Merge branch 'develop' into zm/refactor-quality-reports-impl

.gitignore

@@ -20,8 +20,8 @@ __pycache__
 .coverage
 .husky/
 .python-version
-tmp*cvat/
-temp*/
+/tmp*cvat/
+/temp*/
 
 # Ignore generated test files
 docker-compose.tests.yml

README.md

@@ -207,7 +207,6 @@ up to 10x. Here is a list of the algorithms we support, and the platforms they c
 | [HRNet](/serverless/pytorch/saic-vul/hrnet/nuclio)                                                      | interactor | PyTorch    |     | ✔️  |
 | [Inside-Outside Guidance](/serverless/pytorch/shiyinzhang/iog/nuclio)                                   | interactor | PyTorch    | ✔️  |     |
 | [Faster RCNN](/serverless/tensorflow/faster_rcnn_inception_v2_coco/nuclio)                              | detector   | TensorFlow | ✔️  | ✔️  |
-| [Mask RCNN](/serverless/tensorflow/matterport/mask_rcnn/nuclio)                                         | detector   | TensorFlow | ✔️  | ✔️  |
 | [RetinaNet](serverless/pytorch/facebookresearch/detectron2/retinanet_r101/nuclio)                       | detector   | PyTorch    | ✔️  | ✔️  |
 | [Face Detection](/serverless/openvino/omz/intel/face-detection-0205/nuclio)                             | detector   | OpenVINO   | ✔️  |     |
 

changelog.d/20250128_144218_roman_aa_fun_label_types.md

@@ -0,0 +1,5 @@
+### Added
+
+- \[SDK\] The shapes output by auto-annotation functions are now checked
+  for compatibility with the function's and the task's label specs
+  (<https://github.com/cvat-ai/cvat/pull/9005>)

changelog.d/20250129_140847_klakhov_add_detector_threshold.md

@@ -0,0 +1,4 @@
+### Added
+
+- A `threshold` parameter to UI detector runner
+  (<https://github.com/cvat-ai/cvat/pull/9011>)

changelog.d/20250130_185457_roman.md

@@ -0,0 +1,5 @@
+### Fixed
+
+- \[Compose\] An outdated version of Traefik is no longer used in
+  deployments with HTTPS enabled
+  (<https://github.com/cvat-ai/cvat/pull/9028>)

cvat-sdk/cvat_sdk/auto_annotation/driver.py

@@ -56,12 +56,28 @@ class _AnnotationMapper:
     class _LabelIdMapping:
         id: int
         sublabels: Mapping[int, Optional[_AnnotationMapper._SublabelIdMapping]]
-        expected_num_elements: int = 0
+        expected_num_elements: int
+        expected_type: str
 
     _SpecIdMapping: TypeAlias = Mapping[int, Optional[_LabelIdMapping]]
 
     _spec_id_mapping: _SpecIdMapping
 
+    def _get_expected_function_output_type(self, fun_label, ds_label):
+        fun_output_type = getattr(fun_label, "type", "any")
+        if fun_output_type == "any":
+            return ds_label.type
+
+        if self._conv_mask_to_poly and fun_output_type == "mask":
+            fun_output_type = "polygon"
+
+        if not self._are_label_types_compatible(fun_output_type, ds_label.type):
+            raise BadFunctionError(
+                f"label {fun_label.name!r} has type {fun_output_type!r} in the function,"
+                f" but {ds_label.type!r} in the dataset"
+            )
+        return fun_output_type
+
     def _build_label_id_mapping(
         self,
         fun_label: models.ILabel,
@@ -70,36 +86,37 @@ def _build_label_id_mapping(
         label_nm: _LabelNameMapping,
         allow_unmatched_labels: bool,
     ) -> Optional[_LabelIdMapping]:
-        sl_map = {}
-
-        if getattr(fun_label, "sublabels", []):
-            ds_sublabels_by_name = {ds_sl.name: ds_sl for ds_sl in ds_label.sublabels}
-
-            def sublabel_mapping(fun_sl: models.ILabel) -> Optional[int]:
-                sublabel_nm = label_nm.map_sublabel(fun_sl.name)
-                if sublabel_nm is None:
-                    return None
-
-                ds_sl = ds_sublabels_by_name.get(sublabel_nm.name)
-                if not ds_sl:
-                    if not allow_unmatched_labels:
-                        raise BadFunctionError(
-                            f"sublabel {fun_sl.name!r} of label {fun_label.name!r} is not in dataset"
-                        )
-
-                    self._logger.info(
-                        "sublabel %r of label %r is not in dataset; any annotations using it will be ignored",
-                        fun_sl.name,
-                        fun_label.name,
+        ds_sublabels_by_name = {ds_sl.name: ds_sl for ds_sl in ds_label.sublabels}
+
+        def sublabel_mapping(fun_sl: models.ILabel) -> Optional[int]:
+            sublabel_nm = label_nm.map_sublabel(fun_sl.name)
+            if sublabel_nm is None:
+                return None
+
+            ds_sl = ds_sublabels_by_name.get(sublabel_nm.name)
+            if not ds_sl:
+                if not allow_unmatched_labels:
+                    raise BadFunctionError(
+                        f"sublabel {fun_sl.name!r} of label {fun_label.name!r} is not in dataset"
                     )
-                    return None
 
