diff --git a/CHANGELOG.md b/CHANGELOG.md index 4e3f6fadc51..9ce412c1be2 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -11,6 +11,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 - Notification if the browser does not support nesassary API - Added ability to export project as a dataset () + and project with 3D tasks () - Additional inline tips in interactors with demo gifs () ### Changed diff --git a/cvat-core/package-lock.json b/cvat-core/package-lock.json index e0b9594df79..15be69a6b42 100644 --- a/cvat-core/package-lock.json +++ b/cvat-core/package-lock.json @@ -1,6 +1,6 @@ { "name": "cvat-core", - "version": "3.14.0", + "version": "3.15.0", "lockfileVersion": 1, "requires": true, "dependencies": { diff --git a/cvat-core/package.json b/cvat-core/package.json index 9c169475461..229b9bec6ae 100644 --- a/cvat-core/package.json +++ b/cvat-core/package.json @@ -1,6 +1,6 @@ { "name": "cvat-core", - "version": "3.14.0", + "version": "3.15.0", "description": "Part of Computer Vision Tool which presents an interface for client-side integration", "main": "babel.config.js", "scripts": { diff --git a/cvat-core/src/project.js b/cvat-core/src/project.js index bd25fc0f1b1..7e324498b95 100644 --- a/cvat-core/src/project.js +++ b/cvat-core/src/project.js @@ -34,6 +34,7 @@ task_subsets: undefined, training_project: undefined, task_ids: undefined, + dimension: undefined, }; for (const property in data) { @@ -153,7 +154,7 @@ /** * @name createdDate * @type {string} - * @memberof module:API.cvat.classes.Task + * @memberof module:API.cvat.classes.Project * @readonly * @instance */ @@ -163,13 +164,24 @@ /** * @name updatedDate * @type {string} - * @memberof module:API.cvat.classes.Task + * @memberof module:API.cvat.classes.Project * @readonly * @instance */ updatedDate: { get: () => data.updated_date, }, + /** + * Dimesion of the tasks in the project, if no task dimension is null + * @name dimension + * @type {string} + * @memberof module:API.cvat.classes.Project + * @readonly + * @instance + */ + dimension: { + get: () => data.dimension, + }, /** * After project has been created value can be appended only. * @name labels diff --git a/cvat-ui/src/components/export-dataset/export-dataset-modal.tsx b/cvat-ui/src/components/export-dataset/export-dataset-modal.tsx index 400cdc4e21c..d1660dfee78 100644 --- a/cvat-ui/src/components/export-dataset/export-dataset-modal.tsx +++ b/cvat-ui/src/components/export-dataset/export-dataset-modal.tsx @@ -34,9 +34,9 @@ function ExportDatasetModal(): JSX.Element { const instance = useSelector((state: CombinedState) => state.export.instance); const modalVisible = useSelector((state: CombinedState) => state.export.modalVisible); const dumpers = useSelector((state: CombinedState) => state.formats.annotationFormats.dumpers); - const { - tasks: taskExportActivities, projects: projectExportActivities, - } = useSelector((state: CombinedState) => state.export); + const { tasks: taskExportActivities, projects: projectExportActivities } = useSelector( + (state: CombinedState) => state.export, + ); const initActivities = (): void => { if (instance instanceof core.classes.Project) { @@ -62,19 +62,28 @@ function ExportDatasetModal(): JSX.Element { dispatch(exportActions.closeExportModal()); }; - const handleExport = useCallback((values: FormValues): void => { - // have to validate format before so it would not be undefined - dispatch( - exportDatasetAsync(instance, values.selectedFormat as string, values.customName ? `${values.customName}.zip` : '', values.saveImages), - ); - closeModal(); - Notification.info({ - message: 'Dataset export started', - description: `Dataset export was started for ${instanceType} #${instance?.id}. ` + - 'Download will start automaticly as soon as the dataset is ready.', - className: `cvat-notification-notice-export-${instanceType}-start`, - }); - }, [instance?.id, instance instanceof core.classes.Project, instanceType]); + const handleExport = useCallback( + (values: FormValues): void => { + // have to validate format before so it would not be undefined + dispatch( + exportDatasetAsync( + instance, + values.selectedFormat as string, + values.customName ? `${values.customName}.zip` : '', + values.saveImages, + ), + ); + closeModal(); + Notification.info({ + message: 'Dataset export started', + description: + `Dataset export was started for ${instanceType} #${instance?.id}. ` + + 'Download will start automaticly as soon as the dataset is ready.', + className: `cvat-notification-notice-export-${instanceType}-start`, + }); + }, + [instance?.id, instance instanceof core.classes.Project, instanceType], + ); return ( {dumpers .sort((a: any, b: any) => a.name.localeCompare(b.name)) - .filter( - (dumper: any): boolean => - !