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[Feature/OTX] Rebase develop to feature/otx before MPA refactoring (#…
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…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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@harimkang @ashwinvaidya17
@jaegukhyun @nikita-savelyevv @sovrasov @JihwanEom @goodsong81 @supersoob @eugene123tw @chuneuny-emily @ljcornel @eunwoosh @yunchu
13 people authored and yunchu committed Nov 8, 2022
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6 changes: 3 additions & 3 deletions .pre-commit-config.yaml
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Expand Up @@ -19,7 +19,7 @@ repos:
- id: isort
alias: isort_rest
name: "isort - legacy (ote_cli|external)"
files: '^(ote_cli|external/anomaly)/.*\.py'
files: '^(ote_cli|external/anomaly|external/model-preparation-algorithm)/.*\.py'
exclude: "tests/"

- repo: https://github.com/psf/black
Expand All @@ -39,7 +39,7 @@ repos:
- id: black
name: "black - legacy (rest)"
args: [--line-length, "120"]
files: '^external/anomaly/.*\.py'
files: '^(external/anomaly|external/model-preparation-algorithm)/.*\.py'

- repo: https://github.com/PyCQA/flake8
rev: "5.0.3"
Expand All @@ -56,7 +56,7 @@ repos:
# is to be removed.
- id: flake8
name: "flake8 - legacy "
files: '^(ote_sdk|ote_cli|external/anomaly)/.*\.py'
files: '^(ote_sdk|ote_cli|external/anomaly|external/model-preparation-algorithm)/.*\.py'
args: ["--config", ".flake8", "--max-complexity", "20"]
exclude: ".*/protobuf"

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19 changes: 19 additions & 0 deletions QUICK_START_GUIDE.md
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Expand Up @@ -173,6 +173,9 @@ usage: ote train template params [-h]
[--learning_parameters.learning_rate LEARNING_RATE]
[--learning_parameters.learning_rate_warmup_iters LEARNING_RATE_WARMUP_ITERS]
[--learning_parameters.num_iters NUM_ITERS]
[--learning_parameters.enable_early_stopping ENABLE_EARLY_STOPPING]
[--learning_parameters.early_stop_patience EARLY_STOP_PATIENCE]
[--learning_parameters.early_stop_iteration_patience EARLY_STOP_ITERATION_PATIENCE]
[--postprocessing.confidence_threshold CONFIDENCE_THRESHOLD]
[--postprocessing.result_based_confidence_threshold RESULT_BASED_CONFIDENCE_THRESHOLD]
[--nncf_optimization.enable_quantization ENABLE_QUANTIZATION]
Expand Down Expand Up @@ -205,6 +208,22 @@ optional arguments:
default_value: 300
max_value: 100000
min_value: 1
--learning_parameters.enable_early_stopping ENABLE_EARLY_STOPPING
header: Enable early stopping of the training
type: BOOLEAN
default_value: True
--learning_parameters.early_stop_patience EARLY_STOP_PATIENCE
header: Patience for early stopping
type: INTEGER
default_value: 10
max_value: 50
min_value: 0
--learning_parameters.early_stop_iteration_patience EARLY_STOP_ITERATION_PATIENCE
header: Iteration patience for early stopping
type: INTEGER
default_value: 0
max_value: 1000
min_value: 0
--postprocessing.confidence_threshold CONFIDENCE_THRESHOLD
header: Confidence threshold
type: FLOAT
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82 changes: 37 additions & 45 deletions external/README.md
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Expand Up @@ -5,68 +5,60 @@ Every sub-project is fully indepedent from each other, and each of them has its

## Anomaly Classification

| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| -------------------------------- | ----- | ------------------- | --------------- | ---------------------------------------------------- |
| ote_anomaly_classification_padim | PADIM | 3.9 | 168.4 | anomaly/templates/classification/padim/template.yaml |
| ote_anomaly_classification_stfpm | STFPM | 5.6 | 21.1 | anomaly/templates/classification/stfpm/template.yaml |
| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| -------------------------------- | ----- | ------------------- | --------------- | -------------------------------------------------- |
| ote_anomaly_classification_padim | PADIM | 3.9 | 168.4 | anomaly/configs/classification/padim/template.yaml |
| ote_anomaly_classification_stfpm | STFPM | 5.6 | 21.1 | anomaly/configs/classification/stfpm/template.yaml |