-                return ds_sl.id
+                self._logger.info(
+                    "sublabel %r of label %r is not in dataset; any annotations using it will be ignored",
+                    fun_sl.name,
+                    fun_label.name,
+                )
+                return None
 
-            sl_map = {fun_sl.id: sublabel_mapping(fun_sl) for fun_sl in fun_label.sublabels}
+            return ds_sl.id
 
         return self._LabelIdMapping(
-            ds_label.id, sublabels=sl_map, expected_num_elements=len(ds_label.sublabels)
+            ds_label.id,
+            sublabels={
+                fun_sl.id: sublabel_mapping(fun_sl)
+                for fun_sl in getattr(fun_label, "sublabels", [])
+            },
+            expected_num_elements=len(ds_label.sublabels),
+            expected_type=self._get_expected_function_output_type(fun_label, ds_label),
         )
 
     def _build_spec_id_mapping(
@@ -254,6 +271,12 @@ def _remap_shape(self, shape: models.LabeledShapeRequest, ds_frame: int) -> bool
 
         shape.label_id = label_id_mapping.id
 
+        if not self._are_label_types_compatible(shape.type.value, label_id_mapping.expected_type):
+            raise BadFunctionError(
+                f"function output shape of type {shape.type.value!r}"
+                f" (expected {label_id_mapping.expected_type!r})"
+            )
+
         if shape.type.value == "mask" and self._conv_mask_to_poly:
             raise BadFunctionError("function output mask shape despite conv_mask_to_poly=True")
 
@@ -269,6 +292,11 @@ def _remap_shape(self, shape: models.LabeledShapeRequest, ds_frame: int) -> bool
     def validate_and_remap(self, shapes: list[models.LabeledShapeRequest], ds_frame: int) -> None:
         shapes[:] = [shape for shape in shapes if self._remap_shape(shape, ds_frame)]
 
+    @staticmethod
+    def _are_label_types_compatible(source_type: str, destination_type: str) -> bool:
+        assert source_type != "any"
+        return destination_type == "any" or destination_type == source_type
+
 
 @attrs.frozen(kw_only=True)
 class _DetectionFunctionContextImpl(DetectionFunctionContext):

cvat-sdk/cvat_sdk/auto_annotation/functions/_torchvision.py

@@ -10,6 +10,8 @@
 
 
 class TorchvisionFunction:
+    _label_type = "any"
+
     def __init__(self, model_name: str, weights_name: str = "DEFAULT", **kwargs) -> None:
         weights_enum = torchvision.models.get_model_weights(model_name)
         self._weights = weights_enum[weights_name]
@@ -21,7 +23,7 @@ def __init__(self, model_name: str, weights_name: str = "DEFAULT", **kwargs) ->
     def spec(self) -> cvataa.DetectionFunctionSpec:
         return cvataa.DetectionFunctionSpec(
             labels=[
-                cvataa.label_spec(cat, i)
+                cvataa.label_spec(cat, i, type=self._label_type)
                 for i, cat in enumerate(self._weights.meta["categories"])
                 if cat != "N/A"
             ]

cvat-sdk/cvat_sdk/auto_annotation/functions/torchvision_detection.py

@@ -11,6 +11,8 @@
 
 
 class _TorchvisionDetectionFunction(TorchvisionFunction):
+    _label_type = "rectangle"
+
     def detect(
         self, context: cvataa.DetectionFunctionContext, image: PIL.Image.Image
     ) -> list[models.LabeledShapeRequest]:

cvat-sdk/cvat_sdk/auto_annotation/functions/torchvision_instance_segmentation.py

@@ -50,6 +50,8 @@ def _generate_shapes(
 
 
 class _TorchvisionInstanceSegmentationFunction(TorchvisionFunction):
+    _label_type = "mask"
+
     def detect(
         self, context: cvataa.DetectionFunctionContext, image: PIL.Image.Image
     ) -> list[models.LabeledShapeRequest]:

cvat-ui/src/components/job-item/job-actions-menu.tsx

@@ -17,60 +17,72 @@ interface Props {
     job: Job;
 }
 
+export enum Actions {
+    TASK = 'task',
+    PROJECT = 'project',
+    BUG_TRACKER = 'bug_tracker',
+    IMPORT_JOB = 'import_job',
+    EXPORT_JOB = 'export_job',
+    VIEW_ANALYTICS = 'view_analytics',
+    DELETE = 'delete',
+}
+
 function JobActionsMenu(props: Props): JSX.Element {
     const { job } = props;
 
     const dispatch = useDispatch();
     const history = useHistory();
 