(instance instanceof core.classes.Task) || - dumper.dimension === instance?.dimension, - ) + .filter((dumper: any): boolean => dumper.dimension === instance?.dimension) .map( (dumper: any): JSX.Element => { const pending = (activities || []).includes(dumper.name); diff --git a/cvat-ui/src/components/projects-page/actions-menu.tsx b/cvat-ui/src/components/projects-page/actions-menu.tsx index 75d71508652..c85684ad6db 100644 --- a/cvat-ui/src/components/projects-page/actions-menu.tsx +++ b/cvat-ui/src/components/projects-page/actions-menu.tsx @@ -37,12 +37,13 @@ export default function ProjectActionsMenuComponent(props: Props): JSX.Element { return ( - Delete dispatch(exportActions.openExportModal(projectInstance))} > Export project dataset +
+ Delete ); } diff --git a/cvat/apps/dataset_manager/bindings.py b/cvat/apps/dataset_manager/bindings.py index 6a61b2cf93c..2062e0333fb 100644 --- a/cvat/apps/dataset_manager/bindings.py +++ b/cvat/apps/dataset_manager/bindings.py @@ -513,7 +513,7 @@ class ProjectData(InstanceLabelData): Track = NamedTuple('Track', [('label', str), ('group', int), ('source', str), ('shapes', List[TrackedShape]), ('task_id', int)]) Tag = NamedTuple('Tag', [('frame', int), ('label', str), ('attributes', List[InstanceLabelData.Attribute]), ('source', str), ('group', int), ('task_id', int)]) Tag.__new__.__defaults__ = (0, ) - Frame = NamedTuple('Frame', [('task_id', int), ('subset', str), ('idx', int), ('frame', int), ('name', str), ('width', int), ('height', int), ('labeled_shapes', List[Union[LabeledShape, TrackedShape]]), ('tags', List[Tag])]) + Frame = NamedTuple('Frame', [('task_id', int), ('subset', str), ('idx', int), ('id', int), ('frame', int), ('name', str), ('width', int), ('height', int), ('labeled_shapes', List[Union[LabeledShape, TrackedShape]]), ('tags', List[Tag])]) def __init__(self, annotation_irs: Mapping[str, AnnotationIR], db_project: Project, host: str, create_callback: Callable = None): self._annotation_irs = annotation_irs @@ -581,6 +581,7 @@ def _init_frame_info(self): else: self._frame_info.update({(task.id, self.rel_frame_id(task.id, db_image.frame)): { "path": mangle_image_name(db_image.path, defaulted_subset, original_names), + "id": db_image.id, "width": db_image.width, "height": db_image.height, "subset": defaulted_subset @@ -683,6 +684,7 @@ def get_frame(task_id: int, idx: int) -> ProjectData.Frame: task_id=task_id, subset=frame_info["subset"], idx=idx, + id=frame_info.get('id',0), frame=abs_frame, name=frame_info["path"], height=frame_info["height"], @@ -807,10 +809,18 @@ def _load_categories(labels: list): for _, attr in label['attributes']: label_categories.attributes.add(attr['name']) + categories[datumaro.AnnotationType.label] = label_categories return categories + @staticmethod + def _load_user_info(meta: dict): + return { + "name": meta['owner']['username'], + "createdAt": meta['created'], + "updatedAt": meta['updated'] + } def _read_cvat_anno(self, cvat_frame_anno: Union[ProjectData.Frame, TaskData.Frame], labels: list): categories = self.categories() @@ -827,7 +837,8 @@ def map_label(name): return label_cat.find(name)[0] class CvatTaskDataExtractor(datumaro.SourceExtractor, CVATDataExtractorMixin): def __init__(self, task_data, include_images=False, format_type=None, dimension=DimensionType.DIM_2D): super().