Add model category attributes to model template

src/otx/algorithms/anomaly/configs/classification/padim/template.yaml

@@ -29,3 +29,7 @@ training_targets:
 # Computational Complexity
 gigaflops: 3.9
 size: 168.4
+
+# Model spec
+model_category: SPEED
+is_default_for_task: true

src/otx/algorithms/anomaly/configs/classification/stfpm/template.yaml

@@ -35,3 +35,6 @@ training_targets:
 # Computational Complexity
 gigaflops: 5.6
 size: 21.1
+
+# Model spec
+model_category: ACCURACY

src/otx/algorithms/anomaly/configs/detection/padim/template.yaml

@@ -29,3 +29,7 @@ training_targets:
 # Computational Complexity
 gigaflops: 3.9
 size: 168.4
+
+# Model spec
+model_category: SPEED
+is_default_for_task: true

src/otx/algorithms/anomaly/configs/detection/stfpm/template.yaml

@@ -35,3 +35,6 @@ training_targets:
 # Computational Complexity
 gigaflops: 5.6
 size: 21.1
+
+# Model spec
+model_category: ACCURACY

src/otx/algorithms/anomaly/configs/segmentation/padim/template.yaml

@@ -29,3 +29,7 @@ training_targets:
 # Computational Complexity
 gigaflops: 3.9
 size: 168.4
+
+# Model spec
+model_category: SPEED
+is_default_for_task: true

src/otx/algorithms/anomaly/configs/segmentation/stfpm/template.yaml

@@ -35,3 +35,6 @@ training_targets:
 # Computational Complexity
 gigaflops: 5.6
 size: 21.1
+
+# Model spec
+model_category: ACCURACY

src/otx/algorithms/classification/configs/efficientnet_b0_cls_incr/template.yaml

@@ -57,3 +57,7 @@ training_targets:
 # Stats.
 gigaflops: 0.81
 size: 4.09
+
+# Model spec
+model_category: BALANCE
+is_default_for_task: true

src/otx/algorithms/classification/configs/efficientnet_v2_s_cls_incr/template.yaml

@@ -57,3 +57,6 @@ training_targets:
 # Stats.
 gigaflops: 5.76
 size: 20.23
+
+# Model spec
+model_category: ACCURACY

src/otx/algorithms/classification/configs/mobilenet_v3_large_1_cls_incr/template.yaml

@@ -57,3 +57,6 @@ training_targets:
 # Stats.
 gigaflops: 0.44
 size: 4.29
+
+# Model spec
+model_category: SPEED

src/otx/algorithms/detection/configs/detection/cspdarknet_yolox/template.yaml

@@ -57,8 +57,6 @@ training_targets:
 # Stats.
 gigaflops: 6.5
 size: 20.4
-# # Inference options. Defined by OpenVINO capabilities, not Algo Backend or Platform.
-# inference_targets:
-#   - CPU
-#   - GPU
-#   - VPU
+
+# Model spec
+model_category: SPEED

src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/template.yaml

@@ -57,8 +57,7 @@ training_targets:
 # Stats.
 gigaflops: 20.6
 size: 9.1
-# # Inference options. Defined by OpenVINO capabilities, not Algo Backend or Platform.
-# inference_targets:
-#   - CPU
-#   - GPU
-#   - VPU
+
+# Model spec
+model_category: ACCURACY
+is_default_for_task: true

src/otx/algorithms/detection/configs/detection/mobilenetv2_ssd/template.yaml

@@ -57,8 +57,6 @@ training_targets:
 # Stats.
 gigaflops: 9.4
 size: 7.6
-# # Inference options. Defined by OpenVINO capabilities, not Algo Backend or Platform.
-# inference_targets:
-#   - CPU
-#   - GPU
-#   - VPU
+
+# Model spec
+model_category: BALANCE

src/otx/algorithms/detection/configs/instance_segmentation/efficientnetb2b_maskrcnn/template.yaml