-    const onDelete = useCallback(() => {
-        Modal.confirm({
-            title: `The job ${job.id} will be deleted`,
-            content: 'All related data (annotations) will be lost. Continue?',
-            className: 'cvat-modal-confirm-delete-job',
-            onOk: () => {
-                dispatch(deleteJobAsync(job));
-            },
-            okButtonProps: {
-                type: 'primary',
-                danger: true,
-            },
-            okText: 'Delete',
-        });
-    }, [job]);
+    const onClickMenu = useCallback(
+        (action: MenuInfo) => {
+            if (action.key === Actions.TASK) {
+                history.push(`/tasks/${job.taskId}`);
+            } else if (action.key === Actions.PROJECT) {
+                history.push(`/projects/${job.projectId}`);
+            } else if (action.key === Actions.BUG_TRACKER) {
+                if (job.bugTracker) {
+                    window.open(job.bugTracker, '_blank', 'noopener noreferrer');
+                }
+            } else if (action.key === Actions.IMPORT_JOB) {
+                dispatch(importActions.openImportDatasetModal(job));
+            } else if (action.key === Actions.EXPORT_JOB) {
+                dispatch(exportActions.openExportDatasetModal(job));
+            } else if (action.key === Actions.VIEW_ANALYTICS) {
+                history.push(`/tasks/${job.taskId}/jobs/${job.id}/analytics`);
+            } else if (action.key === Actions.DELETE) {
+                Modal.confirm({
+                    title: `The job ${job.id} will be deleted`,
+                    content: 'All related data (annotations) will be lost. Continue?',
+                    className: 'cvat-modal-confirm-delete-job',
+                    onOk: () => {
+                        dispatch(deleteJobAsync(job));
+                    },
+                    okButtonProps: {
+                        type: 'primary',
+                        danger: true,
+                    },
+                    okText: 'Delete',
+                });
+            }
+        },
+        [job],
+    );
 
     return (
         <Menu
             className='cvat-job-item-menu'
-            onClick={(action: MenuInfo) => {
-                if (action.key === 'task') {
-                    history.push(`/tasks/${job.taskId}`);
-                } else if (action.key === 'project') {
-                    history.push(`/projects/${job.projectId}`);
-                } else if (action.key === 'bug_tracker') {
-                    if (job.bugTracker) {
-                        window.open(job.bugTracker, '_blank', 'noopener noreferrer');
-                    }
-                } else if (action.key === 'import_job') {
-                    dispatch(importActions.openImportDatasetModal(job));
-                } else if (action.key === 'export_job') {
-                    dispatch(exportActions.openExportDatasetModal(job));
-                } else if (action.key === 'view_analytics') {
-                    history.push(`/tasks/${job.taskId}/jobs/${job.id}/analytics`);
-                }
-            }}
+            onClick={onClickMenu}
         >
-            <Menu.Item key='task' disabled={job.taskId === null}>Go to the task</Menu.Item>
-            <Menu.Item key='project' disabled={job.projectId === null}>Go to the project</Menu.Item>
-            <Menu.Item key='bug_tracker' disabled={!job.bugTracker}>Go to the bug tracker</Menu.Item>
-            <Menu.Item key='import_job'>Import annotations</Menu.Item>
-            <Menu.Item key='export_job'>Export annotations</Menu.Item>
-            <Menu.Item key='view_analytics'>View analytics</Menu.Item>
+            <Menu.Item key={Actions.TASK} disabled={job.taskId === null}>Go to the task</Menu.Item>
+            <Menu.Item key={Actions.PROJECT} disabled={job.projectId === null}>Go to the project</Menu.Item>
+            <Menu.Item key={Actions.BUG_TRACKER} disabled={!job.bugTracker}>Go to the bug tracker</Menu.Item>
+            <Menu.Item key={Actions.IMPORT_JOB}>Import annotations</Menu.Item>
+            <Menu.Item key={Actions.EXPORT_JOB}>Export annotations</Menu.Item>
+            <Menu.Item key={Actions.VIEW_ANALYTICS}>View analytics</Menu.Item>
             <Menu.Divider />
             <Menu.Item
-                key='delete'
+                key={Actions.DELETE}
                 disabled={job.type !== JobType.GROUND_TRUTH}
-                onClick={() => onDelete()}
             >
                 Delete
             </Menu.Item>