__init__() - self._categories, self._user = self._load_categories(task_data, dimension=dimension) + self._categories = self._load_categories(task_data.meta['task']['labels']) + self._user = self._load_user_info(task_data.meta['task']) if dimension == DimensionType.DIM_3D else {} self._dimension = dimension self._format_type = format_type dm_items = [] @@ -893,11 +904,9 @@ def _make_image(i, **kwargs): attributes["createdAt"] = self._user["createdAt"] attributes["updatedAt"] = self._user["updatedAt"] attributes["labels"] = [] - index = 0 - for _, label in task_data.meta['task']['labels']: - attributes["labels"].append({"label_id": index, "name": label["name"], "color": label["color"]}) + for (idx, (_, label)) in enumerate(task_data.meta['task']['labels']): + attributes["labels"].append({"label_id": idx, "name": label["name"], "color": label["color"]}) attributes["track_id"] = -1 - index += 1 dm_item = datumaro.DatasetItem(id=osp.split(frame_data.name)[-1].split('.')[0], annotations=dm_anno, point_cloud=dm_image[0], related_images=dm_image[1], @@ -907,27 +916,6 @@ def _make_image(i, **kwargs): self._items = dm_items - @staticmethod - def _load_categories(cvat_anno, dimension): # pylint: disable=arguments-differ - categories = {} - - label_categories = datumaro.LabelCategories(attributes=['occluded']) - - user_info = {} - if dimension == DimensionType.DIM_3D: - user_info = {"name": cvat_anno.meta['task']['owner']['username'], - "createdAt": cvat_anno.meta['task']['created'], - "updatedAt": cvat_anno.meta['task']['updated']} - for _, label in cvat_anno.meta['task']['labels']: - label_categories.add(label['name']) - for _, attr in label['attributes']: - label_categories.attributes.add(attr['name']) - - - categories[datumaro.AnnotationType.label] = label_categories - - return categories, user_info - def _read_cvat_anno(self, cvat_frame_anno: TaskData.Frame, labels: list): categories = self.categories() label_cat = categories[datumaro.AnnotationType.label] @@ -940,9 +928,12 @@ def map_label(name): return label_cat.find(name)[0] return convert_cvat_anno_to_dm(cvat_frame_anno, label_attrs, map_label, self._format_type, self._dimension) class CVATProjectDataExtractor(datumaro.Extractor, CVATDataExtractorMixin): - def __init__(self, project_data: ProjectData, include_images: bool = False): + def __init__(self, project_data: ProjectData, include_images: bool = False, format_type: str = None, dimension: DimensionType = DimensionType.DIM_2D): super().__init__() self._categories = self._load_categories(project_data.meta['project']['labels']) + self._user = self._load_user_info(project_data.meta['project']) if dimension == DimensionType.DIM_3D else {} + self._dimension = dimension + self._format_type = format_type dm_items: List[datumaro.DatasetItem] = [] @@ -952,12 +943,28 @@ def __init__(self, project_data: ProjectData, include_images: bool = False): for task in project_data.tasks: is_video = task.mode == 'interpolation' ext_per_task[task.id] = FrameProvider.VIDEO_FRAME_EXT if is_video else '' - if include_images: - frame_provider = FrameProvider(task.data) + if self._dimension == DimensionType.DIM_3D: + def image_maker_factory(task): + images_query = task.data.images.prefetch_related() + def _make_image(i, **kwargs): + loader = osp.join( + task.data.get_upload_dirname(), kwargs['path'], + ) + related_images = [] + image = images_query.get(id=i) + for i in image.related_files.all(): + path = osp.realpath(str(i.path)) + if osp.isfile(path): + related_images.append(path) + return loader, related_images + return _make_image + image_maker_per_task[task.id] = image_maker_factory(task) + elif include_images: if is_video: # optimization for videos: use numpy arrays instead of bytes # some formats or transforms can require image data - def image_maker_factory(frame_provider): + def image_maker_factory(task): + frame_provider = FrameProvider(task.data) def _make_image(i, **kwargs): loader = lambda _: frame_provider.get_frame(i, quality=frame_provider.Quality.ORIGINAL, @@ -966,30 +973,48 @@ def _make_image(i, **kwargs): return _make_image else: # for images use encoded data to avoid recoding - def image_maker_factory(frame_provider): + def image_maker_factory(task): + frame_provider = FrameProvider(task.data) def _make_image(i, **kwargs): loader = lambda _: frame_provider.get_frame(i, quality=frame_provider.Quality.ORIGINAL, out_type=frame_provider.Type.BUFFER)[0].getvalue() return ByteImage(data=loader, **kwargs) return _make_image - image_maker_per_task[task.id] = image_maker_factory(frame_provider) + image_maker_per_task[task.id] = image_maker_factory(task) for frame_data in project_data.group_by_frame(include_empty=True): image_args = { 'path': frame_data.name + ext_per_task[frame_data.task_id], 'size': (frame_data.height, frame_data.width), } - if include_images: + if self._dimension == DimensionType.DIM_3D: + dm_image = image_maker_per_task[frame_data.task_id](frame_data.id, **image_args) + elif include_images: dm_image = image_maker_per_task[frame_data.task_id](frame_data.idx, **image_args) else: dm_image = Image(**image_args) dm_anno = self._read_cvat_anno(frame_data, project_data.meta['project']['labels']) - dm_item = datumaro.DatasetItem(id=osp.splitext(frame_data.name)[0], - annotations=dm_anno, image=dm_image, - subset=frame_data.subset, - attributes={'frame': frame_data.frame} - ) + if self._dimension == DimensionType.DIM_2D: + dm_item = datumaro.DatasetItem(id=osp.splitext(frame_data.name)[0], + annotations=dm_anno, image=dm_image, + subset=frame_data.subset, + attributes={'frame': frame_data.frame} + ) + else: + attributes = {'frame': frame_data.frame} + if format_type == "sly_pointcloud": + attributes["name"] = self._user["name"] + attributes["createdAt"] = self._user["createdAt"] + attributes["updatedAt"] = self._user["updatedAt"] + attributes["labels"] = [] + for (idx, (_, label)) in enumerate(project_data.meta['project']['labels']): + attributes["labels"].append({"label_id": idx, "name": label["name"], "color": label["color"]}) + attributes["track_id"] = -1 + + dm_item = datumaro.DatasetItem(id=osp.splitext(osp.split(frame_data.name)[-1])[0], + annotations=dm_anno, point_cloud=dm_image[0], related_images=dm_image[1], + attributes=attributes, subset=frame_data.subset) dm_items.append(dm_item) self._items = dm_items @@ -1004,11 +1029,11 @@ def __len__(self): return len(self._items) -def GetCVATDataExtractor(instance_data: Union[ProjectData, TaskData], include_images: bool=False): +def GetCVATDataExtractor(instance_data: Union[ProjectData, TaskData], include_images: bool = False, format_type: str = None, dimension: DimensionType = DimensionType.DIM_2D): if isinstance(instance_data, ProjectData): - return CVATProjectDataExtractor(instance_data, include_images) + return CVATProjectDataExtractor(instance_data, include_images, format_type, dimension) else: - return CvatTaskDataExtractor(instance_data, include_images) + return CvatTaskDataExtractor(instance_data, include_images, format_type, dimension) class CvatImportError(Exception): pass diff --git a/cvat/apps/dataset_manager/formats/pointcloud.py b/cvat/apps/dataset_manager/formats/pointcloud.py index 458029a132d..0009cd2f5c8 100644 --- a/cvat/apps/dataset_manager/formats/pointcloud.py +++ b/cvat/apps/dataset_manager/formats/pointcloud.py @@ -7,7 +7,7 @@ from datumaro.components.dataset import Dataset -from cvat.apps.dataset_manager.bindings import (CvatTaskDataExtractor, TaskData, +from cvat.apps.dataset_manager.bindings import (GetCVATDataExtractor, import_dm_annotations) from cvat.apps.dataset_manager.util import make_zip_archive from cvat.apps.engine.models import DimensionType @@ -18,10 +18,7 @@ @exporter(name='Sly Point Cloud Format', ext='ZIP', version='1.0', dimension=DimensionType.DIM_3D) def _export_images(dst_file, task_data, save_images=False): - if not isinstance(task_data, TaskData): - raise Exception("Export to \"Sly Point Cloud\" format is working only with tasks temporarily") - - dataset = Dataset.from_extractors(CvatTaskDataExtractor( + dataset = Dataset.from_extractors(GetCVATDataExtractor( task_data, include_images=save_images, format_type='sly_pointcloud', dimension=DimensionType.DIM_3D), env=dm_env) with TemporaryDirectory() as temp_dir: diff --git a/cvat/apps/dataset_manager/formats/velodynepoint.py b/cvat/apps/dataset_manager/formats/velodynepoint.py index 7384f7beabe..747c47513d8 100644 --- a/cvat/apps/dataset_manager/formats/velodynepoint.py +++ b/cvat/apps/dataset_manager/formats/velodynepoint.py @@ -7,7 +7,7 @@ from datumaro.components.dataset import Dataset -from cvat.apps.dataset_manager.bindings import CvatTaskDataExtractor, TaskData, \ +from cvat.apps.dataset_manager.bindings import GetCVATDataExtractor, \ import_dm_annotations from .registry import dm_env @@ -20,10 +20,7 @@ @exporter(name='Kitti Raw Format', ext='ZIP', version='1.0', dimension=DimensionType.DIM_3D) def _export_images(dst_file, task_data, save_images=False): - if not