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CVS-133383 Update models used in nightly/stress tests (#23157) 

Old models listed in configs were removed from omz repository

### Tickets:
 - CVS-133383
 
Models changed basing on docs and availability in
[omz_repo](https://github.com/openvinotoolkit/open_model_zoo/tree/master/models)
-
https://docs.openvino.ai/nightly/omz_demos_classification_demo_python.html
-
https://docs.openvino.ai/nightly/omz_demos_face_recognition_demo_python.html
-
https://docs.openvino.ai/nightly/omz_demos_classification_demo_python.html
-
https://docs.openvino.ai/nightly/omz_demos_single_human_pose_estimation_demo_python.html
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wkobielx 2024-03-08 12:18:00 +01:00 committed by GitHub
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3 changed files with 49 additions and 57 deletions
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74
tests/stress_tests/.automation/memcheck_tests/nightly_configs/desktop_test_config.xml
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@ -6,77 +6,69 @@
<models>
<!--Models with FP32 precision-->
<model name="mobilenet-v2-1.4-224" precision="FP32" source="omz" />
<model name="brain-tumor-segmentation-0001" precision="FP32" source="omz" />
<model name="brain-tumor-segmentation-0002" precision="FP32" source="omz" />
<model name="faster_rcnn_inception_resnet_v2_atrous_coco" precision="FP32" source="omz" />
<model name="yolo-v2-tf" precision="FP32" source="omz" />
<model name="se-inception" precision="FP32" source="omz" />
<model name="convnext-tiny" precision="FP32" source="omz" />
<model name="efficientnet-b0" precision="FP32" source="omz" />
<model name="mobilenet-v1-1.0-224-tf" precision="FP32" source="omz" />
<model name="mask_rcnn_resnet50_atrous_coco" precision="FP32" source="omz" />
<model name="ssd_mobilenet_v1_coco" precision="FP32" source="omz" />
<model name="googlenet-v3" precision="FP32" source="omz" />
<model name="alexnet" precision="FP32" source="omz" />
<model name="googlenet-v4-tf" precision="FP32" source="omz" />
<model name="ssd300" precision="FP32" source="omz" />
<model name="vgg19" precision="FP32" source="omz" />
<model name="googlenet-v1" precision="FP32" source="omz" />
<model name="yolo-v3-tf" precision="FP32" source="omz" />
<model name="mtcnn-o" precision="FP32" source="omz" />
<model name="yolo-v1-tiny-tf" precision="FP32" source="omz" />
<model name="pedestrian-and-vehicle-detector-adas-0001" precision="FP32" source="omz" />
<model name="mixnet-l" precision="FP32" source="omz" />
<model name="googlenet-v1-tf" precision="FP32" source="omz" />
<model name="yolo-v3-tf" precision="FP32" source="omz" />
<model name="face-reidentification-retail-0095" precision="FP32" source="omz" />
<model name="yolo-v1-tiny-tf" precision="FP32" source="omz" />
<model name="yolo-v2-tiny-tf" precision="FP32" source="omz" />
<model name="ssd512" precision="FP32" source="omz" />
<model name="brain-tumor-segmentation-0002" precision="FP32" source="omz" />
<model name="Sphereface" precision="FP32" source="omz" />
<model name="googlenet-v2" precision="FP32" source="omz" />
<model name="pedestrian-detection-adas-0002" precision="FP32" source="omz" />
<model name="face-detection-retail-0004" precision="FP32" source="omz" />
<model name="googlenet-v2-tf" precision="FP32" source="omz" />
<model name="ctdet_coco_dlav0_512" precision="FP32" source="omz" />
<model name="ctpn" precision="FP32" source="omz" />
<model name="i3d-rgb-tf" precision="FP32" source="omz" />
<model name="mobilenet-v2" precision="FP32" source="omz" />
<model name="mobilenet-ssd" precision="FP32" source="omz" />
<model name="se-resnext-50" precision="FP32" source="omz" />
<model name="caffenet" precision="FP32" source="omz" />
<model name="mtcnn-r" precision="FP32" source="omz" />
<model name="se-resnet-50" precision="FP32" source="omz" />
<model name="densenet-121" precision="FP32" source="omz" />
<model name="ssdlite_mobilenet_v2" precision="FP32" source="omz" />
<model name="resnest-50-pytorch" precision="FP32" source="omz" />
<model name="levit-128s" precision="FP32" source="omz" />