## Anomaly Detection

| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| --------------------------- | ----- | ------------------- | --------------- | ----------------------------------------------- |
| ote_anomaly_detection_padim | PADIM | 3.9 | 168.4 | anomaly/templates/detection/padim/template.yaml |
| ote_anomaly_detection_stfpm | STFPM | 5.6 | 21.1 | anomaly/templates/detection/stfpm/template.yaml |
| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| --------------------------- | ----- | ------------------- | --------------- | --------------------------------------------- |
| ote_anomaly_detection_padim | PADIM | 3.9 | 168.4 | anomaly/configs/detection/padim/template.yaml |
| ote_anomaly_detection_stfpm | STFPM | 5.6 | 21.1 | anomaly/configs/detection/stfpm/template.yaml |

## Anomaly Segmentation

| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| ------------------------------ | ----- | ------------------- | --------------- | -------------------------------------------------- |
| ote_anomaly_segmentation_padim | PADIM | 3.9 | 168.4 | anomaly/templates/segmentation/padim/template.yaml |
| ote_anomaly_segmentation_stfpm | STFPM | 5.6 | 21.1 | anomaly/templates/segmentation/stfpm/template.yaml |
| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| ------------------------------ | ----- | ------------------- | --------------- | ------------------------------------------------ |
| ote_anomaly_segmentation_padim | PADIM | 3.9 | 168.4 | anomaly/configs/segmentation/padim/template.yaml |
| ote_anomaly_segmentation_stfpm | STFPM | 5.6 | 21.1 | anomaly/configs/segmentation/stfpm/template.yaml |

## Image Classification

| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| -------------------------------------------------------------- | -------------------------------- | ------------------- | --------------- | -------------------------------------------------------------------------------------------------- |
| 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 |
| 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 |
| 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 |
| 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 |
| ClassIncremental_Image_Classification_EfficinetNet-B0 | EfficientNet-B0-ClsIncr | 0.81 | 4.09 | model-preparation-algorithm/configs/classification/efficientnet_b0_cls_incr/template.yaml |
| Custom_Image_Classification_EfficinetNet-B0 | EfficientNet-B0 | 0.81 | 4.09 | deep-object-reid/configs/ote_custom_classification/efficientnet_b0/template_experimental.yaml |
| 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 |
| 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 |
| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| ------------------------------------------------- | --------------------- | ------------------- | --------------- | ---------------------------------------------------------------------------------------------- |
| 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 |
| Custom_Image_Classification_EfficinetNet-B0 | EfficientNet-B0 | 0.81 | 4.09 | model-preparation-algorithm/configs/classification/efficientnet_b0_cls_incr/template.yaml |
| 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 |

## Object Detection

| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| -------------------------------------------- | ------------- | ------------------- | --------------- | -------------------------------------------------------------------------------------------- |
| Custom_Object_Detection_YOLOX | YOLOX | 6.5 | 20.4 | mmdetection/configs/custom-object-detection/cspdarknet_YOLOX/template_experimental.yaml |
| Custom_Object_Detection_Gen3_SSD | SSD | 9.4 | 7.6 | mmdetection/configs/custom-object-detection/gen3_mobilenetV2_SSD/template_experimental.yaml |
| ClassIncremental_Object_Detection_Gen3_ATSS | ATSS-ClsIncr | 20.6 | 9.1 | model-preparation-algorithm/configs/detection/mobilenetv2_atss_cls_incr/template.yaml |
| Custom_Object_Detection_Gen3_ATSS | ATSS | 20.6 | 9.1 | mmdetection/configs/custom-object-detection/gen3_mobilenetV2_ATSS/template_experimental.yaml |
| ClassIncremental_Object_Detection_Gen3_VFNet | VFNet-ClsIncr | 457.4 | 126.0 | model-preparation-algorithm/configs/detection/resnet50_vfnet_cls_incr/template.yaml |
| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| --------------------------------- | ----- | ------------------- | --------------- | ------------------------------------------------------------------------------------- |
| Custom_Object_Detection_YOLOX | YOLOX | 6.5 | 20.4 | model-preparation-algorithm/configs/detection/cspdarknet_yolox_cls_incr/template.yaml |
| Custom_Object_Detection_Gen3_SSD | SSD | 9.4 | 7.6 | model-preparation-algorithm/configs/detection/mobilenetv2_ssd_cls_incr/template.yaml |
| Custom_Object_Detection_Gen3_ATSS | ATSS | 20.6 | 9.1 | model-preparation-algorithm/configs/detection/mobilenetv2_atss_cls_incr/template.yaml |