@@ -60,3 +60,6 @@ training_targets:
 # Stats.
 gigaflops: 68.48
 size: 13.27
+
+# Model spec
+model_category: SPEED

src/otx/algorithms/detection/configs/instance_segmentation/resnet50_maskrcnn/template.yaml

@@ -60,3 +60,7 @@ training_targets:
 # Stats.
 gigaflops: 533.8
 size: 177.9
+
+# Model spec
+model_category: ACCURACY
+is_default_for_task: true

src/otx/algorithms/detection/configs/rotated_detection/efficientnetb2b_maskrcnn/template.yaml

@@ -60,3 +60,6 @@ training_targets:
 # Stats.
 gigaflops: 68.48
 size: 13.27
+
+# Model spec
+model_category: SPEED

src/otx/algorithms/detection/configs/rotated_detection/resnet50_maskrcnn/template.yaml

@@ -60,3 +60,7 @@ training_targets:
 # Stats.
 gigaflops: 533.8
 size: 177.9
+
+# Model spec
+model_category: ACCURACY
+is_default_for_task: true

src/otx/algorithms/segmentation/configs/ocr_lite_hrnet_18_mod2/template.yaml

@@ -58,3 +58,7 @@ training_targets:
 # Stats.
 gigaflops: 3.63
 size: 4.8
+
+# Model spec
+model_category: BALANCE
+is_default_for_task: true

src/otx/algorithms/segmentation/configs/ocr_lite_hrnet_s_mod2/template.yaml

@@ -59,3 +59,6 @@ training_targets:
 # Stats.
 gigaflops: 1.82
 size: 3.5
+
+# Model spec
+model_category: SPEED

src/otx/algorithms/segmentation/configs/ocr_lite_hrnet_x_mod3/template.yaml

@@ -59,3 +59,6 @@ training_targets:
 # Stats.
 gigaflops: 13.97
 size: 6.4
+
+# Model spec
+model_category: ACCURACY

src/otx/api/entities/model_template.py

@@ -1,6 +1,6 @@
 """This file defines the ModelConfiguration, ModelEntity and Model classes."""
 
-# Copyright (C) 2021-2022 Intel Corporation
+# Copyright (C) 2021-2023 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 #
 import copy
@@ -459,6 +459,30 @@ class EntryPoints:
     nncf: Optional[str] = None
 
 
+class ModelCategory(Enum):
+    """Represents model category regarding accuracy & speed trade-off."""
+
+    SPEED = auto()
+    BALANCE = auto()
+    ACCURACY = auto()
+    OTHER = auto()
+
+    def __str__(self) -> str:
+        """Returns the name of the model category."""
+        return str(self.name)
+
+
+class ModelStatus(Enum):
+    """Represents model status regarding deprecation process."""
+
+    ACTIVE = auto()
+    DEPRECATED = auto()
+
+    def __str__(self) -> str:
+        """Returns the name of the model status."""
+        return str(self.name)
+
+
 # pylint: disable=too-many-instance-attributes
 @dataclass
 class ModelTemplate:
@@ -499,6 +523,9 @@ class ModelTemplate:
         priority. mobilenet is less important, and has a higher value. Default is zero (the highest priority).
     gigaflops (float): how many billions of operations are required to do inference on a single data item.
     size (float): how much disk space the model will approximately take.
+    model_category (ModelCategory): Represents model category regarding accuracy & speed trade-off. Default to OTHER.
+    model_status (ModelStatus): Represents model status regarding deprecation process. Default to ACTIVE.
+    is_default_for_task (bool): Whether this model is a default recommendation for the task
     """
 
     model_template_id: str
@@ -528,6 +555,9 @@ class ModelTemplate:
     gigaflops: float = 0
     size: float = 0
     hpo: Optional[Dict] = None
+    model_category: ModelCategory = ModelCategory.OTHER
+    model_status: ModelStatus = ModelStatus.ACTIVE
+    is_default_for_task: bool = False
 
     def __post_init__(self):
         """Do sanitation checks before loading the hyper-parameters."""

