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Merge pull request #29134 from svigh:gapi_u8_nd_mats_onnx_layout_fix

Merge pull request #29134 from svigh/gapi_u8_nd_mats_onnx_layout_fix

Gapi u8 N-D mats onnx layout workaround #29134

### Pull Request Readiness Checklist

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

- [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
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
This commit is contained in:
Vigh Sebastian
2026-05-26 18:09:44 +03:00
committed by GitHub
parent 05acc5d4c6
commit 8ec62ad346
2 changed files with 35 additions and 3 deletions
@@ -330,7 +330,8 @@ inline void preprocess(const cv::Mat& src,
cv::Mat& dst) {
// CNN input type
const auto type = toCV(ti.type);
if (src.depth() != CV_8U) {
if (src.depth() != CV_8U || src.dims > 2) {
// Just pass the tensor as-is.
// No layout or dimension transformations done here!
// TODO: This needs to be aligned across all NN backends.
@@ -338,10 +339,10 @@ inline void preprocess(const cv::Mat& src,
if (tensor_dims.size() == ti.dims.size()) {
for (size_t i = 0; i < ti.dims.size(); ++i) {
GAPI_Assert((ti.dims[i] == -1 || ti.dims[i] == tensor_dims[i]) &&
"Non-U8 tensor dimensions should match with all non-dynamic NN input dimensions");
"Tensor dimensions should match with all non-dynamic NN input dimensions");
}
} else {
GAPI_Error("Non-U8 tensor size should match with NN input");
GAPI_Error("Tensor size should match with NN input");
}
dst = src;