[MPA] Enable SSD and YOLOX model template

external/model-preparation-algorithm/configs/detection/cspdarknet_yolox_cls_incr/data_pipeline.py

@@ -0,0 +1,74 @@
+dataset_type = 'CocoDataset'
+data_root = 'data/coco/'
+samples_per_gpu = 2
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+img_scale = (640, 640)
+
+train_pipeline = [
+    dict(type='Mosaic', img_scale=img_scale, pad_val=114.0),
+    dict(
+        type='RandomAffine',
+        scaling_ratio_range=(0.5, 1.5),
+        border=(-img_scale[0] // 2, -img_scale[1] // 2)),
+    dict(
+        type='PhotoMetricDistortion',
+        brightness_delta=32,
+        contrast_range=(0.5, 1.5),
+        saturation_range=(0.5, 1.5),
+        hue_delta=18),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='Resize', keep_ratio=True),
+    dict(type='Pad', pad_to_square=True, pad_val=114.0),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
+]
+
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(416, 416),
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=False),
+            dict(type='RandomFlip'),
+            dict(type='Pad', size=(416, 416), pad_val=114.0),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='DefaultFormatBundle'),
+            dict(type='Collect', keys=['img'])
+        ])
+]
+
+data = dict(
+    samples_per_gpu=samples_per_gpu,
+    workers_per_gpu=4,
+    num_classes=2,
+    train=dict(
+        type='MultiImageMixDataset',
+        dataset=dict(
+            type=dataset_type,
+            ann_file=data_root + 'annotations/instances_train2017.json',
+            img_prefix=data_root + 'train2017/',
+            pipeline=[
+                    dict(type='LoadImageFromFile', to_float32=True),
+                    dict(type='LoadAnnotations', with_bbox=True)
+            ],
+        ),
+        pipeline=train_pipeline,
+        dynamic_scale=img_scale,
+    ),
+    val=dict(
+        type=dataset_type,
+        ann_file=data_root + 'annotations/instances_val2017.json',
+        img_prefix=data_root + 'val2017/',
+        test_mode=True,
+        pipeline=test_pipeline),
+    test=dict(
+        type=dataset_type,
+        ann_file=data_root + 'annotations/instances_val2017.json',
+        img_prefix=data_root + 'val2017/',
+        test_mode=True,
+        pipeline=test_pipeline)
+)

external/model-preparation-algorithm/configs/detection/cspdarknet_yolox_cls_incr/hpo_config.yaml

@@ -0,0 +1,16 @@
+metric: mAP
+search_algorithm: smbo
+early_stop: None
+hp_space:
+  learning_parameters.learning_rate:
+    param_type: quniform
+    range:
+      - 0.001
+      - 0.1
+      - 0.001
+  learning_parameters.batch_size:
+    param_type: qloguniform
+    range:
+      - 4
+      - 8
+      - 2

external/model-preparation-algorithm/configs/detection/cspdarknet_yolox_cls_incr/model.py

@@ -0,0 +1,3 @@
+_base_ = [
+  '../../../submodule/recipes/stages/_base_/models/detectors/yolox.custom.py'
+]

external/model-preparation-algorithm/configs/detection/cspdarknet_yolox_cls_incr/template_experimental.yaml

@@ -0,0 +1,51 @@
+# Description.
+model_template_id: ClassIncremental_Object_Detection_YOLOX
+name: YOLOX-ClsIncr
+task_type: DETECTION
+task_family: VISION
+instantiation: "CLASS"
+summary: Class-Incremental Object Detection for YOLOX
+application: ~
+
+# Algo backend.
+framework: MPA v1.1.0
+
+# Task implementations.
+entrypoints:
+  base: mpa_tasks.apis.detection.DetectionTrainTask
+  openvino: detection_tasks.apis.detection.OpenVINODetectionTask
+
+# Capabilities.
+capabilities: []
+
+# Hyperparameters.
+hyper_parameters:
+  base_path: ../configuration.yaml
+  parameter_overrides:
+    learning_parameters:
+      batch_size:
+        default_value: 16
+      learning_rate:
+        default_value: 0.0025
+      learning_rate_warmup_iters:
+        default_value: 500
+      num_iters:
+        default_value: 300
+    algo_backend:
+      train_type:
+        default_value: Incremental
+
+# Training resources.
+max_nodes: 1
+training_targets:
+  - GPU
+  - CPU
+
+# Stats.
+gigaflops: 20.6
+size: 9.1
+# # Inference options. Defined by OpenVINO capabilities, not Algo Backend or Platform.
+# inference_targets:
+#   - CPU
+#   - GPU
+#   - VPU

