refactoring detectors

giskard_vision/core/detectors/transformation_blurring_detector.py → giskard_vision/core/detectors/blur_detector.py

@@ -1,20 +1,21 @@
 from giskard_vision.core.dataloaders.wrappers import BlurredDataLoader
 
-from ...core.detectors.decorator import maybe_detector
+from .decorator import maybe_detector
 from .perturbation import PerturbationBaseDetector
 
 
 @maybe_detector(
-    "blurring",
+    "blur",
     tags=[
+        "blur",
         "vision",
         "robustness",
         "image_classification",
         "landmark_detection",
         "object_detection",
     ],
 )
-class TransformationBlurringDetector(PerturbationBaseDetector):
+class BlurDetector(PerturbationBaseDetector):
     """
     Detector that evaluates models performance on blurred images
     """

giskard_vision/core/detectors/transformation_color_detector.py → giskard_vision/core/detectors/color_detector.py

@@ -1,21 +1,21 @@
 from giskard_vision.core.dataloaders.wrappers import ColoredDataLoader
 
-from ...core.detectors.decorator import maybe_detector
+from .decorator import maybe_detector
 from .perturbation import PerturbationBaseDetector
 
 
 @maybe_detector(
-    "coloring",
+    "color",
     tags=[
         "vision",
         "robustness",
         "image_classification",
         "landmark_detection",
         "object_detection",
-        "coloring",
+        "color",
     ],
 )
-class TransformationColorDetector(PerturbationBaseDetector):
+class ColorDetector(PerturbationBaseDetector):
     """
     Detector that evaluates models performance depending on images in grayscale
     """

giskard_vision/core/detectors/metadata_scan_detector.py → giskard_vision/core/detectors/metadata_detector.py

@@ -16,7 +16,7 @@ class Surrogate:
     surrogate: Optional[Callable] = None
 
 
-class MetaDataScanDetector(DetectorVisionBase):
+class MetaDataDetector(DetectorVisionBase):
     """
     Detector based on Giskard scan that looks for issues based on metadata
 

giskard_vision/core/detectors/transformation_noise_detector.py → giskard_vision/core/detectors/noise_detector.py

@@ -1,6 +1,6 @@
 from giskard_vision.core.dataloaders.wrappers import NoisyDataLoader
 
-from ...core.detectors.decorator import maybe_detector
+from .decorator import maybe_detector
 from .perturbation import PerturbationBaseDetector
 
 
@@ -15,7 +15,7 @@
         "noise",
     ],
 )
-class TransformationNoiseDetector(PerturbationBaseDetector):
+class NoiseDetector(PerturbationBaseDetector):
     """
     Detector that evaluates models performance on noisy images
     """

giskard_vision/image_classification/detectors/__init__.py

@@ -1,5 +1,5 @@
-from .metadata_detector import MetaDataScanDetectorClassification
+from .metadata_detector import MetaDataDetectorClassification
 
 __all__ = [
-    "MetaDataScanDetectorClassification",
+    "MetaDataDetectorClassification",
 ]

giskard_vision/image_classification/detectors/metadata_detector.py

@@ -1,9 +1,9 @@
-from giskard_vision.core.detectors.metadata_scan_detector import MetaDataScanDetector
+from giskard_vision.core.detectors.metadata_detector import MetaDataDetector
 
 from ...core.detectors.decorator import maybe_detector
 from .specs import DetectorSpecs
 
 
 @maybe_detector("metadata_classification", tags=["vision", "image_classification", "metadata"])
-class MetaDataScanDetectorClassification(DetectorSpecs, MetaDataScanDetector):
+class MetaDataDetectorClassification(DetectorSpecs, MetaDataDetector):
     pass

giskard_vision/landmark_detection/detectors/__init__.py

@@ -1,9 +1,9 @@
-from .cropping_detector import CroppingDetectorLandmark
-from .metadata_detector import MetaDataScanDetectorLandmark
-from .transformation_resize_detector import TransformationResizeDetectorLandmark
+from .crop_detector import CropDetectorLandmarkDetection
+from .metadata_detector import MetaDataDetectorLandmarkDetection
+from .resize_detector import TransformationResizeDetectorLandmarkDetection
 
 __all__ = [
-    "CroppingDetectorLandmark",
-    "TransformationResizeDetectorLandmark",
-    "MetaDataScanDetectorLandmark",
+    "CropDetectorLandmarkDetection",
+    "TransformationResizeDetectorLandmarkDetection",
+    "MetaDataDetectorLandmarkDetection",
 ]

giskard_vision/landmark_detection/detectors/cropping_detector.py → giskard_vision/landmark_detection/detectors/crop_detector.py

@@ -6,8 +6,8 @@
 from .base import LandmarkDetectionBaseDetector
 
 
-@maybe_detector("cropping_landmark", tags=["vision", "face", "landmark_detection", "transformed", "cropped"])
-class CroppingDetectorLandmark(LandmarkDetectionBaseDetector):
+@maybe_detector("crop_landmark_detection", tags=["vision", "face", "landmark_detection", "transformed", "crop"])
+class CropDetectorLandmarkDetection(LandmarkDetectionBaseDetector):
     """
     Detector that evaluates models performance relative to a facial part
     """

giskard_vision/landmark_detection/detectors/metadata_detector.py

@@ -1,4 +1,4 @@
-from giskard_vision.core.detectors.metadata_scan_detector import MetaDataScanDetector
+from giskard_vision.core.detectors.metadata_detector import MetaDataDetector
 from giskard_vision.landmark_detection.detectors.surrogate_functions import (
     SurrogateNME,
     SurrogateVolumeConvexHull,
@@ -8,6 +8,6 @@
 from .specs import DetectorSpecs
 
