dnn(test): skip tests on 32-bit Windows

modules/dnn/test/test_backends.cpp

@@ -330,8 +330,11 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_v2_TensorFlow)
 
 TEST_P(DNNTestNetwork, SSD_VGG16)
 {
-    applyTestTag(CV_TEST_TAG_LONG, (target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_1GB : CV_TEST_TAG_MEMORY_2GB),
-                 CV_TEST_TAG_DEBUG_VERYLONG);
+    applyTestTag(
+        CV_TEST_TAG_MEMORY_2GB,
+        CV_TEST_TAG_LONG,
+        CV_TEST_TAG_DEBUG_VERYLONG
+    );
     if (backend == DNN_BACKEND_HALIDE && target == DNN_TARGET_CPU)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_HALIDE);  // TODO HALIDE_CPU
 

modules/dnn/test/test_onnx_importer.cpp

@@ -2786,6 +2786,8 @@ TEST_P(Test_ONNX_nets, YOLOv8)
 //  4. 1D mat dimension issue with the output of range operator
 TEST_P(Test_ONNX_nets, YOLOv7)
 {
+    applyTestTag(CV_TEST_TAG_MEMORY_2GB);
+
     std::string weightPath = _tf("models/yolov7_not_simplified.onnx", false);
     // Reference, which is collected with input size of 640x640
     std::vector<int> refClassIds{1, 16, 7};

modules/dnn/test/test_tf_importer.cpp

@@ -1804,7 +1804,10 @@ TEST_P(Test_TensorFlow_nets, Mask_RCNN)
     if (target == DNN_TARGET_CUDA_FP16)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA_FP16);
 
-    applyTestTag(CV_TEST_TAG_MEMORY_1GB, CV_TEST_TAG_DEBUG_VERYLONG);
+    applyTestTag(
+        CV_TEST_TAG_MEMORY_2GB,
+        CV_TEST_TAG_DEBUG_VERYLONG
+    );
     Mat img = imread(findDataFile("dnn/street.png"));
     std::string proto = findDataFile("dnn/mask_rcnn_inception_v2_coco_2018_01_28.pbtxt");
     std::string model = findDataFile("dnn/mask_rcnn_inception_v2_coco_2018_01_28.pb", false);