external/model-preparation-algorithm/configs/detection/mobilenetv2_atss_cls_incr/template_experimental.yaml

@@ -28,9 +28,9 @@ hyper_parameters:
       learning_rate:
         default_value: 0.001
       learning_rate_warmup_iters:
-        default_value: 200
+        default_value: 10
       num_iters:
-        default_value: 30
+        default_value: 100
     algo_backend:
       train_type:
         default_value: Incremental

external/model-preparation-algorithm/configs/detection/mobilenetv2_ssd_cls_incr/hpo_config.yaml

@@ -0,0 +1,16 @@
+metric: mAP
+search_algorithm: smbo
+early_stop: None
+hp_space:
+  learning_parameters.learning_rate:
+    param_type: quniform
+    range:
+      - 0.001
+      - 0.1
+      - 0.001
+  learning_parameters.batch_size:
+    param_type: qloguniform
+    range:
+      - 4
+      - 8
+      - 2

external/model-preparation-algorithm/configs/detection/mobilenetv2_ssd_cls_incr/model.py

@@ -0,0 +1,8 @@
+_base_ = [
+  '../../../submodule/samples/cfgs/models/backbones/ote_mobilenet_v2_w1.yaml',
+  '../../../submodule/recipes/stages/_base_/models/detectors/ssd.custom.py'
+]
+
+model = dict(
+    backbone=dict(out_indices=(4, 5,))
+)

external/model-preparation-algorithm/configs/detection/mobilenetv2_ssd_cls_incr/template_experimental.yaml

@@ -0,0 +1,51 @@
+# Description.
+model_template_id: ClassIncremental_Object_Detection_Gen3_SSD
+name: SSD-ClsIncr
+task_type: DETECTION
+task_family: VISION
+instantiation: "CLASS"
+summary: Class-Incremental Object Detection for SSD
+application: ~
+
+# Algo backend.
+framework: MPA v1.1.0
+
+# Task implementations.
+entrypoints:
+  base: mpa_tasks.apis.detection.DetectionTrainTask
+  openvino: detection_tasks.apis.detection.OpenVINODetectionTask
+
+# Capabilities.
+capabilities: []
+
+# Hyperparameters.
+hyper_parameters:
+  base_path: ../configuration.yaml
+  parameter_overrides:
+    learning_parameters:
+      batch_size:
+        default_value: 4
+      learning_rate:
+        default_value: 0.001
+      learning_rate_warmup_iters:
+        default_value: 200
+      num_iters:
+        default_value: 30
+    algo_backend:
+      train_type:
+        default_value: Incremental
+
+# Training resources.
+max_nodes: 1
+training_targets:
+  - GPU
+  - CPU
+
+# Stats.
+gigaflops: 20.6
+size: 9.1
+# # Inference options. Defined by OpenVINO capabilities, not Algo Backend or Platform.
+# inference_targets:
+#   - CPU
+#   - GPU
+#   - VPU

ote_sdk/requirements.txt

@@ -2,7 +2,7 @@ numpy>=1.16.4
 scikit-learn==0.24.*
 Shapely>=1.7.1,<=1.8.0
 networkx>=2.5,<2.8.1rc1
-opencv-python==4.5.5.*
+opencv-python==4.5.*
 pymongo==3.12.0
 omegaconf==2.1.*
 natsort>=6.0.0