AC: add opencv section to configs

models/public/Sphereface/accuracy-check.yml

@@ -5,6 +5,13 @@ models:
       - framework: openvino
         adapter: reid
 
+      - framework: opencv
+        inputs:
+          - name: data
+            type: INPUT
+            shape: 3, 112, 96
+        adapter: reid
+
     datasets:
       - name: lfw
 

models/public/aclnet-int8/accuracy-check.yml

@@ -5,6 +5,13 @@ models:
       - framework: openvino
         adapter: classification
 
+      - framework: opencv
+        inputs:
+          - name: result.1
+            type: INPUT
+            shape: 1, 1, 16000
+        adapter: classification
+
     datasets:
       - name: sound_classification
 

models/public/aclnet/accuracy-check.yml

@@ -5,6 +5,13 @@ models:
       - framework: openvino
         adapter: classification
 
+      - framework: opencv
+        inputs:
+          - name: input
+            type: INPUT
+            shape: 1, 1, 16000
+        adapter: classification
+
     datasets:
       - name: sound_classification
 

models/public/alexnet/accuracy-check.yml

@@ -28,6 +28,12 @@ models:
     launchers:
       - framework: openvino
         adapter: classification
+      - framework: opencv
+        inputs:
+          - name: data
+            type: INPUT
+            shape: 3, 227, 227
+        adapter: classification
 
     datasets:
       - name: imagenet_1000_classes

models/public/anti-spoof-mn3/accuracy-check.yml

@@ -5,6 +5,13 @@ models:
       - framework: openvino
         adapter: classification
 
+      - framework: opencv
+        inputs:
+          - name: actual_input_1
+            type: INPUT
+            shape: 3, 128, 128
+        adapter: classification
+
     datasets:
       - name: antispoof_test_data
 

models/public/background-matting-mobilenetv2/accuracy-check.yml

@@ -15,6 +15,21 @@ models:
             type: INPUT
             value: bgr*
 
+      - framework: opencv
+        adapter:
+          type: background_matting_with_pha_and_fgr
+          alpha_out: pha
+          foreground_out: fgr
+        inputs:
+          - name: src
+            type: INPUT
+            value: com*
+            shape: 3, 720, 1280
+          - name: bgr
+            type: INPUT
+            value: bgr*
+            shape: 3, 720, 1280
+
     datasets:
       - name: HumanMattingClips120
         reader: pillow_imread

models/public/bert-base-ner/accuracy-check.yml

@@ -13,6 +13,22 @@ models:
           - name: 'token_type_ids'
             type: INPUT
             value: 'segment_ids'
+      - framework: opencv
+        inputs:
+          - name: "input_ids"
+            type: INPUT
+            value: "input_ids"
+            shape: 128
+          - name: "attention_mask"
+            type: INPUT
+            value: 'input_mask'
+            shape: 128
+          - name: 'token_type_ids'
+            type: INPUT
+            value: 'segment_ids'
+            shape: 128
+        adapter: bert_ner
+
     datasets:
       - name: CONLL2003_bert_cased
         reader:

models/public/brain-tumor-segmentation-0001/accuracy-check.yml

@@ -7,6 +7,15 @@ models:
           type: brain_tumor_segmentation
           make_argmax: True
 
+      - framework: opencv
+        inputs:
+          - name: data_crop
+            type: INPUT
+            shape: 4, 128, 128, 128
+        adapter:
+          type: brain_tumor_segmentation
+          make_argmax: True
+
     datasets:
       - name: BraTS
 

models/public/brain-tumor-segmentation-0002/accuracy-check.yml

@@ -5,6 +5,13 @@ models:
       - framework: openvino
         adapter:
           type: brain_tumor_segmentation
+      - framework: opencv
+        inputs:
+          - name: '0'
+            type: INPUT
+            shape: 4, 128, 128, 128
+        adapter:
+          type: brain_tumor_segmentation
 
     datasets:
       - name: BraTS_2017

models/public/caffenet/accuracy-check.yml

@@ -28,6 +28,12 @@ models:
     launchers:
       - framework: openvino
         adapter: classification
+      - framework: opencv
+        inputs:
+          - name: data
+            type: INPUT
+            shape: 3, 227, 227
+        adapter: classification
 
     datasets:
       - name: imagenet_1000_classes

models/public/cocosnet/accuracy-check.yml

@@ -22,6 +22,21 @@ evaluations:
               type: INPUT
               value: "(.*)ADE(.*)train(.*).png"
 
+        - framework: opencv
+          inputs:
+            - name: "input_seg_map"
+              type: INPUT
+              value: "(.*)ADE(.*)val(.*).png"
+              shape: 151, 256, 256
+            - name: "ref_image"
+              type: INPUT
+              value: "(.*)train(.*).jpg"
+              shape: 3, 256, 256
+            - name: "ref_seg_map"
+              type: INPUT
+              value: "(.*)ADE(.*)train(.*).png"
+              shape: 151, 256, 256
+
       datasets:
         - name: cocosnet_image_translation
 

models/public/colorization-siggraph/accuracy-check.yml

@@ -15,6 +15,24 @@ models:
             type: CONST_INPUT
             value: 0
             shape: [1, 1, 256, 256]
+      - framework: opencv
+        inputs:
+          - name: data_l
+            type: INPUT
+            shape: 1, 256, 256
+          - name: "user_ab"
+            type: CONST_INPUT
+            value: 0
+            shape: [2, 256, 256]
+          - name: "user_map"
+            type: CONST_INPUT
+            value: 0
+            shape: [1, 256, 256]
+        adapter:
+          type: image_processing
+          std: 1
+          cast_to_uint8: false
+
     datasets:
       - name: imagenet_colorization
         subsample_size: 2000