tests/integration/cli/anomaly/test_anomaly_classification.py

@@ -1,23 +1,13 @@
 """Tests for anomaly classification with OTX CLI"""
-
-# Copyright (C) 2021 Intel Corporation
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
+# Copyright (C) 2021-2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
 #
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions
-# and limitations under the License.
 
 import os
 
 import pytest
 
+from otx.api.entities.model_template import parse_model_template, ModelCategory, ModelStatus
 from otx.cli.registry import Registry
 from tests.test_suite.e2e_test_system import e2e_pytest_component
 from tests.test_suite.run_test_command import (
@@ -44,6 +34,38 @@
 templates_ids = [template.model_template_id for template in templates]
 
 
+class TestAnomalyClassificationModelTemplates:
+    @e2e_pytest_component
+    def test_model_category(self):
+        stat = {
+            ModelCategory.SPEED: 0,
+            ModelCategory.BALANCE: 0,
+            ModelCategory.ACCURACY: 0,
+            ModelCategory.OTHER: 0,
+        }
+        for template in templates:
+            stat[template.model_category] += 1
+        assert stat[ModelCategory.SPEED] == 1
+        assert stat[ModelCategory.BALANCE] <= 1
+        assert stat[ModelCategory.ACCURACY] == 1
+
+    @e2e_pytest_component
+    def test_model_status(self):
+        for template in templates:
+            if template.model_status == ModelStatus.DEPRECATED:
+                assert template.model_category == ModelCategory.OTHER
+
+    @e2e_pytest_component
+    def test_default_for_task(self):
+        num_default_model = 0
+        for template in templates:
+            if template.is_default_for_task:
+                num_default_model += 1
+                assert template.model_category != ModelCategory.OTHER
+                assert template.model_status == ModelStatus.ACTIVE
+        assert num_default_model == 1
+
+
 class TestToolsAnomalyClassification:
     @e2e_pytest_component
     @pytest.mark.parametrize("template", templates, ids=templates_ids)

tests/integration/cli/anomaly/test_anomaly_detection.py

@@ -1,23 +1,13 @@
 """Tests for anomaly detection with OTX CLI."""
-
-# Copyright (C) 2021 Intel Corporation
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
+# Copyright (C) 2021-2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
 #
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions
-# and limitations under the License.
 
 import os
 
 import pytest
 
+from otx.api.entities.model_template import parse_model_template, ModelCategory, ModelStatus
 from otx.cli.registry import Registry
 from tests.test_suite.e2e_test_system import e2e_pytest_component
 from tests.test_suite.run_test_command import (
@@ -44,6 +34,38 @@
 templates_ids = [template.model_template_id for template in templates]
 
 
+class TestAnomalyDetectionModelTemplates:
+    @e2e_pytest_component
+    def test_model_category(self):
+        stat = {
+            ModelCategory.SPEED: 0,
+            ModelCategory.BALANCE: 0,
+            ModelCategory.ACCURACY: 0,
+            ModelCategory.OTHER: 0,
+        }
+        for template in templates:
+            stat[template.model_category] += 1
+        assert stat[ModelCategory.SPEED] == 1
+        assert stat[ModelCategory.BALANCE] <= 1
+        assert stat[ModelCategory.ACCURACY] == 1
+
+    @e2e_pytest_component
+    def test_model_status(self):
+        for template in templates:
+            if template.model_status == ModelStatus.DEPRECATED:
+                assert template.model_category == ModelCategory.OTHER
+
+    @e2e_pytest_component
+    def test_default_for_task(self):
+        num_default_model = 0
+        for template in templates:
+            if template.is_default_for_task:
+                num_default_model += 1
+                assert template.model_category != ModelCategory.OTHER
+                assert template.model_status == ModelStatus.ACTIVE
+        assert num_default_model == 1
+
+
 class TestToolsAnomalyDetection:
     @e2e_pytest_component
     @pytest.mark.parametrize("template", templates, ids=templates_ids)