Merge main and resolve conflicts (open-edge-platform#2287)

* Reduce rich methods (open-edge-platform#2283)

remove rich

Signed-off-by: Ashwin Vaidya <[email protected]>

* Refactor BaseThreshold to Threshold (open-edge-platform#2278)

* Refactor BaseThreshold to Threshold

* Add relative import and add tests

Signed-off-by: Samet Akcay <[email protected]>

* Revert threshold.py to base.py

Signed-off-by: Samet Akcay <[email protected]>

* Revert threshold imports

Signed-off-by: Samet Akcay <[email protected]>

* Update tests/unit/metrics/threshold/test_threshold.py

Co-authored-by: Ashwin Vaidya <[email protected]>

---------

Signed-off-by: Samet Akcay <[email protected]>
Co-authored-by: Ashwin Vaidya <[email protected]>

* Enable Ruff Rules: PLW1514 and PLR6201 (open-edge-platform#2284)

* pre-commit autoupdate

Signed-off-by: Samet Akcay <[email protected]>

* Enable preview feautures, and disable some of the updated features

* Add missing copyrights

Signed-off-by: Samet Akcay <[email protected]>

* Ignore copyrights in notebooks

* "PLW1514", # Add explicit encoding argument

Signed-off-by: Samet Akcay <[email protected]>

* "PLR6201", # Convert to set

Signed-off-by: Samet Akcay <[email protected]>

---------

Signed-off-by: Samet Akcay <[email protected]>

---------

Signed-off-by: Ashwin Vaidya <[email protected]>
Signed-off-by: Samet Akcay <[email protected]>
Co-authored-by: Ashwin Vaidya <[email protected]>
Co-authored-by: Ashwin Vaidya <[email protected]>

Author: 2 people

src/anomalib/deploy/inferencers/openvino_inferencer.py

@@ -200,7 +200,4 @@ def predict(
         predictions = self.model(image)
         pred_dict = self.post_process(predictions)
 
-        return NumpyImageBatch(
-            image=image,
-            **pred_dict,
-        )
+        return NumpyImageBatch(image=image, **pred_dict)

src/anomalib/models/components/base/anomaly_module.py

@@ -20,7 +20,7 @@
 
 from anomalib import LearningType
 from anomalib.dataclasses import Batch, InferenceBatch
-from anomalib.metrics.threshold import BaseThreshold
+from anomalib.metrics.threshold import Threshold
 from anomalib.post_processing import OneClassPostProcessor, PostProcessor
 
 from .export_mixin import ExportMixin
@@ -157,7 +157,7 @@ def _save_to_state_dict(self, destination: OrderedDict, prefix: str, keep_vars:
 
         return super()._save_to_state_dict(destination, prefix, keep_vars)
 
-    def _get_instance(self, state_dict: OrderedDict[str, Any], dict_key: str) -> BaseThreshold:
+    def _get_instance(self, state_dict: OrderedDict[str, Any], dict_key: str) -> Threshold:
         """Get the threshold class from the ``state_dict``."""
         class_path = state_dict.pop(dict_key)
         module = importlib.import_module(".".join(class_path.split(".")[:-1]))

tests/integration/model/test_models.py

@@ -178,7 +178,7 @@ def _get_objects(
         """
         # select task type
 
-        task_type = TaskType.CLASSIFICATION if model_name in ("ganomaly", "dfkde") else TaskType.SEGMENTATION
+        task_type = TaskType.CLASSIFICATION if model_name in {"ganomaly", "dfkde"} else TaskType.SEGMENTATION
 
         # set extra model args
         # TODO(ashwinvaidya17): Fix these Edge cases

tests/unit/data/base/image.py

@@ -28,7 +28,7 @@ def test_get_item_returns_correct_keys_and_shapes(subset: str, datamodule: Anoma
         assert batch.image.shape == (4, 3, 256, 256)
         assert batch.gt_label.shape == (4,)
 
-        if dataloader.dataset.task in ("detection", "segmentation"):
+        if dataloader.dataset.task in {"detection", "segmentation"}:
             assert batch.gt_mask.shape == (4, 256, 256)
 
     @staticmethod

tests/unit/data/base/video.py

@@ -41,7 +41,7 @@ def test_get_item_returns_correct_keys_and_shapes(datamodule: AnomalibDataModule
         # We don't know the shape of the original image, so we only check that it is a list of 4 images.
         assert batch.original_image.shape[0] == 4
 
-        if subset in ("val", "test"):
+        if subset in {"val", "test"}:
             assert len(batch.gt_label) == 4
             assert batch.gt_mask.shape == (4, 256, 256)
             assert batch.gt_mask.shape == (4, 256, 256)

tools/inference/gradio_inference.py

@@ -56,7 +56,7 @@ def get_inferencer(weight_path: Path) -> Inferencer:
         torch_inferencer = module.TorchInferencer
         inferencer = torch_inferencer(path=weight_path)
 
-    elif extension in (".onnx", ".bin", ".xml"):
+    elif extension in {".onnx", ".bin", ".xml"}:
         openvino_inferencer = module.OpenVINOInferencer
         inferencer = openvino_inferencer(path=weight_path)