Merge branch 'main' into otx-decoupling

.github/workflows/build-package-internal-pypi.yaml

@@ -6,6 +6,9 @@ on:
   release:
     types: [published]
 
+permissions:
+  contents: read
+
 jobs:
   build:
     uses: ./.github/workflows/build-package.yaml

.github/workflows/build-package-pypi.yaml

@@ -3,6 +3,9 @@ name: Publish package [PyPI]
 on:
   workflow_dispatch:
 
+permissions:
+  contents: read
+
 jobs:
   build:
     uses: ./.github/workflows/build-package.yaml

.github/workflows/build-package-test-pypi.yaml

@@ -6,6 +6,9 @@ on:
   release:
     types: [published]
 
+permissions:
+  contents: read
+
 jobs:
   build:
     uses: ./.github/workflows/build-package.yaml

.github/workflows/build-package.yaml

@@ -23,6 +23,9 @@ env:
   PYPI_PORT: ${{ secrets.PYPI_PORT }}
   ENABLE_DEV_DEPENDENCIES: ${{ inputs.enable_dev_dependencies }}
 
+permissions:
+  contents: read
+
 jobs:
   build_sdk:
     runs-on: [self-hosted, sdk-runner]

.github/workflows/nightly-tests-geti-develop.yaml

@@ -6,6 +6,9 @@ on:
   schedule: # Execute tests at midnight every day
     - cron: "0 0 * * *"
 
+permissions:
+  contents: read
+
 jobs:
   build:
     uses: ./.github/workflows/nightly-tests.yaml

.github/workflows/nightly-tests-geti-latest.yaml

@@ -6,6 +6,9 @@ on:
   schedule: # Execute tests at midnight every day
     - cron: "0 0 * * *"
 
+permissions:
+  contents: read
+
 jobs:
   build:
     uses: ./.github/workflows/nightly-tests.yaml

.github/workflows/nightly-tests-geti-mvp.yaml

@@ -6,6 +6,9 @@ on:
   schedule: # Execute tests at midnight every day
     - cron: "0 0 * * *"
 
+permissions:
+  contents: read
+
 jobs:
   build:
     uses: ./.github/workflows/nightly-tests.yaml

.github/workflows/nightly-tests.yaml

@@ -37,6 +37,9 @@ env:
   CONDA_ENV: sc_sdk_nightly_test_environment
   PYTHON_VERSION: 3.8
 
+permissions:
+  contents: read
+
 jobs:
   nightly_tests:
     runs-on: [self-hosted, sdk-runner]

.github/workflows/pre-merge-tests.yml

@@ -14,6 +14,11 @@ env:
   REPORT_DIRECTORY: reports
   PYTHONUTF8: '1'
 
+permissions:
+  contents: read
+  checks: write
+  actions: write
+
 jobs:
   pr_tests:
     runs-on: ${{ matrix.os }}