cvat-ui/src/components/labels-editor/label-form.tsx

@@ -425,7 +425,7 @@ export default class LabelForm extends React.Component<Props> {
                                     className: 'cvat-modal-delete-label-attribute',
                                     icon: <ExclamationCircleOutlined />,
                                     title: `Do you want to remove the "${attr.name}" attribute?`,
-                                    content: 'This action is undone. All annotations associated to the attribute will be removed',
+                                    content: 'This action cannot be undone. All annotations associated to the attribute will be removed',
                                     type: 'warning',
                                     okButtonProps: { type: 'primary', danger: true },
                                     onOk: () => {

cvat-ui/src/components/labels-editor/labels-editor.tsx

@@ -162,7 +162,7 @@ export default class LabelsEditor extends React.PureComponent<LabelsEditorProps,
                 className: 'cvat-modal-delete-label',
                 icon: <ExclamationCircleOutlined />,
                 title: `Do you want to delete "${label.name}" label?`,
-                content: 'This action is undone. All annotations associated to the label will be deleted.',
+                content: 'This action cannot be undone. All annotations associated to the label will be deleted.',
                 type: 'warning',
                 okButtonProps: { type: 'primary', danger: true },
                 onOk() {

cvat-ui/src/components/model-runner-modal/detector-runner.tsx

@@ -13,7 +13,7 @@ import Button from 'antd/lib/button';
 import Switch from 'antd/lib/switch';
 import Tag from 'antd/lib/tag';
 import notification from 'antd/lib/notification';
-import { ArrowRightOutlined } from '@ant-design/icons';
+import { ArrowRightOutlined, QuestionCircleOutlined } from '@ant-design/icons';
 
 import CVATTooltip from 'components/common/cvat-tooltip';
 import { clamp } from 'utils/math';
@@ -72,6 +72,7 @@ function DetectorRunner(props: Props): JSX.Element {
     const [cleanup, setCleanup] = useState<boolean>(false);
     const [mapping, setMapping] = useState<FullMapping>([]);
     const [convertMasksToPolygons, setConvertMasksToPolygons] = useState<boolean>(false);
+    const [detectorThreshold, setDetectorThreshold] = useState<number | null>(null);
     const [modelLabels, setModelLabels] = useState<LabelInterface[]>([]);
     const [taskLabels, setTaskLabels] = useState<LabelInterface[]>([]);
 
@@ -179,6 +180,29 @@ function DetectorRunner(props: Props): JSX.Element {
                     <Text>Clean previous annotations</Text>
                 </div>
             )}
+            {isDetector && (
+                <div className='cvat-detector-runner-threshold-wrapper'>
+                    <Row align='middle' justify='start'>
+                        <Col>
+                            <InputNumber
+                                min={0.01}
+                                step={0.01}
+                                max={1}
+                                value={detectorThreshold}
+                                onChange={(value: number | null) => {
+                                    setDetectorThreshold(value);
+                                }}
+                            />
+                        </Col>
+                        <Col>
+                            <Text>Threshold</Text>
+                            <CVATTooltip title='Minimum confidence threshold for detections. Leave empty to use the default value specified in the model settings'>
+                                <QuestionCircleOutlined className='cvat-info-circle-icon' />
+                            </CVATTooltip>
+                        </Col>
+                    </Row>
+                </div>
+            )}
             {isReId ? (
                 <div>
                     <Row align='middle' justify='start'>
@@ -236,6 +260,7 @@ function DetectorRunner(props: Props): JSX.Element {
                                     mapping: serverMapping,
                                     cleanup,
                                     conv_mask_to_poly: convertMasksToPolygons,
+                                    ...(detectorThreshold !== null ? { threshold: detectorThreshold } : {}),
                                 });
                             } else if (model.kind === ModelKind.REID) {
                                 runInference(model, { threshold, max_distance: distance });

cvat-ui/src/components/model-runner-modal/styles.scss

@@ -105,8 +105,15 @@
 }
 
 .cvat-detector-runner-clean-previous-annotations-wrapper,
-.cvat-detector-runner-convert-masks-to-polygons-wrapper {
-    span {
+.cvat-detector-runner-convert-masks-to-polygons-wrapper,
+.cvat-detector-runner-threshold-wrapper {
+    .ant-typography {
+        margin-left: $grid-unit-size;
+    }
+}
+
+.cvat-detector-runner-threshold-wrapper {
+    .cvat-info-circle-icon {
         margin-left: $grid-unit-size;
     }
 }