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Songki Choi
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Make max_num_detections configurable (#2647)
* Make max_num_detections configurable * Fix RCNN case with integration test * Apply max_num_detections to train_cfg, too --------- Signed-off-by: Songki Choi <[email protected]>
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18 files changed

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‎CHANGELOG.md‎

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@@ -9,6 +9,7 @@ All notable changes to this project will be documented in this file.
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- Update ModelAPI configuration(<https://github.com/openvinotoolkit/training_extensions/pull/2564>)
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- Add Anomaly modelAPI changes (<https://github.com/openvinotoolkit/training_extensions/pull/2563>)
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- Update Image numpy access (<https://github.com/openvinotoolkit/training_extensions/pull/2586>)
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- Make max_num_detections configurable (<https://github.com/openvinotoolkit/training_extensions/pull/2647>)
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### Bug fixes
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‎src/otx/algorithms/common/configs/training_base.py‎

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@@ -1,18 +1,7 @@
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"""Base Configuration of OTX Common Algorithms."""
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# Copyright (C) 2022 Intel Corporation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions
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# and limitations under the License.
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# Copyright (C) 2022-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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from sys import maxsize
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@@ -227,6 +216,16 @@ class BasePostprocessing(ParameterGroup):
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affects_outcome_of=ModelLifecycle.INFERENCE,
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)
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max_num_detections = configurable_integer(
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header="Maximum number of detection per image",
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description="Extra detection outputs will be discared in non-maximum suppression process. "
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"Defaults to 0, which means per-model default value.",
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default_value=0,
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min_value=0,
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max_value=10000,
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affects_outcome_of=ModelLifecycle.INFERENCE,
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)
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use_ellipse_shapes = configurable_boolean(
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default_value=False,
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header="Use ellipse shapes",

‎src/otx/algorithms/detection/adapters/mmdet/configurer.py‎

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@@ -64,13 +64,14 @@ def configure(
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ir_options=None,
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data_classes=None,
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model_classes=None,
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max_num_detections=0,
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):
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"""Create MMCV-consumable config from given inputs."""
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logger.info(f"configure!: training={training}")
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self.configure_base(cfg, data_cfg, data_classes, model_classes)
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self.configure_device(cfg, training)
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self.configure_model(cfg, ir_options)
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self.configure_model(cfg, ir_options, max_num_detections)
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self.configure_ckpt(cfg, model_ckpt)
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self.configure_data(cfg, training, data_cfg)
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self.configure_regularization(cfg, training)
@@ -113,7 +114,7 @@ def configure_base(self, cfg, data_cfg, data_classes, model_classes):
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new_classes = np.setdiff1d(data_classes, model_classes).tolist()
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train_data_cfg["new_classes"] = new_classes
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def configure_model(self, cfg, ir_options): # noqa: C901
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def configure_model(self, cfg, ir_options, max_num_detections=0): # noqa: C901
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"""Patch config's model.
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Change model type to super type
@@ -149,6 +150,23 @@ def is_mmov_model(key, value):
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{"model_path": ir_model_path, "weight_path": ir_weight_path, "init_weight": ir_weight_init},
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)
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# Test config
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if max_num_detections > 0:
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logger.info(f"Model max_num_detections: {max_num_detections}")
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test_cfg = cfg.model.test_cfg
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test_cfg.max_per_img = max_num_detections
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test_cfg.nms_pre = max_num_detections * 10
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# Special cases for 2-stage detectors (e.g. MaskRCNN)
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if hasattr(test_cfg, "rpn"):
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test_cfg.rpn.nms_pre = max_num_detections * 20
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test_cfg.rpn.max_per_img = max_num_detections * 10
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if hasattr(test_cfg, "rcnn"):
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test_cfg.rcnn.max_per_img = max_num_detections
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train_cfg = cfg.model.train_cfg
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if hasattr(train_cfg, "rpn_proposal"):
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train_cfg.rpn_proposal.nms_pre = max_num_detections * 20
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train_cfg.rpn_proposal.max_per_img = max_num_detections * 10
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def configure_data(self, cfg, training, data_cfg): # noqa: C901
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"""Patch cfg.data.
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‎src/otx/algorithms/detection/adapters/mmdet/task.py‎