.github/workflows/scorecard.yml

@@ -0,0 +1,72 @@
+# This workflow uses actions that are not certified by GitHub. They are provided
+# by a third-party and are governed by separate terms of service, privacy
+# policy, and support documentation.
+
+name: Scorecard supply-chain security
+on:
+  # For Branch-Protection check. Only the default branch is supported. See
+  # https://github.com/ossf/scorecard/blob/main/docs/checks.md#branch-protection
+  branch_protection_rule:
+  # To guarantee Maintained check is occasionally updated. See
+  # https://github.com/ossf/scorecard/blob/main/docs/checks.md#maintained
+  schedule:
+    - cron: '18 5 * * 2'
+  push:
+    branches: [ "main" ]
+
+# Declare default permissions as read only.
+permissions: read-all
+
+jobs:
+  analysis:
+    name: Scorecard analysis
+    runs-on: ubuntu-latest
+    permissions:
+      # Needed to upload the results to code-scanning dashboard.
+      security-events: write
+      # Needed to publish results and get a badge (see publish_results below).
+      id-token: write
+      # Uncomment the permissions below if installing in a private repository.
+      # contents: read
+      # actions: read
+
+    steps:
+      - name: "Checkout code"
+        uses: actions/checkout@93ea575cb5d8a053eaa0ac8fa3b40d7e05a33cc8 # v3.1.0
+        with:
+          persist-credentials: false
+
+      - name: "Run analysis"
+        uses: ossf/scorecard-action@e38b1902ae4f44df626f11ba0734b14fb91f8f86 # v2.1.2
+        with:
+          results_file: results.sarif
+          results_format: sarif
+          # (Optional) "write" PAT token. Uncomment the `repo_token` line below if:
+          # - you want to enable the Branch-Protection check on a *public* repository, or
+          # - you are installing Scorecard on a *private* repository
+          # To create the PAT, follow the steps in https://github.com/ossf/scorecard-action#authentication-with-pat.
+          # repo_token: ${{ secrets.SCORECARD_TOKEN }}
+
+          # Public repositories:
+          #   - Publish results to OpenSSF REST API for easy access by consumers
+          #   - Allows the repository to include the Scorecard badge.
+          #   - See https://github.com/ossf/scorecard-action#publishing-results.
+          # For private repositories:
+          #   - `publish_results` will always be set to `false`, regardless
+          #     of the value entered here.
+          publish_results: true
+
+      # Upload the results as artifacts (optional). Commenting out will disable uploads of run results in SARIF
+      # format to the repository Actions tab.
+      - name: "Upload artifact"
+        uses: actions/upload-artifact@3cea5372237819ed00197afe530f5a7ea3e805c8 # v3.1.0
+        with:
+          name: SARIF file
+          path: results.sarif
+          retention-days: 5
+
+      # Upload the results to GitHub's code scanning dashboard.
+      - name: "Upload to code-scanning"
+        uses: github/codeql-action/upload-sarif@17573ee1cc1b9d061760f3a006fc4aac4f944fd5 # v2.2.4
+        with:
+          sarif_file: results.sarif

.github/workflows/security-scan.yaml

@@ -11,6 +11,9 @@ env:
   SNYK_TOKEN: ${{ secrets.SNYK_TOKEN }}
   REPORT_DIRECTORY: reports
 
+permissions:
+  contents: read
+
 jobs:
   security:
     runs-on: [self-hosted, sdk-runner]

geti_sdk/deployment/legacy_converters/__init__.py

@@ -17,6 +17,24 @@
 versions of the Intel® Geti™ platform, i.e. v1.8 and below.
 """
 
-from .legacy_anomaly_converter import AnomalyClassificationToAnnotationConverter
+from .legacy_anomaly_converter import (
+    AnomalyClassificationToAnnotationConverter,
+    AnomalyDetectionToAnnotationConverter,
+    AnomalySegmentationToAnnotationConverter,
+)
+from .legacy_classification_converter import ClassificationToAnnotationConverter
+from .legacy_detection_converter import RotatedRectToAnnotationConverter
+from .legacy_segmentation_converter import (
+    MaskToAnnotationConverter,
+    SegmentationToAnnotationConverter,
+)
 
-__all__ = ["AnomalyClassificationToAnnotationConverter"]
+__all__ = [
+    "AnomalyClassificationToAnnotationConverter",
+    "AnomalyDetectionToAnnotationConverter",
+    "AnomalySegmentationToAnnotationConverter",
+    "ClassificationToAnnotationConverter",
+    "SegmentationToAnnotationConverter",
+    "MaskToAnnotationConverter",
+    "RotatedRectToAnnotationConverter",
+]

geti_sdk/deployment/legacy_converters/legacy_anomaly_converter.py

@@ -14,6 +14,7 @@
 from typing import Any, Dict
 
 import numpy as np
+from openvino.model_api.models.utils import AnomalyResult
 from otx.api.entities.annotation import (
     Annotation,
     AnnotationSceneEntity,
@@ -25,6 +26,7 @@
 from otx.api.usecases.exportable_code.prediction_to_annotation_converter import (
     IPredictionToAnnotationConverter,
 )
+from otx.api.utils.segmentation_utils import create_annotation_from_segmentation_map
 
