:: +aeroplane:10,10,128:: +bicycle:10,128,0:: +bird:0,108,128:: +boat:108,0,100:: +bottle:18,0,8:: +bus:12,28,0:: +``` + +The mask is a `png` image that can have either 1 or 3 channels. +Each pixel in the image has a color that corresponds to a specific label. +The colors are generated according to the Pascal VOC [ +algorithm](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/htmldoc/devkit_doc.html#sec:voclabelcolormap). +By default, the color `(0, 0, 0)` is used to represent the background. + +## Segmentation mask import + +Uploaded file: a zip archive of the following structure: + +```bash + taskname.zip/ + ├── labelmap.txt # optional, required for non-VOC labels + ├── ImageSets/ + │ └── Segmentation/ + │ └── .txt + ├── SegmentationClass/ + │ ├── image1.png + │ └── image2.png + └── SegmentationObject/ + ├── image1.png + └── image2.png +``` + +It is also possible to import grayscale (1-channel) PNG masks. +For grayscale masks provide a list of labels with the number of lines equal +to the maximum color index on images. The lines must be in the right order +so that line index is equal to the color index. Lines can have arbitrary, +but different, colors. If there are gaps in the used color +indices in the annotations, they must be filled with arbitrary dummy labels. +Example: + +``` +q:0,128,0:: # color index 0 +aeroplane:10,10,128:: # color index 1 +_dummy2:2,2,2:: # filler for color index 2 +_dummy3:3,3,3:: # filler for color index 3 +boat:108,0,100:: # color index 3 +... +_dummy198:198,198,198:: # filler for color index 198 +_dummy199:199,199,199:: # filler for color index 199 +... +the last label:12,28,0:: # color index 200 +``` + +- supported shapes: Polygons diff --git a/site/content/en/docs/manual/advanced/formats/format-tfrecord.md b/site/content/en/docs/manual/advanced/formats/format-tfrecord.md index b01950ab992f..478fca02e353 100644 --- a/site/content/en/docs/manual/advanced/formats/format-tfrecord.md +++ b/site/content/en/docs/manual/advanced/formats/format-tfrecord.md @@ -3,16 +3,21 @@ linkTitle: 'TFRecord' weight: 8 --- -# [TFRecord](https://www.tensorflow.org/tutorials/load_data/tfrecord) +The TFRecord format is tightly integrated with TensorFlow +and is commonly used for training models within the TensorFlow ecosystem. -- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/tf_detection_api_dataset) +TFRecord is an incredibly flexible data format. +We strive to align our implementation with the +format employed by the [TensorFlow Object Detection API](https://github.com/tensorflow/models/tree/master/research/object_detection), +making only minimal changes as necessary. + +For more information, see: -TFRecord is a very flexible format, but we try to correspond the -format that used in -[TF object detection](https://github.com/tensorflow/models/tree/master/research/object_detection) -with minimal modifications. +- [TFRecord](https://www.tensorflow.org/tutorials/load_data/tfrecord) +- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/tf_detection_api_dataset) -Used feature description: +This format does not have a fixed structure, so in +CVAT the following structure is used: ```python image_feature_description = { @@ -32,7 +37,14 @@ image_feature_description = { ## TFRecord export -Downloaded file: a zip archive with following structure: +For export of images: + +- Supported annotations: Bounding Boxes, Polygons + (as masks, manually over [Datumaro](https://github.com/cvat-ai/datumaro/blob/develop/docs/user_manual.md)) +- Attributes: Not supported. +- Tracks: Not supported. + +The downloaded file is a .zip archive with the following structure: ```bash taskname.zip/ @@ -51,19 +63,21 @@ item { ... ``` -- supported annotations: Rectangles, Polygons (as masks, manually over [Datumaro](https://github.com/cvat-ai/datumaro/blob/develop/docs/user_manual.md)) - How to export masks: -1. Export annotations in `Datumaro` format -1. Apply `polygons_to_masks` and `boxes_to_masks` transforms - ```bash - datum transform -t polygons_to_masks -p path/to/proj -o ptm - datum transform -t boxes_to_masks -p ptm -o btm - ``` -1. Export in the `TF Detection API` format - ```bash - datum export -f tf_detection_api -p btm [-- --save-images] - ``` + +1. Export annotations in [Datumaro](/docs/manual/advanced/formats/format-datumaro/) format. +1. Apply `polygons_to_masks` and `boxes_to_masks` transforms: + + ```bash + datum transform -t polygons_to_masks -p path/to/proj -o ptm + datum transform -t boxes_to_masks -p ptm -o btm + ``` + +1. Export in the `TF Detection API` format: + + ```bash + datum export -f tf_detection_api -p btm [-- --save-images] + ``` ## TFRecord import diff --git a/site/content/en/docs/manual/advanced/formats/format-vggface2.md b/site/content/en/docs/manual/advanced/formats/format-vggface2.md index da32c6872715..697ea165bee1 100644 --- a/site/content/en/docs/manual/advanced/formats/format-vggface2.md +++ b/site/content/en/docs/manual/advanced/formats/format-vggface2.md @@ -3,13 +3,24 @@ linkTitle: 'VGGFace2' weight: 12 --- -# [VGGFace2](https://github.com/ox-vgg/vgg_face2) +The VGGFace2 is primarily designed for face recognition tasks and is +most commonly used with deep learning models specifically designed for face recognition, +verification, and similar tasks. +For more information, see: + +- [VGGFace2 Github](https://github.com/ox-vgg/vgg_face2) - [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/vgg_face2_dataset) ## VGGFace2 export -Downloaded file: a zip archive of the following structure: +For export of images: + +- Supported annotations: Bounding Boxes, Points (landmarks - groups of 5 points). +- Attributes: Not supported. +- Tracks: Not supported. + +The downloaded file is a .zip archive with the following structure: ```bash taskname.zip/ @@ -28,8 +39,6 @@ label0 label1 ``` -- supported annotations: Rectangles, Points (landmarks - groups of 5 points) - ## VGGFace2 import Uploaded file: a zip archive of the structure above diff --git a/site/content/en/docs/manual/advanced/formats/format-voc.md b/site/content/en/docs/manual/advanced/formats/format-voc.md index 9703b9d2c8b3..e94f70657ea5 100644 --- a/site/content/en/docs/manual/advanced/formats/format-voc.md +++ b/site/content/en/docs/manual/advanced/formats/format-voc.md @@ -3,27 +3,31 @@ linkTitle: 'Pascal VOC' weight: 6 --- -# [Pascal VOC](http://host.robots.ox.ac.uk/pascal/VOC/) +he Pascal VOC (Visual Object Classes) format +is one of the earlier established benchmarks for object classification and detection, +which provides a standardized image data set for object class recognition. -- [Format specification](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/devkit_doc.pdf) -- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/voc_dataset) +The export data format is XML-based and has been widely adopted in computer vision tasks. -- supported annotations: +For more information, see: - - Rectangles (`detection` and `layout` tasks) - - Tags (`action-` and `classification` tasks) - - Polygons (`segmentation` task) +- [Pascal VOC](http://host.robots.ox.ac.uk/pascal/VOC/) +- [Format specification](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/devkit_doc.pdf) +- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/voc_dataset) -- supported attributes: +## Pascal VOC export - - `occluded` (both UI option and a separate attribute) - - `truncated` and `difficult` (should be defined for labels as `checkbox` -es) - - action attributes (import only, should be defined as `checkbox` -es) - - arbitrary attributes (in the `attributes` section of XML files) +For export of images: -## Pascal VOC export +- Supported annotations: Bounding Boxes (detection), + Tags (classification), Polygons (segmentation) +- Attributes: + - `occluded` as both UI option and a separate attribute. + - `truncated` and `difficult` must be defined for labels as `checkbox`. + - Arbitrary attributes in the `attributes` section of XML files. +- Tracks: Not supported. -Downloaded file: a zip archive of the following structure: +The downloaded file is a .zip archive