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"""Task of OTX Detection using mmdetection training backend."""
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# Copyright (C) 2023 Intel Corporation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions
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# and limitations under the License.
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# SPDX-License-Identifier: Apache-2.0
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import glob
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import io
@@ -206,6 +195,7 @@ def configure(self, training=True, subset="train", ir_options=None, train_datase
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ir_options,
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data_classes,
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model_classes,
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self.max_num_detections,
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)
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if should_cluster_anchors(self._recipe_cfg):
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if train_dataset is not None:
@@ -513,6 +503,12 @@ def _export_model(
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assert len(self._precision) == 1
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export_options["precision"] = str(self._precision[0])
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export_options["type"] = str(export_format)
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if self.max_num_detections > 0:
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logger.info(f"Export max_num_detections: {self.max_num_detections}")
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post_proc_cfg = export_options["deploy_cfg"]["codebase_config"]["post_processing"]
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post_proc_cfg["max_output_boxes_per_class"] = self.max_num_detections
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post_proc_cfg["keep_top_k"] = self.max_num_detections
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post_proc_cfg["pre_top_k"] = self.max_num_detections * 10
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export_options["deploy_cfg"]["dump_features"] = dump_features
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if dump_features:

‎src/otx/algorithms/detection/adapters/openvino/task.py‎

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"""Openvino Task of Detection."""
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# Copyright (C) 2021 Intel Corporation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions
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# and limitations under the License.
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# Copyright (C) 2021-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import copy
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import io

‎src/otx/algorithms/detection/configs/base/configuration.py‎

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"""Configuration file of OTX Detection."""
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# Copyright (C) 2022 Intel Corporation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions
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# and limitations under the License.
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# Copyright (C) 2022-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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from attr import attrs
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‎src/otx/algorithms/detection/configs/detection/configuration.yaml‎

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value: 0.01
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visible_in_ui: true
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warning: null
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max_num_detections:
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affects_outcome_of: INFERENCE
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default_value: 0
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description:
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Extra detection outputs will be discared in non-maximum suppression process.
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Defaults to 0, which means per-model default values.
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editable: true
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header: Maximum number of detections per image
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max_value: 10000
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min_value: 0
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type: INTEGER
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ui_rules:
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action: DISABLE_EDITING
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operator: AND
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rules: []
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type: UI_RULES
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value: 0
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visible_in_ui: true
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warning: null
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use_ellipse_shapes:
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affects_outcome_of: INFERENCE
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default_value: false

‎src/otx/algorithms/detection/configs/instance_segmentation/configuration.yaml‎

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@@ -258,6 +258,25 @@ postprocessing:
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value: 0.01
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visible_in_ui: true
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warning: null
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max_num_detections:
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affects_outcome_of: INFERENCE
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default_value: 0
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description:
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Extra detection outputs will be discared in non-maximum suppression process.
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Defaults to 0, which means per-model default values.
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editable: true
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header: Maximum number of detections per image
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max_value: 10000
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min_value: 0
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type: INTEGER
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ui_rules:
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action: DISABLE_EDITING
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operator: AND
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rules: []
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type: UI_RULES
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value: 0
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visible_in_ui: true
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warning: null
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use_ellipse_shapes:
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affects_outcome_of: INFERENCE
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default_value: false

‎src/otx/algorithms/detection/configs/instance_segmentation/convnext_maskrcnn/model.py‎

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nms=dict(type="nms", iou_threshold=0.7),
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min_bbox_size=0,
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),
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rcnn=dict(
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score_thr=0.05, nms=dict(type="nms", iou_threshold=0.5, max_num=100), max_per_img=100, mask_thr_binary=0.5
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),
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rcnn=dict(score_thr=0.05, nms=dict(type="nms", iou_threshold=0.5), max_per_img=100, mask_thr_binary=0.5),
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),
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)
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‎src/otx/algorithms/detection/configs/instance_segmentation/resnet50_maskrcnn/model.py‎

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"""Model configuration of Resnet50-MaskRCNN model for Instance-Seg Task."""
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# Copyright (C) 2022 Intel Corporation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions
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# and limitations under the License.
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# Copyright (C) 2022-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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# pylint: disable=invalid-name
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@@ -149,7 +138,7 @@
149138
),
150139
rcnn=dict(
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score_thr=0.05,
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nms=dict(type="nms", iou_threshold=0.5, max_num=100),
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nms=dict(type="nms", iou_threshold=0.5),
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max_per_img=100,
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mask_thr_binary=0.5,
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),

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