<model name="face-recognition-resnet100-arcface-onnx" precision="FP32" source="omz" />
<model name="resnet-50-pytorch" precision="FP32" source="omz" />
<model name="densenet-121-tf" precision="FP32" source="omz" />
<model name="action-recognition-0001-decoder" precision="FP32" source="omz" />
<model name="action-recognition-0001-encoder" precision="FP32" source="omz" />
<model name="driver-action-recognition-adas-0002-decoder" precision="FP32" source="omz" />
<!--Models with FP16 precision-->
<model name="mobilenet-v2-1.4-224" precision="FP16" source="omz" />
<model name="brain-tumor-segmentation-0001" precision="FP16" source="omz" />
<model name="brain-tumor-segmentation-0002" precision="FP16" source="omz" />
<model name="faster_rcnn_inception_resnet_v2_atrous_coco" precision="FP16" source="omz" />
<model name="yolo-v2-tf" precision="FP16" source="omz" />
<model name="se-inception" precision="FP16" source="omz" />
<model name="convnext-tiny" precision="FP16" source="omz" />
<model name="efficientnet-b0" precision="FP16" source="omz" />
<model name="mobilenet-v1-1.0-224-tf" precision="FP16" source="omz" />
<model name="mask_rcnn_resnet50_atrous_coco" precision="FP16" source="omz" />
<model name="ssd_mobilenet_v1_coco" precision="FP16" source="omz" />
<model name="googlenet-v3" precision="FP16" source="omz" />
<model name="alexnet" precision="FP16" source="omz" />
<model name="googlenet-v4-tf" precision="FP16" source="omz" />
<model name="ssd300" precision="FP16" source="omz" />
<model name="vgg19" precision="FP16" source="omz" />
<model name="googlenet-v1" precision="FP16" source="omz" />
<model name="yolo-v3-tf" precision="FP16" source="omz" />
<model name="mtcnn-o" precision="FP16" source="omz" />
<model name="yolo-v1-tiny-tf" precision="FP16" source="omz" />
<model name="pedestrian-and-vehicle-detector-adas-0001" precision="FP16" source="omz" />
<model name="mixnet-l" precision="FP16" source="omz" />
<model name="googlenet-v1-tf" precision="FP16" source="omz" />
<model name="yolo-v3-tf" precision="FP16" source="omz" />
<model name="face-reidentification-retail-0095" precision="FP16" source="omz" />
<model name="yolo-v1-tiny-tf" precision="FP16" source="omz" />
<model name="yolo-v2-tiny-tf" precision="FP16" source="omz" />
<model name="ssd512" precision="FP16" source="omz" />
<model name="brain-tumor-segmentation-0002" precision="FP16" source="omz" />
<model name="Sphereface" precision="FP16" source="omz" />
<model name="googlenet-v2" precision="FP16" source="omz" />
<model name="pedestrian-detection-adas-0002" precision="FP16" source="omz" />
<model name="face-detection-retail-0004" precision="FP16" source="omz" />
<model name="googlenet-v2-tf" precision="FP16" source="omz" />
<model name="ctdet_coco_dlav0_512" precision="FP16" source="omz" />
<model name="ctpn" precision="FP16" source="omz" />
<model name="i3d-rgb-tf" precision="FP16" source="omz" />
<model name="mobilenet-v2" precision="FP16" source="omz" />
<model name="mobilenet-ssd" precision="FP16" source="omz" />
<model name="se-resnext-50" precision="FP16" source="omz" />
<model name="caffenet" precision="FP16" source="omz" />
<model name="mtcnn-r" precision="FP16" source="omz" />
<model name="se-resnet-50" precision="FP16" source="omz" />
<model name="densenet-121" precision="FP16" source="omz" />
<model name="ssdlite_mobilenet_v2" precision="FP16" source="omz" />
<model name="resnest-50-pytorch" precision="FP16" source="omz" />
<model name="levit-128s" precision="FP16" source="omz" />
<model name="face-recognition-resnet100-arcface-onnx" precision="FP16" source="omz" />
<model name="resnet-50-pytorch" precision="FP16" source="omz" />
<model name="densenet-121-tf" precision="FP16" source="omz" />
<model name="action-recognition-0001-decoder" precision="FP16" source="omz" />
<model name="action-recognition-0001-encoder" precision="FP16" source="omz" />
<model name="driver-action-recognition-adas-0002-decoder" precision="FP16" source="omz" />
@ -106,4 +98,4 @@
<model name="yolo-v2-ava-0001" precision="FP16-INT8" source="omz" />
<model name="person-detection-action-recognition-0005" precision="FP16-INT8" source="omz" />
</models>
</attributes>
</attributes>

