Convert single layer caffe tests to onnx format

[WanliZhong]

Merged with: https://github.com/opencv/opencv_extra/pull/1176 (testdata also should be review) part of https://github.com/opencv/opencv/issues/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 https://github.com/opencv/opencv/pull/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

• 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.

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• [x] I agree to contribute to the project under Apache 2 License.
• [x] 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
• [x] 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

[WanliZhong]

I removed some layer tests because ONNX doesn't support them. Please leave comments if I should try to keep some of them.