Additional Comments for Conformance Denylist #25727
This PR adds additional comments on conformance denylist. Once BOOL type got support in 5.x, some test layer changed their failing issue.
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Added bool support to dnn #25605
Added bool support to dnn pipeline (CPU, OpenVINO and CUDA pipelines).
Added bool support to these layers(CPU and OpenVINO):
- Equal, Greater, GreaterOrEqual, Less, LessOrEqual
- Not
- And, Or, Xor
- Where
Enabled all the conformance tests for these layers.
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Element-wise test for 1D #25116
This PR introduces 1D parametrized test for element wise layer. The means that the tests covers following layer:
`Clip`, `ReLU6`, `ReLU`,
`GeLU`, `GeluApprox`, `TanH`,
`Swish`, `Mish`, `Sigmoid`,
`ELULayer`, `Abs`, `BNLL`,
`Ceil`, `Floor`, `LogLayer`,
`Round`, `Sqrt`, `Acos`,
`Acosh`, `Asin`, `Asinh`,
`Atan`, `Atanh`, `Cos`,
`Sin`, `Sinh`, `Tan`, `Erf`,
`Reciprocal`, `Cosh`, `HardSwish`,
`Softplus`, `Softsign`, `Celu`,
`HardSigmid`, `Selu`, `ThresholdedRelu`,
`Power`, `Exp`, `Sign`, `Shrink`,
`ChannelsPReLU`
Not sure if this is best way to implement this test.
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Add support for scalar and matrix multiplication in einsum #25595
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Disabled conversion to float of model's input #25555
In dnn 4.x usually any model's input is converted to float32 or float16 (except quantized models). Also mean and scale can be applied. In current dnn 5.x there is the same conversion except int32 and int64 types. I removed this conversion.
Here is how the pipeline works now:
- if input Mat type is float32, the pipeline applies mean and scale and may convert it to float16.
- if input Mat type is not float32, the pipeline preserves the input type and doesn't apply mean and scale
There was a conflict in protobuf parser between ONNX importer and tests. In ONNX importer any uint8 weight was handled as quantized weight and x = int8(x_uint8 - 128) conversion was used inside the protobuf parser. ONNX conformance tests used the same protobuf reader, so tests with uint8 inputs couldn't read the input values properly. I've made this conversion optional.
These ONNX conformance tests are enabled:
- test_add_uint8
- test_div_uint8
- test_mul_uint8
- test_sub_uint8
- test_max_int8
- test_max_uint8
- test_min_int8
- test_min_uint8
- test_mod_mixed_sign_int8
- test_mod_uint8
These tests were removed:
- Test_two_inputs.basic (when input is uint8)
- setInput.normalization (when input is uint8)
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Added int support for OpenVINO dnn backend #25458
Modified dnn OpenVINO integration to support type inference and int operations.
Added OpenVINO support to Cast, CumSum, Expand, Gather, GatherElements, Scatter, ScatterND, Tile layers.
I tried to add Reduce layer, but looks like OpenVINO uses float values inside Reduce operation so it can't pass our int tests.
OpenVINO uses int32 precision for int64 operations, so I've modified input values for int64 tests when backend is OpenVINO.
OpenVINO has a strange behavior with custom layers and int64 values. After model compilation OpenVINO may change types, so the model can have different output type. That's why these tests were disabled:
- Test_ArgMax_Int.random/0, where GetParam() = (4, NGRAPH/CPU)
- Test_ArgMax_Int.random/6, where GetParam() = (11, NGRAPH/CPU)
- Test_Reduce_Int.random/6, where GetParam() = (11, NGRAPH/CPU)
- Test_Reduce_Int.two_axes/6, where GetParam() = (11, NGRAPH/CPU)
Also these tests were temporary disabled, they didn't work on both 4.x and 5.x branches:
- Test_Caffe_layers.layer_prelu_fc/0, where GetParam() = NGRAPH/CPU
- Test_ONNX_layers.LSTM_Activations/0, where GetParam() = NGRAPH/CPU
- Test_ONNX_layers.Quantized_Convolution/0, where GetParam() = NGRAPH/CPU
- Test_ONNX_layers.Quantized_Eltwise_Scalar/0, where GetParam() = NGRAPH/CPU
- Test_TFLite.EfficientDet_int8/0, where GetParam() = NGRAPH/CPU
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Additional fixes to 0/1D tests #25487
This has additional fixes requited for 0/1D tests.
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1/0D test padding layer #25390
This PR introduces 0/1D test for `padding` layer.
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Improved segmentation sample #25559#25006
This pull request replaces caffe models with onnx for the dnn segmentation sample in cpp and python
fcnresnet-50 and fcnresnet-101 has been replaced
u2netp (foreground-background) segmentation onnx model has been added [U2NET](https://github.com/xuebinqin/U-2-Net)
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0/1D test for tile layer #25409
This PR introduces `0/1D` test for `Tile` layer. It also add fuctionality to support `0/1D` cases.