24
tests/stress_tests/.automation/memleaks_tests/nightly_configs/desktop_test_config.xml
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@ -1,27 +1,27 @@
<cases>
<device name="CPU" iterations="1000" processes="1" threads="1">
<model name="alexnet" precision="FP32" source="omz" />
<model name="densenet-121-tf" precision="FP32" source="omz" />
</device>
<device name="CPU" iterations="1000" processes="1" threads="1">
<model name="mobilenet-ssd" precision="FP32" source="omz" />
<model name="ssd_mobilenet_v1_coco" precision="FP32" source="omz" />
</device>
<device name="CPU" iterations="1000" processes="1" threads="1">
<model name="mtcnn-r" precision="FP32" source="omz" />
<model name="face-recognition-resnet100-arcface-onnx" precision="FP32" source="omz" />
</device>
<device name="GPU" iterations="1000" processes="1" threads="1">
<model name="alexnet" precision="FP32" source="omz" />
<model name="densenet-121-tf" precision="FP32" source="omz" />
</device>
<device name="GPU" iterations="1000" processes="1" threads="1">
<model name="mobilenet-ssd" precision="FP32" source="omz" />
<model name="ssd_mobilenet_v1_coco" precision="FP32" source="omz" />
</device>
<device name="GPU" iterations="1000" processes="1" threads="1">
<model name="mtcnn-r" precision="FP32" source="omz" />
<model name="face-recognition-resnet100-arcface-onnx" precision="FP32" source="omz" />
</device>
<device name="CPU" iterations="1000" processes="1" threads="1">
@ -33,15 +33,15 @@
</device>
<device name="CPU" iterations="1000" processes="1" threads="1">
<model name="alexnet" precision="FP32" source="omz" />
<model name="mobilenet-ssd" precision="FP32" source="omz" />
<model name="mtcnn-r" precision="FP32" source="omz" />
<model name="densenet-121-tf" precision="FP32" source="omz" />
<model name="ssd_mobilenet_v1_coco" precision="FP32" source="omz" />
<model name="face-recognition-resnet100-arcface-onnx" precision="FP32" source="omz" />
</device>
<device name="GPU" iterations="1000" processes="1" threads="1">
<model name="alexnet" precision="FP32" source="omz" />
<model name="mobilenet-ssd" precision="FP32" source="omz" />
<model name="mtcnn-r" precision="FP32" source="omz" />
<model name="densenet-121-tf" precision="FP32" source="omz" />
<model name="ssd_mobilenet_v1_coco" precision="FP32" source="omz" />
<model name="face-recognition-resnet100-arcface-onnx" precision="FP32" source="omz" />
</device>
</cases>

8
tests/stress_tests/.automation/unittests/nightly_configs/desktop_test_config.xml
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@ -15,8 +15,8 @@
<value>GPU</value>
</devices>
<models>
<model name="alexnet" precision="FP32" source="omz" />
<model name="mobilenet-ssd" precision="FP32" source="omz" />
<model name="mtcnn-r" precision="FP32" source="omz" />
<model name="densenet-121-tf" precision="FP32" source="omz" />
<model name="ssd_mobilenet_v1_coco" precision="FP32" source="omz" />
<model name="face-recognition-resnet100-arcface-onnx" precision="FP32" source="omz" />
</models>
</attributes>
</attributes>