Merged with: opencv/opencv_extra#1176 (testdata also should be review)
part of #25314

This PR is used to convert all caffe tests with 'single' layer to onnx format. Tests in test_int8_layer.cpp and test_caffe_importer.cpp will be removed in #25323

Most layers converted by caffe2onnx
Some of them are generated by pytorch and onnxruntime
Some of them are wrong after converting, so I use onnx-modifier to correct it.

EXTRA NOTE

UPDATE(2024-08): All below tests are kept because we decide to keep Caffe platform.

• Remove layer_lrn_spatial: norm_region is WITHIN_CHANNEL , but ONNX defines the default mode as ACROSS_CHANNELS, and if users want it, they may try BatchNormalization. (ref: LRN in ONNX)

• Change layer_deconvolution: onnx doesn't define deconvolution operator, use ConvTranspose to replace. (ref: ConvTranspose in ONNX)

• Remove InnerProduct: ONNX doesn't define this layer, user may convert it to GEMM or MatMul

• Change layer_mvn: onnx doesn't define MVN operator, use InstanceNormalization to replace.

• Remove layer_batch_norm_local_stats: use_global_stats: false is useless in ONNX. (ref: BatchNormalization in ONNX)

• Remove layer_eltwise: the model has a node with 2 inputs but from the same layer, which then causes an error. However, we have enough eltwise tests.

• Remove accum and accum_ref: they use 1x2x2x4 accum 1x3x8x12, we can't use ADD operator to replace it.

• Remove flow_wrap: ONNX doesn't define this operator.

• Remove DataAugmentation: ONNX doesn't define this operator.

• Remove nearest_2inps and nearest: ONNX doesn't define Resample operator.

• Remove Correlation: ONNX doesn't define this operator.

• Remove conv_2_inps: ONNX doesn't support this defination, no need to test it in ONNX.

• Remove layer_interp: ONNX doesn't define Interp operator.

• Disabled net_roi_pooling: can be replaced by RoiAlign operator in ONNX, but OpenCV dnn doesn't support.

• Remove reshape_splice_split: Can't be converted to ONNX format. Because there are many re-use layers in caffe format.

Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

• I agree to contribute to the project under Apache 2 License.
• To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
• The PR is proposed to the proper branch
• There is a reference to the original bug report and related work
• There is accuracy test, performance test and test data in opencv_extra repository, if applicable
  Patch to opencv_extra has the same branch name.
• The feature is well documented and sample code can be built with the project CMake