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0/1D Einsum Layer Test #25567
This PR introduces 0/1D test cases for Einsum layer.
TODO:
- Add support for 0D tensors to Einsum layer
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Change opencv_face_detector related tests and samples from caffe to onnx #25463
Part of https://github.com/opencv/opencv/issues/25314
This PR aims to change the tests related to opencv_face_detector from caffe framework to onnx. Tests in `test_int8_layer.cpp` and `test_caffe_importer.cpp` will be removed in https://github.com/opencv/opencv/pull/25323
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core: add universal intrinsics for fp16 #25196
Partially resolves the section "Universal intrinsics evolution in OpenCV 5.0" in https://github.com/opencv/opencv/issues/25019.
Universal intrinsics for bf16 will be added in a subsequent pull request.
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Remove goturn caffe model #25503
**Merged with:** https://github.com/opencv/opencv_extra/pull/1174
**Merged with:** https://github.com/opencv/opencv_contrib/pull/3729
Part of https://github.com/opencv/opencv/issues/25314
This PR aims to remove goturn tracking model because Caffe importer will be remove in 5.0
The GOTURN model will take **388 MB** of traffic for each download if converted to onnx. If the user wants to use the tracking method, we can recommend they use Vit or dasimRPN.
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Fix broken js build after moving HaarCascades to contrib #25324
The HaarCascades related are not completely cleaned up #25311 after #25198, which breaks the JavaScript build. The PR is to fix the issue.
Related PR: opencv/opencv_contrib#3712
Fixed ONNX Range layer to support any input type #25492
Fixed ONNX Range layer to support any input type
Extra PR: https://github.com/opencv/opencv_extra/pull/1173Fixes#25363
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Add logs of test failure to test_onnx_conformance_layer_filter_opencv_all_denylist.inl.hpp #25480
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This PR add logs to test failures to `test_onnx_conformance_layer_filter_opencv_all_denylist.inl.hpp` and it continuation of #25442
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0/1D test for BatchNorm layer #25420
This PR introduces support for 0/1D inputs in `BatchNorm` layer.
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Comments for parser denylist #25465
Relates to https://github.com/opencv/opencv/issues/21078
This PR is designed to figure out why the test in `test_onnx_conformance_layer_parser_denylist.inl.hpp` fails. Currently, conformance tests do not pass for the following reasons:
1. BOOL, INT(8, 16) types are not supported **(MAJOR)**
2. Some layers can not be created due to various reasons **(MAJOR)**
3. Shape mismatches while creating layers **(MAJOR)**
4. Some layers are expected to support dynamic parameter initialization **(MAJOR)**
5. Some layers are expected to receive weight as inputs (no idea why that is needed) **(MAJOR)**
6. Other unknown reasons
**(MAJOR)** - These are the most frequently encountered reasons for test failure.
The style of comments is not consistent everywhere. Let's keep this PR without merging, just for our reference.
A couple of tests are commented on since they have passed on the MacOS platform.
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CI pipeline with Windows 10 ARM64 for 5.x #25428
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Add cv::currentUIFramework #25354
issue https://github.com/opencv/opencv/issues/25329
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Remove unnecessary FIXIT section in grfmt_tiff.cpp #25447
No int64/uint64 is used in the code anymore.
grfmt_tiff.hpp includes the tiff.h header inside of the tiff_dummy_namespace declaration. One implication of this is that all namespaced declarations made in tiff.h become qualified with tiff_dummy_namespace::.
Because tiff.h includes standard library headers, the std namespace declarations are converted to tiff_dummy_namespace::std declarations.
Subsequently, grfmt_tiff.hpp declares using namespace tiff_dummy_namespace;.
This can lead to an ambiguity error during the resolution of the std namespace.
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Fix for IPP 2021.10 with OneAPI 2024 #25317fixes#25270
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Replaced caffe model with onnx for colorization sample #25433#25006
Improved sample for colorization with onnx model in cpp and python. Added a demo image in data folder for testing
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apps: createsamples: fix comment to remove last backslash #25445Close#25403
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Conformance test denylist reduce #25442
Comment out all passing tests in `test_onnx_conformance_layer_filter_opencv_all_denylist.inl.hpp` file.
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Fix race condition in InternalFFMpegRegister initialization. #25419
initLogger_ does not check if the logger has been initizalized before and it might initialize it several times from different threads, racing with other threads that are logging.
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Abduragim Shtanchaev
alexlyulkov
Alexander Smorkalov
Abduragim Shtanchaev
Gursimar Singh
Wanli
Yuantao Feng
Letu Ren
WU Jia
Alexander Smorkalov
Laurent Berger
Vincent Rabaud
JunX
Rostislav Vasilikhin
Kumataro
Maksim Shabunin