 
 class AnomalyClassificationToAnnotationConverter(IPredictionToAnnotationConverter):
@@ -63,3 +65,102 @@ def convert_to_annotation(
         return AnnotationSceneEntity(
             kind=AnnotationSceneKind.PREDICTION, annotations=annotations
         )
+
+
+class AnomalySegmentationToAnnotationConverter(IPredictionToAnnotationConverter):
+    """
+    Convert AnomalySegmentation Predictions ModelAPI to Annotations.
+
+    :param labels: Label Schema containing the label info of the task
+    """
+
+    def __init__(self, label_schema: LabelSchemaEntity):
+        labels = label_schema.get_labels(include_empty=False)
+        self.normal_label = [label for label in labels if not label.is_anomalous][0]
+        self.anomalous_label = [label for label in labels if label.is_anomalous][0]
+        self.label_map = {0: self.normal_label, 1: self.anomalous_label}
+
+    def convert_to_annotation(
+        self, predictions: AnomalyResult, metadata: Dict[str, Any]
+    ) -> AnnotationSceneEntity:
+        """
+        Convert predictions to OTX Annotation Scene using the metadata.
+
+        :param predictions: Raw predictions from the model.
+        :param metadata: Variable containing metadata information.
+        :return: OTX annotation scene entity object.
+        """
+        assert predictions.pred_mask is not None
+        assert predictions.anomaly_map is not None
+        annotations = create_annotation_from_segmentation_map(
+            predictions.pred_mask, predictions.anomaly_map / 255.0, self.label_map
+        )
+        if len(annotations) == 0:
+            # TODO: add confidence to this label
+            annotations = [
+                Annotation(
+                    Rectangle.generate_full_box(),
+                    labels=[ScoredLabel(label=self.normal_label, probability=1.0)],
+                )
+            ]
+        return AnnotationSceneEntity(
+            kind=AnnotationSceneKind.PREDICTION, annotations=annotations
+        )
+
+
+class AnomalyDetectionToAnnotationConverter(IPredictionToAnnotationConverter):
+    """
+    Convert Anomaly Detection Predictions ModelAPI to Annotations.
+
+    :param labels: Label Schema containing the label info of the task
+    """
+
+    def __init__(self, label_schema: LabelSchemaEntity):
+        labels = label_schema.get_labels(include_empty=False)
+        self.normal_label = [label for label in labels if not label.is_anomalous][0]
+        self.anomalous_label = [label for label in labels if label.is_anomalous][0]
+        self.label_map = {0: self.normal_label, 1: self.anomalous_label}
+
+    def convert_to_annotation(
+        self, predictions: AnomalyResult, metadata: Dict[str, Any]
+    ) -> AnnotationSceneEntity:
+        """
+        Convert predictions to OTX Annotation Scene using the metadata.
+
+        :param predictions: Raw predictions from the model.
+        :param metadata: Variable containing metadata information.
+        :return: OTX annotation scene entity object.
+        """
+        assert predictions.pred_boxes is not None
+        assert predictions.pred_score is not None
+        assert predictions.pred_mask is not None
+        annotations = []
+        image_h, image_w = predictions.pred_mask.shape
+        for box in predictions.pred_boxes:
+            annotations.append(
+                Annotation(
+                    Rectangle(
+                        box[0] / image_w,
+                        box[1] / image_h,
+                        box[2] / image_w,
+                        box[3] / image_h,
+                    ),
+                    labels=[
+                        ScoredLabel(
+                            label=self.anomalous_label,
+                            probability=predictions.pred_score,
+                        )
+                    ],
+                )
+            )
+        if len(annotations) == 0:
+            # TODO: add confidence to this label
+            annotations = [
+                Annotation(
+                    Rectangle.generate_full_box(),
+                    labels=[ScoredLabel(label=self.normal_label, probability=1.0)],
+                )
+            ]
+        return AnnotationSceneEntity(
+            kind=AnnotationSceneKind.PREDICTION, annotations=annotations
+        )