 
-@maybe_detector("metadata_landmark", tags=["vision", "face", "landmark_detection", "metadata"])
-class MetaDataScanDetectorLandmark(DetectorSpecs, MetaDataScanDetector):
+@maybe_detector("metadata_landmark_detection", tags=["vision", "face", "landmark_detection", "metadata"])
+class MetaDataDetectorLandmarkDetection(DetectorSpecs, MetaDataDetector):
     surrogates = [SurrogateVolumeConvexHull, SurrogateNME]

giskard_vision/landmark_detection/detectors/transformation_resize_detector.py → giskard_vision/landmark_detection/detectors/resize_detector.py

@@ -5,8 +5,8 @@
 from .base import LandmarkDetectionBaseDetector
 
 
-@maybe_detector("resize_landmark", tags=["vision", "face", "landmark_detection", "transformed", "resized"])
-class TransformationResizeDetectorLandmark(LandmarkDetectionBaseDetector):
+@maybe_detector("resize_landmark_detection", tags=["vision", "face", "landmark_detection", "transformed", "resize"])
+class TransformationResizeDetectorLandmarkDetection(LandmarkDetectionBaseDetector):
     """
     Detector that evaluates models performance on resized images
     """

giskard_vision/landmark_detection/detectors/surrogate_functions.py

@@ -1,7 +1,7 @@
 import numpy as np
 from scipy.spatial import ConvexHull
 
-from giskard_vision.core.detectors.metadata_scan_detector import Surrogate
+from giskard_vision.core.detectors.metadata_detector import Surrogate
 from giskard_vision.landmark_detection.tests.performance import NMEMean
 from giskard_vision.landmark_detection.types import PredictionResult
 

giskard_vision/object_detection/detectors/__init__.py

@@ -1,5 +1,5 @@
-from .metadata_detector import MetaDataScanDetectorObjectDetection
+from .metadata_detector import MetaDataDetectorObjectDetection
 
 __all__ = [
-    "MetaDataScanDetectorObjectDetection",
+    "MetaDataDetectorObjectDetection",
 ]

giskard_vision/object_detection/detectors/metadata_detector.py

@@ -1,4 +1,4 @@
-from giskard_vision.core.detectors.metadata_scan_detector import MetaDataScanDetector
+from giskard_vision.core.detectors.metadata_detector import MetaDataDetector
 from giskard_vision.object_detection.detectors.surrogate_functions import (
     SurrogateArea,
     SurrogateAspectRatio,
@@ -21,7 +21,7 @@
 
 
 @maybe_detector("metadata_object_detection", tags=["vision", "object_detection", "metadata"])
-class MetaDataScanDetectorObjectDetection(DetectorSpecs, MetaDataScanDetector):
+class MetaDataDetectorObjectDetection(DetectorSpecs, MetaDataDetector):
     surrogates = [
         SurrogateCenterMassX,
         SurrogateCenterMassY,

giskard_vision/object_detection/detectors/surrogate_functions.py

@@ -1,6 +1,6 @@
 import numpy as np
 
-from giskard_vision.core.detectors.metadata_scan_detector import Surrogate
+from giskard_vision.core.detectors.metadata_detector import Surrogate
 
 
 @staticmethod

tests/landmark_detection/detectors/test_detectors.py

@@ -1,31 +1,25 @@
 from giskard.scanner.issues import Issue, IssueLevel
 from pytest import mark
 
-from giskard_vision.core.detectors.transformation_blurring_detector import (
-    TransformationBlurringDetector,
-)
-from giskard_vision.core.detectors.transformation_color_detector import (
-    TransformationColorDetector,
-)
-from giskard_vision.core.detectors.transformation_noise_detector import (
-    TransformationNoiseDetector,
-)
+from giskard_vision.core.detectors.blur_detector import BlurDetector
+from giskard_vision.core.detectors.color_detector import ColorDetector
+from giskard_vision.core.detectors.noise_detector import NoiseDetector
 from giskard_vision.landmark_detection.detectors import (
-    CroppingDetectorLandmark,
-    MetaDataScanDetectorLandmark,
-    TransformationResizeDetectorLandmark,
+    CropDetectorLandmarkDetection,
+    MetaDataDetectorLandmarkDetection,
+    TransformationResizeDetectorLandmarkDetection,
 )
 from giskard_vision.landmark_detection.detectors.base import ScanResult
 
 
 @mark.parametrize(
     "detector",
     [
-        CroppingDetectorLandmark,
-        TransformationBlurringDetector,
-        TransformationColorDetector,
-        TransformationNoiseDetector,
-        TransformationResizeDetectorLandmark,
+        CropDetectorLandmarkDetection,
+        BlurDetector,
+        ColorDetector,
+        NoiseDetector,
+        TransformationResizeDetectorLandmarkDetection,
     ],
 )
 def test_base_detector(opencv_model, dataset_300w, detector):
@@ -43,10 +37,10 @@ def test_base_detector(opencv_model, dataset_300w, detector):
 
 
 def test_meta_detector(opencv_model, dataset_ffhq):
-    results = MetaDataScanDetectorLandmark().get_results(opencv_model, dataset_ffhq)
+    results = MetaDataDetectorLandmarkDetection().get_results(opencv_model, dataset_ffhq)
     assert isinstance(results, list)
 
-    issues = MetaDataScanDetectorLandmark().get_issues(
+    issues = MetaDataDetectorLandmarkDetection().get_issues(
         opencv_model, dataset_ffhq, results, (IssueLevel.MINOR, IssueLevel.MEDIUM, IssueLevel.MAJOR)
     )
     assert isinstance(issues, list)