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[Feature/OTX] Rebase develop to feature/otx before MPA refactoring (#1284)
* Update submodule branch (#1222) * Enhance training schedule for multi-label classification (#1212) * [CVS-88098] Remove initialize from export functions (#1226) * Train graph added (#1211) Co-authored-by: Lee, Soobee <soobeele@intel.com> * Add @attrs decorator for base configs (#1229) Signed-off-by: Songki Choi <songki.choi@intel.com> Co-authored-by: Harim Kang <harim.kang@intel.com> * Pretrained weight download error in MobilenetV3-large-1 of deep-object-reid in SC (#1233) * [Anomaly Task] Revert hpo template (#1230) * 🐞 [Anomaly Task] Fix progress bar (#1223) * [CVS-90555] Fix NaN value in classification (#1244) * update hpo_config.yaml (#1240) * [CVS-90400, CVS-91015] NNCF pruning supported tweaks (#1248) * Turned off pruning_support visibility for anomaly models (CVS-91015) * Disabled pruning for EfficientNet-V2-S (CVS-90400) * [Anomaly Task] 🐞 Fix inference when model backbone changes (#1242) * Fix CVS-91469 sseg compatibility issue * [CVS-91472] Add pruning_supported value (#1263) * Pruning supported tweaks (#1256) * [CVS-90400, CVS-91015] NNCF pruning supported tweaks (#1248) * Turned off pruning_support visibility for anomaly models (CVS-91015) * Disabled pruning for EfficientNet-V2-S (CVS-90400) * Revert "[CVS-90400, CVS-91015] NNCF pruning supported tweaks (#1248)" (#1269) * [OTE-TEST] Disable obsolete test cases (#1220) * [OTE-TEST] hot-fix for MPA performance tests (#1273) * Expose early stopping hyper-parameters for all tasks (#1241) * Resolve pre-commit issues (#1272) * Remove LazyEarlyStopHook in model_multilabel.py (#1281) * Removed xfail (#1239) Signed-off-by: Songki Choi <songki.choi@intel.com> Co-authored-by: Ashwin Vaidya <ashwin.vaidya@intel.com> Co-authored-by: Jaeguk Hyun <jaeguk.hyun@intel.com> Co-authored-by: Nikita Savelyev <nikita.savelyev@intel.com> Co-authored-by: Vladisalv Sovrasov <sovrasov.vlad@gmail.com> Co-authored-by: Jihwan Eom <jihwan.eom@intel.com> Co-authored-by: Songki Choi <songki.choi@intel.com> Co-authored-by: Soobee Lee <soobee.lee@intel.com> Co-authored-by: Lee, Soobee <soobeele@intel.com> Co-authored-by: Eugene Liu <eugene.liu@intel.com> Co-authored-by: Emily Chun <emily.chun@intel.com> Co-authored-by: ljcornel <ludo.cornelissen@intel.com> Co-authored-by: Eunwoo Shin <eunwoo.shin@intel.com>
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‎.pre-commit-config.yaml

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- id: isort
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alias: isort_rest
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name: "isort - legacy (ote_cli|external)"
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files: '^(ote_cli|external/anomaly)/.*\.py'
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files: '^(ote_cli|external/anomaly|external/model-preparation-algorithm)/.*\.py'
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exclude: "tests/"
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- repo: https://github.com/psf/black
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- id: black
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name: "black - legacy (rest)"
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args: [--line-length, "120"]
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files: '^external/anomaly/.*\.py'
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files: '^(external/anomaly|external/model-preparation-algorithm)/.*\.py'
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- repo: https://github.com/PyCQA/flake8
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rev: "5.0.3"
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# is to be removed.
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- id: flake8
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name: "flake8 - legacy "
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files: '^(ote_sdk|ote_cli|external/anomaly)/.*\.py'
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files: '^(ote_sdk|ote_cli|external/anomaly|external/model-preparation-algorithm)/.*\.py'
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args: ["--config", ".flake8", "--max-complexity", "20"]
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exclude: ".*/protobuf"
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‎QUICK_START_GUIDE.md