## Object Counting
## Instance Segmentation (Object Counting)

| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| -------------------------------------------------------------- | ------------------------ | ------------------- | --------------- | --------------------------------------------------------------------------------------- |
| Custom_Counting_Instance_Segmentation_MaskRCNN_EfficientNetB2B | MaskRCNN-EfficientNetB2B | 68.48 | 13.27 | mmdetection/configs/custom-counting-instance-seg/efficientnetb2b_maskrcnn/template.yaml |
| Custom_Counting_Instance_Segmentation_MaskRCNN_ResNet50 | MaskRCNN-ResNet50 | 533.8 | 177.9 | mmdetection/configs/custom-counting-instance-seg/resnet50_maskrcnn/template.yaml |
| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| -------------------------------------------------------------- | ------------------------ | ------------------- | --------------- | ------------------------------------------------------------------------------------------------ |
| Custom_Counting_Instance_Segmentation_MaskRCNN_EfficientNetB2B | MaskRCNN-EfficientNetB2B | 68.48 | 13.27 | model-preparation-algorithm/configs/instance-segmentation/efficientnetb2b_maskrcnn/template.yaml |
| Custom_Counting_Instance_Segmentation_MaskRCNN_ResNet50 | MaskRCNN-ResNet50 | 533.8 | 177.9 | model-preparation-algorithm/configs/instance-segmentation/resnet50_maskrcnn/template.yaml |

## Rotated Object Detection

| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| --------------------------------------------------------------------------- | ------------------------ | ------------------- | --------------- | ---------------------------------------------------------------------------- |
| Custom_Rotated_Detection_via_Instance_Segmentation_MaskRCNN_EfficientNetB2B | MaskRCNN-EfficientNetB2B | 68.48 | 13.27 | mmdetection/configs/rotated_detection/efficientnetb2b_maskrcnn/template.yaml |
| Custom_Rotated_Detection_via_Instance_Segmentation_MaskRCNN_ResNet50 | MaskRCNN-ResNet50 | 533.8 | 177.9 | mmdetection/configs/rotated_detection/resnet50_maskrcnn/template.yaml |
| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| --------------------------------------------------------------------------- | ------------------------ | ------------------- | --------------- | -------------------------------------------------------------------------------------------- |
| Custom_Rotated_Detection_via_Instance_Segmentation_MaskRCNN_EfficientNetB2B | MaskRCNN-EfficientNetB2B | 68.48 | 13.27 | model-preparation-algorithm/configs/rotated-detection/efficientnetb2b_maskrcnn/template.yaml |
| Custom_Rotated_Detection_via_Instance_Segmentation_MaskRCNN_ResNet50 | MaskRCNN-ResNet50 | 533.8 | 177.9 | model-preparation-algorithm/configs/rotated-detection/resnet50_maskrcnn/template.yaml |

## Semantic Segmentation

| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| -------------------------------------------------------- | ------------------------- | ------------------- | --------------- | ----------------------------------------------------------------------------------------- |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| ID | Name | Complexity (GFlops) | Model size (MB) | Path |
| --------------------------------------------------- | ------------------ | ------------------- | --------------- | ------------------------------------------------------------------------------------- |
| 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 |
| 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 |
| 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 |
| 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 |
10 changes: 0 additions & 10 deletions ...p-object-reid/configs/ote_custom_classification/efficientnet_v2_s/compression_config.json
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Expand Up @@ -44,16 +44,6 @@
},
"nncf_config": {
"compression": [
{
"algorithm": "filter_pruning",
"pruning_init": 0.1,
"params": {
"schedule": "baseline",
"pruning_flops_target": 0.1,
"filter_importance": "geometric_median",
"prune_downsample_convs": true
}
},
{
"algorithm": "quantization",
"preset": "mixed",
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2 changes: 1 addition & 1 deletion ...bject-reid/configs/ote_custom_classification/efficientnet_v2_s/template_experimental.yaml
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Expand Up @@ -43,7 +43,7 @@ hyper_parameters:
enable_pruning:
default_value: false
pruning_supported:
default_value: true
default_value: false
maximal_accuracy_degradation:
default_value: 1.0

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1 change: 1 addition & 0 deletions external/deep-object-reid/constraints.txt
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@@ -1 +1,2 @@
opencv-python==4.5.5.64 # remedy for fixed opencv-python-headless version in e2e-test-framework
optuna==2.10.1 # remedy for fixed optuna version incompatible in OTE CI
2 changes: 1 addition & 1 deletion external/deep-object-reid/submodule
Submodule submodule updated 12 files
+2 −1 .github/workflows/main.yml
+2 −2 openvino-requirements.txt
+0 −1 optional-requirements.txt
+1 −1 requirements.txt
+1 −1 tools/auxiliary/optuna_optim.py
+1 −1 tools/auxiliary/run_classification.py
+1 −1 tools/auxiliary/run_multilabel.py
+63 −0 tools/check_classes_mlc.py
+2 −2 torchreid/engine/engine.py
+4 −7 torchreid/losses/asl.py
+0 −6 torchreid/models/timm_wrapper.py
+3 −1 torchreid/utils/torchtools.py
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