isinstance(task_data, TaskData): - raise Exception("Export to \"Kitti raw\" format is working only with tasks temporarily") - - dataset = Dataset.from_extractors(CvatTaskDataExtractor( + dataset = Dataset.from_extractors(GetCVATDataExtractor( task_data, include_images=save_images, format_type="kitti_raw", dimension=DimensionType.DIM_3D), env=dm_env) with TemporaryDirectory() as temp_dir: diff --git a/cvat/apps/engine/serializers.py b/cvat/apps/engine/serializers.py index 767b393e1f3..f50e799bf42 100644 --- a/cvat/apps/engine/serializers.py +++ b/cvat/apps/engine/serializers.py @@ -504,13 +504,15 @@ class ProjectWithoutTaskSerializer(serializers.ModelSerializer): owner_id = serializers.IntegerField(write_only=True, allow_null=True, required=False) assignee = BasicUserSerializer(allow_null=True, required=False) assignee_id = serializers.IntegerField(write_only=True, allow_null=True, required=False) + task_subsets = serializers.ListField(child=serializers.CharField(), required=False) training_project = TrainingProjectSerializer(required=False, allow_null=True) + dimension = serializers.CharField(max_length=16, required=False) class Meta: model = models.Project fields = ('url', 'id', 'name', 'labels', 'tasks', 'owner', 'assignee', 'owner_id', 'assignee_id', - 'bug_tracker', 'created_date', 'updated_date', 'status', 'training_project') - read_only_fields = ('created_date', 'updated_date', 'status', 'owner', 'asignee') + 'bug_tracker', 'task_subsets', 'created_date', 'updated_date', 'status', 'training_project', 'dimension') + read_only_fields = ('created_date', 'updated_date', 'status', 'owner', 'asignee', 'task_subsets', 'dimension') ordering = ['-id'] @@ -519,6 +521,7 @@ def to_representation(self, instance): task_subsets = set(instance.tasks.values_list('subset', flat=True)) task_subsets.discard('') response['task_subsets'] = list(task_subsets) + response['dimension'] = instance.tasks.first().dimension if instance.tasks.count() else None return response class ProjectSerializer(ProjectWithoutTaskSerializer): @@ -580,7 +583,9 @@ def validate_labels(self, value): return value def to_representation(self, instance): - return serializers.ModelSerializer.to_representation(self, instance) # ignoring subsets here + response = serializers.ModelSerializer.to_representation(self, instance) # ignoring subsets here + response['dimension'] = instance.tasks.first().dimension if instance.tasks.count() else None + return response class ExceptionSerializer(serializers.Serializer): system = serializers.CharField(max_length=255) diff --git a/cvat/apps/engine/views.py b/cvat/apps/engine/views.py index 2cd724edcab..afe9ef504fa 100644 --- a/cvat/apps/engine/views.py +++ b/cvat/apps/engine/views.py @@ -239,6 +239,8 @@ class ProjectViewSet(auth.ProjectGetQuerySetMixin, viewsets.ModelViewSet): http_method_names = ['get', 'post', 'head', 'patch', 'delete'] def get_serializer_class(self): + if self.request.path.endswith('tasks'): + return TaskSerializer if self.request.query_params and self.request.query_params.get("names_only") == "true": return ProjectSearchSerializer if self.request.query_params and self.request.query_params.get("without_tasks") == "true": diff --git "a/tests/cypress/integration/canvas3d_functionality/case_85_canvas3d_functionality_cuboid_\321\201ancel_drawing.js" "b/tests/cypress/integration/canvas3d_functionality/case_85_canvas3d_functionality_cuboid_\321\201ancel_drawing.js" index fbaa436d7c1..8302d8b5ac1 100644 --- "a/tests/cypress/integration/canvas3d_functionality/case_85_canvas3d_functionality_cuboid_\321\201ancel_drawing.js" +++ "b/tests/cypress/integration/canvas3d_functionality/case_85_canvas3d_functionality_cuboid_\321\201ancel_drawing.js" @@ -8,10 +8,11 @@ import { taskName, labelName } from '../../support/const_canvas3d'; context('Canvas 3D functionality. Cancel drawing.', () => { const caseId = '85'; - const screenshotsPath = 'cypress/screenshots/canvas3d_functionality/case_85_canvas3d_functionality_cuboid_сancel_drawing.js'; + const screenshotsPath = + 'cypress/screenshots/canvas3d_functionality/case_85_canvas3d_functionality_cuboid_сancel_drawing.js'; before(() => { - cy.openTask(taskName) + cy.openTask(taskName); cy.openJob(); cy.wait(1000); // Waiting for the point cloud to display });