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[--learning_parameters.learning_rate LEARNING_RATE]
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[--learning_parameters.learning_rate_warmup_iters LEARNING_RATE_WARMUP_ITERS]
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[--learning_parameters.num_iters NUM_ITERS]
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[--learning_parameters.enable_early_stopping ENABLE_EARLY_STOPPING]
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[--learning_parameters.early_stop_patience EARLY_STOP_PATIENCE]
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[--learning_parameters.early_stop_iteration_patience EARLY_STOP_ITERATION_PATIENCE]
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[--postprocessing.confidence_threshold CONFIDENCE_THRESHOLD]
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[--postprocessing.result_based_confidence_threshold RESULT_BASED_CONFIDENCE_THRESHOLD]
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[--nncf_optimization.enable_quantization ENABLE_QUANTIZATION]
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default_value: 300
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max_value: 100000
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min_value: 1
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--learning_parameters.enable_early_stopping ENABLE_EARLY_STOPPING
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header: Enable early stopping of the training
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type: BOOLEAN
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default_value: True
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--learning_parameters.early_stop_patience EARLY_STOP_PATIENCE
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header: Patience for early stopping
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type: INTEGER
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default_value: 10
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max_value: 50
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min_value: 0
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--learning_parameters.early_stop_iteration_patience EARLY_STOP_ITERATION_PATIENCE
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header: Iteration patience for early stopping
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type: INTEGER
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default_value: 0
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max_value: 1000
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min_value: 0
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--postprocessing.confidence_threshold CONFIDENCE_THRESHOLD
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header: Confidence threshold
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type: FLOAT