models/public/colorization-v2/accuracy-check.yml

@@ -6,6 +6,16 @@ models:
           type: image_processing
           std: 1
           cast_to_uint8: false
+      - framework: opencv
+        inputs:
+          - name: data_l
+            type: INPUT
+            shape: 1, 256, 256
+        adapter:
+          type: image_processing
+          std: 1
+          cast_to_uint8: false
+
     datasets:
       - name: imagenet_colorization
         subsample_size: 2000

models/public/common-sign-language-0001/accuracy-check.yml

@@ -9,6 +9,14 @@ models:
             name: input
             layout: NCDHW
 
+      - framework: opencv
+        inputs:
+          - name: input
+            type: INPUT
+            layout: NCDHW
+            shape: 3, 8, 224, 224
+        adapter: classification
+
     datasets:
       - name: jester
 

models/public/ctdet_coco_dlav0_512/accuracy-check.yml

@@ -8,6 +8,16 @@ models:
           width_height_out: width_height
           regression_out: regression
 
+      - framework: opencv
+        inputs:
+          - name: input.1
+            type: INPUT
+            shape: 3, 512, 512
+        adapter:
+          type: ctdet
+          center_heatmap_out: center_heatmap
+          width_height_out: width_height
+          regression_out: regression
 
     datasets:
       - name: ms_coco_detection_80_class_without_background

models/public/ctpn/accuracy-check.yml

@@ -8,6 +8,17 @@ models:
           bbox_pred_out: 'rpn_bbox_pred/Reshape_1'
         allow_reshape_input: True
 
+      - framework: opencv
+        inputs:
+          - name: Placeholder
+            type: INPUT
+            shape: 3, 600, 600
+        adapter:
+          type: ctpn_text_detection
+          cls_prob_out: 'Reshape_2'
+          bbox_pred_out: 'rpn_bbox_pred/Reshape_1'
+        allow_reshape_input: True
+
     datasets:
       - name: ICDAR2013_detection
 

models/public/deblurgan-v2/accuracy-check.yml

@@ -41,6 +41,14 @@ models:
         adapter:
           type: image_processing
           reverse_channels: True
+      - framework: opencv
+        inputs:
+          - name: blur_image
+            type: INPUT
+            shape: 3, 736, 1312
+        adapter:
+          type: image_processing
+          reverse_channels: True
 
     datasets:
       - name: GoPro

models/public/deeplabv3/accuracy-check.yml

@@ -4,6 +4,13 @@ models:
       - framework: openvino
         adapter: segmentation
 
+      - framework: opencv
+        inputs:
+          - name: mul_1/placeholder_port_1
+            type: INPUT
+            shape: 3, 513, 513
+        adapter: segmentation
+
     datasets:
       - name: VOC2012_Segmentation
         preprocessing:

models/public/densenet-121-tf/accuracy-check.yml

@@ -4,6 +4,13 @@ models:
       - framework: openvino
         adapter: classification
 
+      - framework: opencv
+        inputs:
+          - name: input_1
+            type: INPUT
+            shape: 3, 224, 224
+        adapter: classification
+
     datasets:
       - name: imagenet_1000_classes
         preprocessing:

models/public/densenet-121/accuracy-check.yml

@@ -29,6 +29,12 @@ models:
     launchers:
       - framework: openvino
         adapter: classification
+      - framework: opencv
+        inputs:
+          - name: data
+            type: INPUT
+            shape: 3, 224, 224
+        adapter: classification
 
     datasets:
       - name: imagenet_1000_classes

models/public/detr-resnet50/accuracy-check.yml

@@ -33,6 +33,15 @@ models:
           type: detr
           scores_out: "scores"
           boxes_out: "boxes"
+      - framework: opencv
+        inputs:
+          - name: input
+            type: INPUT
+            shape: 3, 800, 1137
+        adapter:
+          type: detr
+          scores_out: "scores"
+          boxes_out: "boxes"
     datasets:
       - name: ms_coco_detection_91_classes
         reader: pillow_imread

models/public/dla-34/accuracy-check.yml

@@ -41,6 +41,12 @@ models:
     launchers:
       - framework: openvino
         adapter: classification
+      - framework: opencv
+        inputs:
+          - name: data
+            type: INPUT
+            shape: 3, 224, 224
+        adapter: classification
 
     datasets:
       - name: imagenet_1000_classes

models/public/drn-d-38/accuracy-check.yml

@@ -5,6 +5,15 @@ models:
         adapter:
           type: segmentation
           make_argmax: true
+      - framework: opencv
+        inputs:
+          - name: input
+            type: INPUT
+            shape: 3, 1024, 2048
+        adapter:
+          type: segmentation
+          make_argmax: true
+
     datasets:
       - name: cityscapes
         metrics:

models/public/efficientdet-d0-tf/accuracy-check.yml

@@ -3,6 +3,13 @@ models:
     launchers:
       - framework: openvino
         adapter: ssd
+      - framework: opencv
+        inputs:
+          - name: image_arrays/placeholder_port_0
+            type: INPUT
+            shape: 3, 512, 512
+        adapter: ssd
+
     datasets:
       - name: ms_coco_detection_90_class_without_background
         preprocessing:

models/public/efficientdet-d1-tf/accuracy-check.yml

@@ -3,6 +3,13 @@ models:
     launchers:
       - framework: openvino
         adapter: ssd
+      - framework: opencv
+        inputs:
+          - name: image_arrays/placeholder_port_0
+            type: INPUT
+            shape: 3, 640, 640
+        adapter: ssd
+
     datasets:
       - name: ms_coco_detection_90_class_without_background
         preprocessing: