AC: add opencv section to configs

Author: APrigarina

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