‎external/README.md

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## Anomaly Classification
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| -------------------------------- | ----- | ------------------- | --------------- | ---------------------------------------------------- |
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| ote_anomaly_classification_padim | PADIM | 3.9 | 168.4 | anomaly/templates/classification/padim/template.yaml |
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| ote_anomaly_classification_stfpm | STFPM | 5.6 | 21.1 | anomaly/templates/classification/stfpm/template.yaml |
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| -------------------------------- | ----- | ------------------- | --------------- | -------------------------------------------------- |
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| ote_anomaly_classification_padim | PADIM | 3.9 | 168.4 | anomaly/configs/classification/padim/template.yaml |
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| ote_anomaly_classification_stfpm | STFPM | 5.6 | 21.1 | anomaly/configs/classification/stfpm/template.yaml |
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## Anomaly Detection
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| --------------------------- | ----- | ------------------- | --------------- | ----------------------------------------------- |
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| ote_anomaly_detection_padim | PADIM | 3.9 | 168.4 | anomaly/templates/detection/padim/template.yaml |
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| ote_anomaly_detection_stfpm | STFPM | 5.6 | 21.1 | anomaly/templates/detection/stfpm/template.yaml |
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| --------------------------- | ----- | ------------------- | --------------- | --------------------------------------------- |
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| ote_anomaly_detection_padim | PADIM | 3.9 | 168.4 | anomaly/configs/detection/padim/template.yaml |
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| ote_anomaly_detection_stfpm | STFPM | 5.6 | 21.1 | anomaly/configs/detection/stfpm/template.yaml |
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## Anomaly Segmentation
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| ------------------------------ | ----- | ------------------- | --------------- | -------------------------------------------------- |
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| ote_anomaly_segmentation_padim | PADIM | 3.9 | 168.4 | anomaly/templates/segmentation/padim/template.yaml |
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| ote_anomaly_segmentation_stfpm | STFPM | 5.6 | 21.1 | anomaly/templates/segmentation/stfpm/template.yaml |
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| ------------------------------ | ----- | ------------------- | --------------- | ------------------------------------------------ |
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| ote_anomaly_segmentation_padim | PADIM | 3.9 | 168.4 | anomaly/configs/segmentation/padim/template.yaml |
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| ote_anomaly_segmentation_stfpm | STFPM | 5.6 | 21.1 | anomaly/configs/segmentation/stfpm/template.yaml |
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## Image Classification
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| -------------------------------------------------------------- | -------------------------------- | ------------------- | --------------- | -------------------------------------------------------------------------------------------------- |
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| ClassIncremental_Image_Classification_MobileNet-V3-small | MobileNet-V3-small-ClsIncr | 0.12 | 1.56 | model-preparation-algorithm/configs/classification/mobilenet_v3_small_cls_incr/template.yaml |
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| ClassIncremental_Image_Classification_MobileNet-V3-large-0.75x | MobileNet-V3-large-0.75x-ClsIncr | 0.32 | 2.76 | model-preparation-algorithm/configs/classification/mobilenet_v3_large_075_cls_incr/template.yaml |
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| ClassIncremental_Image_Classification_MobileNet-V3-large-1x | MobileNet-V3-large-1x-ClsIncr | 0.44 | 4.29 | model-preparation-algorithm/configs/classification/mobilenet_v3_large_1_cls_incr/template.yaml |
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| Custom_Image_Classification_MobileNet-V3-large-1x | MobileNet-V3-large-1x | 0.44 | 4.29 | deep-object-reid/configs/ote_custom_classification/mobilenet_v3_large_1/template_experimental.yaml |
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| ClassIncremental_Image_Classification_EfficinetNet-B0 | EfficientNet-B0-ClsIncr | 0.81 | 4.09 | model-preparation-algorithm/configs/classification/efficientnet_b0_cls_incr/template.yaml |
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| Custom_Image_Classification_EfficinetNet-B0 | EfficientNet-B0 | 0.81 | 4.09 | deep-object-reid/configs/ote_custom_classification/efficientnet_b0/template_experimental.yaml |
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| ClassIncremental_Image_Classification_EfficinetNet-V2-S | EfficientNet-V2-S-ClsIncr | 5.76 | 20.23 | model-preparation-algorithm/configs/classification/efficientnet_v2_s_cls_incr/template.yaml |
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| Custom_Image_Classification_EfficientNet-V2-S | EfficientNet-V2-S | 5.76 | 20.23 | deep-object-reid/configs/ote_custom_classification/efficientnet_v2_s/template_experimental.yaml |
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| ------------------------------------------------- | --------------------- | ------------------- | --------------- | ---------------------------------------------------------------------------------------------- |
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| Custom_Image_Classification_MobileNet-V3-large-1x | MobileNet-V3-large-1x | 0.44 | 4.29 | model-preparation-algorithm/configs/classification/mobilenet_v3_large_1_cls_incr/template.yaml |
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| Custom_Image_Classification_EfficinetNet-B0 | EfficientNet-B0 | 0.81 | 4.09 | model-preparation-algorithm/configs/classification/efficientnet_b0_cls_incr/template.yaml |
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| Custom_Image_Classification_EfficientNet-V2-S | EfficientNet-V2-S | 5.76 | 20.23 | model-preparation-algorithm/configs/classification/efficientnet_v2_s_cls_incr/template.yaml |
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## Object Detection
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| -------------------------------------------- | ------------- | ------------------- | --------------- | -------------------------------------------------------------------------------------------- |
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| Custom_Object_Detection_YOLOX | YOLOX | 6.5 | 20.4 | mmdetection/configs/custom-object-detection/cspdarknet_YOLOX/template_experimental.yaml |
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| Custom_Object_Detection_Gen3_SSD | SSD | 9.4 | 7.6 | mmdetection/configs/custom-object-detection/gen3_mobilenetV2_SSD/template_experimental.yaml |
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| ClassIncremental_Object_Detection_Gen3_ATSS | ATSS-ClsIncr | 20.6 | 9.1 | model-preparation-algorithm/configs/detection/mobilenetv2_atss_cls_incr/template.yaml |
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| Custom_Object_Detection_Gen3_ATSS | ATSS | 20.6 | 9.1 | mmdetection/configs/custom-object-detection/gen3_mobilenetV2_ATSS/template_experimental.yaml |
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| ClassIncremental_Object_Detection_Gen3_VFNet | VFNet-ClsIncr | 457.4 | 126.0 | model-preparation-algorithm/configs/detection/resnet50_vfnet_cls_incr/template.yaml |
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| --------------------------------- | ----- | ------------------- | --------------- | ------------------------------------------------------------------------------------- |
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| Custom_Object_Detection_YOLOX | YOLOX | 6.5 | 20.4 | model-preparation-algorithm/configs/detection/cspdarknet_yolox_cls_incr/template.yaml |
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| Custom_Object_Detection_Gen3_SSD | SSD | 9.4 | 7.6 | model-preparation-algorithm/configs/detection/mobilenetv2_ssd_cls_incr/template.yaml |
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| Custom_Object_Detection_Gen3_ATSS | ATSS | 20.6 | 9.1 | model-preparation-algorithm/configs/detection/mobilenetv2_atss_cls_incr/template.yaml |
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## Object Counting
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## Instance Segmentation (Object Counting)
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| -------------------------------------------------------------- | ------------------------ | ------------------- | --------------- | --------------------------------------------------------------------------------------- |
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| Custom_Counting_Instance_Segmentation_MaskRCNN_EfficientNetB2B | MaskRCNN-EfficientNetB2B | 68.48 | 13.27 | mmdetection/configs/custom-counting-instance-seg/efficientnetb2b_maskrcnn/template.yaml |
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| Custom_Counting_Instance_Segmentation_MaskRCNN_ResNet50 | MaskRCNN-ResNet50 | 533.8 | 177.9 | mmdetection/configs/custom-counting-instance-seg/resnet50_maskrcnn/template.yaml |
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| -------------------------------------------------------------- | ------------------------ | ------------------- | --------------- | ------------------------------------------------------------------------------------------------ |
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| Custom_Counting_Instance_Segmentation_MaskRCNN_EfficientNetB2B | MaskRCNN-EfficientNetB2B | 68.48 | 13.27 | model-preparation-algorithm/configs/instance-segmentation/efficientnetb2b_maskrcnn/template.yaml |
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| Custom_Counting_Instance_Segmentation_MaskRCNN_ResNet50 | MaskRCNN-ResNet50 | 533.8 | 177.9 | model-preparation-algorithm/configs/instance-segmentation/resnet50_maskrcnn/template.yaml |
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## Rotated Object Detection
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| --------------------------------------------------------------------------- | ------------------------ | ------------------- | --------------- | ---------------------------------------------------------------------------- |
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| Custom_Rotated_Detection_via_Instance_Segmentation_MaskRCNN_EfficientNetB2B | MaskRCNN-EfficientNetB2B | 68.48 | 13.27 | mmdetection/configs/rotated_detection/efficientnetb2b_maskrcnn/template.yaml |
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| Custom_Rotated_Detection_via_Instance_Segmentation_MaskRCNN_ResNet50 | MaskRCNN-ResNet50 | 533.8 | 177.9 | mmdetection/configs/rotated_detection/resnet50_maskrcnn/template.yaml |
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| --------------------------------------------------------------------------- | ------------------------ | ------------------- | --------------- | -------------------------------------------------------------------------------------------- |
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| Custom_Rotated_Detection_via_Instance_Segmentation_MaskRCNN_EfficientNetB2B | MaskRCNN-EfficientNetB2B | 68.48 | 13.27 | model-preparation-algorithm/configs/rotated-detection/efficientnetb2b_maskrcnn/template.yaml |
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| Custom_Rotated_Detection_via_Instance_Segmentation_MaskRCNN_ResNet50 | MaskRCNN-ResNet50 | 533.8 | 177.9 | model-preparation-algorithm/configs/rotated-detection/resnet50_maskrcnn/template.yaml |
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| -------------------------------------------------------- | ------------------------- | ------------------- | --------------- | ----------------------------------------------------------------------------------------- |
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| Custom_Semantic_Segmentation_Lite-HRNet-s-mod2_OCR | Lite-HRNet-s-mod2 OCR | 1.82 | 3.5 | mmsegmentation/configs/custom-sematic-segmentation/ocr-lite-hrnet-s-mod2/template.yaml |
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| ClassIncremental_Semantic_Segmentation_Lite-HRNet-18_OCR | Lite-HRNet-18 OCR-ClsIncr | 3.45 | 4.5 | model-preparation-algorithm/configs/segmentation/ocr-lite-hrnet-18-cls-incr/template.yaml |
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| Custom_Semantic_Segmentation_Lite-HRNet-18_OCR | Lite-HRNet-18 OCR | 3.45 | 4.5 | mmsegmentation/configs/custom-sematic-segmentation/ocr-lite-hrnet-18/template.yaml |
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| Custom_Semantic_Segmentation_Lite-HRNet-18-mod2_OCR | Lite-HRNet-18-mod2 OCR | 3.63 | 4.8 | mmsegmentation/configs/custom-sematic-segmentation/ocr-lite-hrnet-18-mod2/template.yaml |
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| Custom_Semantic_Segmentation_Lite-HRNet-x-mod3_OCR | Lite-HRNet-x-mod3 OCR | 13.97 | 6.4 | mmsegmentation/configs/custom-sematic-segmentation/ocr-lite-hrnet-x-mod3/template.yaml |
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| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
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| --------------------------------------------------- | ------------------ | ------------------- | --------------- | ------------------------------------------------------------------------------------- |
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| Custom_Semantic_Segmentation_Lite-HRNet-s-mod2_OCR | Lite-HRNet-s-mod2 | 1.82 | 3.5 | model-preparation-algorithm/configs/segmentation/ocr-lite-hrnet-s-mod2/template.yaml |
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| Custom_Semantic_Segmentation_Lite-HRNet-18_OCR | Lite-HRNet-18 | 3.45 | 4.5 | model-preparation-algorithm/configs/segmentation/ocr-lite-hrnet-18/template.yaml |
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| Custom_Semantic_Segmentation_Lite-HRNet-18-mod2_OCR | Lite-HRNet-18-mod2 | 3.63 | 4.8 | model-preparation-algorithm/configs/segmentation/ocr-lite-hrnet-18-mod2/template.yaml |
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| Custom_Semantic_Segmentation_Lite-HRNet-x-mod3_OCR | Lite-HRNet-x-mod3 | 13.97 | 6.4 | model-preparation-algorithm/configs/segmentation/ocr-lite-hrnet-x-mod3/template.yaml |

‎external/deep-object-reid/configs/ote_custom_classification/efficientnet_v2_s/compression_config.json

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},
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"nncf_config": {
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"pruning_init": 0.1,
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"params": {
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"schedule": "baseline",
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"pruning_flops_target": 0.1,
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"filter_importance": "geometric_median",
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"prune_downsample_convs": true
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‎external/deep-object-reid/configs/ote_custom_classification/efficientnet_v2_s/template_experimental.yaml

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‎external/deep-object-reid/constraints.txt

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opencv-python==4.5.5.64 # remedy for fixed opencv-python-headless version in e2e-test-framework
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optuna==2.10.1 # remedy for fixed optuna version incompatible in OTE CI

‎external/deep-object-reid/submodule

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