with the following structure: ```bash taskname.zip/ @@ -50,6 +54,8 @@ bird::: ## Pascal VOC import +Supported attributes: action attributes (import only, should be defined as `checkbox` -es) + Uploaded file: a zip archive of the structure declared above or the following: ```bash @@ -71,81 +77,7 @@ There are 2 options: 1. match by frame number. File name should be `.jpg` or `frame_000000.jpg`. It should be used when task was created from video. -## Segmentation mask export - -Downloaded file: a zip archive of the following structure: - -```bash -taskname.zip/ -├── labelmap.txt # optional, required for non-VOC labels -├── ImageSets/ -│ └── Segmentation/ -│ └── default.txt # list of image names without extension -├── SegmentationClass/ # merged class masks -│ ├── image1.png -│ └── image2.png -└── SegmentationObject/ # merged instance masks - ├── image1.png - └── image2.png - -# labelmap.txt -# label : color (RGB) : 'body' parts : actions -background:0,128,0:: -aeroplane:10,10,128:: -bicycle:10,128,0:: -bird:0,108,128:: -boat:108,0,100:: -bottle:18,0,8:: -bus:12,28,0:: -``` - -Mask is a `png` image with 1 or 3 channels where each pixel -has own color which corresponds to a label. -Colors are generated following to Pascal VOC [algorithm](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/htmldoc/devkit_doc.html#sec:voclabelcolormap). -`(0, 0, 0)` is used for background by default. - -- supported shapes: Rectangles, Polygons - -## Segmentation mask import - -Uploaded file: a zip archive of the following structure: - -```bash - taskname.zip/ - ├── labelmap.txt # optional, required for non-VOC labels - ├── ImageSets/ - │ └── Segmentation/ - │ └── .txt - ├── SegmentationClass/ - │ ├── image1.png - │ └── image2.png - └── SegmentationObject/ - ├── image1.png - └── image2.png -``` - -It is also possible to import grayscale (1-channel) PNG masks. -For grayscale masks provide a list of labels with the number of lines equal -to the maximum color index on images. The lines must be in the right order -so that line index is equal to the color index. Lines can have arbitrary, -but different, colors. If there are gaps in the used color -indices in the annotations, they must be filled with arbitrary dummy labels. -Example: - -``` -q:0,128,0:: # color index 0 -aeroplane:10,10,128:: # color index 1 -_dummy2:2,2,2:: # filler for color index 2 -_dummy3:3,3,3:: # filler for color index 3 -boat:108,0,100:: # color index 3 -... -_dummy198:198,198,198:: # filler for color index 198 -_dummy199:199,199,199:: # filler for color index 199 -... -the last label:12,28,0:: # color index 200 -``` -- supported shapes: Polygons ## How to create a task from Pascal VOC dataset @@ -165,9 +97,9 @@ the last label:12,28,0:: # color index 200 Select interesting image files (See [Creating an annotation task](/docs/manual/basics/creating_an_annotation_task/) guide for details) -2. zip the corresponding annotation files +1. zip the corresponding annotation files -3. click `Upload annotation` button, choose `Pascal VOC ZIP 1.1` +1. click `Upload annotation` button, choose `Pascal VOC ZIP 1.1` and select the zip file with annotations from previous step. It may take some time. diff --git a/site/content/en/docs/manual/advanced/formats/format-widerface.md b/site/content/en/docs/manual/advanced/formats/format-widerface.md index 36be8290d489..c45191109651 100644 --- a/site/content/en/docs/manual/advanced/formats/format-widerface.md +++ b/site/content/en/docs/manual/advanced/formats/format-widerface.md @@ -3,13 +3,26 @@ linkTitle: 'Wider Face' weight: 9 --- -# [WIDER Face](http://shuoyang1213.me/WIDERFACE/) +he WIDER Face dataset is widely used for face detection tasks. +Many popular models for object detection and face detection +specifically are trained on this dataset for benchmarking and deployment. +For more information, see: + +- [WIDER Face Specification](http://shuoyang1213.me/WIDERFACE/) - [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/widerface_dataset) ## WIDER Face export -Downloaded file: a zip archive of the following structure: +For export of images: + +- Supported annotations: Bounding Boxes (with attributes), Tags. +- Attributes: + - `blur`, `expression`, `illumination`, `pose`, `invalid` + - `occluded` (both the annotation property & an attribute). +- Tracks: Not supported. + +The downloaded file is a .zip archive with the following structure: ```bash taskname.zip/ @@ -24,11 +37,6 @@ taskname.zip/ └── 1_label1_image2.jpg ``` -- supported annotations: Rectangles (with attributes), Labels -- supported attributes: - - `blur`, `expression`, `illumination`, `pose`, `invalid` - - `occluded` (both the annotation property & an attribute) - ## WIDER Face import Uploaded file: a zip archive of the structure above diff --git a/site/content/en/docs/manual/advanced/formats/format-yolo.md b/site/content/en/docs/manual/advanced/formats/format-yolo.md index 9fdcef9a8e9c..dd457de14db4 100644 --- a/site/content/en/docs/manual/advanced/formats/format-yolo.md +++ b/site/content/en/docs/manual/advanced/formats/format-yolo.md @@ -3,15 +3,24 @@ linkTitle: 'YOLO' weight: 7 --- -# [YOLO](https://pjreddie.com/darknet/yolo/) +models, which are designed for real-time object detection tasks. +However, the format can also be adapted for use with other object detection models. +For more information, see: + +- [YOLO Specification](https://pjreddie.com/darknet/yolo/) - [Format specification](https://github.com/AlexeyAB/darknet#how-to-train-to-detect-your-custom-objects) - [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/yolo_dataset) -- supported annotations: Rectangles ## YOLO export -Downloaded file: a zip archive with following structure: +For export of images: + +- Supported annotations: Bounding Boxes. +- Attributes: Not supported. +- Tracks: Not supported. + +The downloaded file is a .zip archive with the following structure: ```bash archive.zip/ @@ -48,12 +57,16 @@ airplane 2 0.7 0.2 0.3 0.1 ``` -Each annotation `*.txt` file has a name that corresponds to the name of -the image file (e. g. `frame_000001.txt` is the annotation -for the `frame_000001.jpg` image). -The `*.txt` file structure: each line describes label and bounding box -in the following format `label_id cx cy w h`. -`obj.names` contains the ordered list of label names. +Each annotation file, with the `.txt` extension, +is named to correspond with its associated image file. + +For example, `frame_000001.txt` serves as the annotation for the +`frame_000001.jpg` image. + +The structure of the `.txt` file is as follows: +each line describes a label and a bounding box +in the format `label_id cx cy w h`. +The file `obj.names` contains an ordered list of label names. ## YOLO import diff --git a/site/content/en/docs/manual/advanced/export-import-datasets.md b/site/content/en/docs/manual/advanced/import-datasets.md similarity index 97% rename from site/content/en/docs/manual/advanced/export-import-datasets.md rename to site/content/en/docs/manual/advanced/import-datasets.md index 942c881fedb1..7342ffe53e21 100644 --- a/site/content/en/docs/manual/advanced/export-import-datasets.md +++ b/site/content/en/docs/manual/advanced/import-datasets.md @@ -1,6 +1,6 @@ --- -title: 'Export/import datasets and upload annotation' -linkTitle: 'Export/import datasets' +title: 'Import datasets and upload annotation' +linkTitle: 'Import datasets and upload annotation' weight: 19 description: 'This section explains how to download and upload datasets (including annotation, images, and metadata) of projects, tasks, and jobs.' diff --git a/site/content/en/images/export_job_as_dataset_dialog.png b/site/content/en/images/export_job_as_dataset_dialog.png new file mode 100644 index 0000000000000000000000000000000000000000..539bcc1989a99ddb1e650d0e8f0e48c6ba98df78 GIT binary patch literal 17751 zcmcJ%1yGh@v@QxFpfu7*cO#8RcPk|b(jXyS(%m3P2#9opARIevT?jRr_#@~aF2o%Ml zGVm9ov$~ul!skA+HTdMNg@lR(0zySB`lT^4e16|S{)ICF0#@7YA4CEsMSlbY=}iS` z2~Br{tr=8rl{Yu2yUvx;W)Em+sP9);WS2>`-V=Tmz1p1r 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