ermig1979 / synet Goto Github PK

Ошибка при конвертировании text-detection-0002.bin/text-detection-0002.xml

Cant't convert layer : type = Interp, name = pixel_cls/resize_images/ResizeBilinear, id = 122 !

VS 2019 x64 Debug

face_detection конвертируется нормально

I try to convert my own custom onnx model but I get an error.

Convert network from Onnx to Synet : Can't found layer onnx !
Can't found layer onnx !
Can't found layer onnx !
Can't found layer onnx !
Can't convert node[4]: type: Slice, name: Slice_4 ( images onnx::Slice_127 onnx::Slice_128 onnx::Slice_126 onnx::Slice_129 ) -> ( onnx::Slice_130 ) { } !

Conversion finished with errors!
Do you have any idea why I get this error and maybe how I could fix it?

Hello,

I tried to use the following model:
Expected output:
Name: age_conv3, shape: 1, 1, 1, 1 - Estimated age divided by 100.
Name: prob, shape: 1, 2, 1, 1 - Softmax output across 2 type classes [0 - female, 1 - male].

Received output example:
age_conv3 = [0.349784911, 0.328657120, 0.373537451, 0.369158268] (4 values instead of one)
prob = [0.0271999519, 0.972800076, 0.0115807839, 0.988419175, 0.0321026519, 0.967897415, 0.0114557156, 0.988544285] (8 values instead of 2)

The question is, why do I receive such output? Maybe I use wrong output processing for StubLayer?

Thank you

After making some testing I found that the performance of the x64 build is substantially better than win32 build (about 50% difference). The input was a standard, 4x down scaled 720p video.

Is this an expected behavior? Any ways to improve the win32 performance?

Hello,

I can see that the ONNX support has been added.
But how do I convert from the .onnx model file? Your converter requires .bin and .xml

Thank you

Hello Igor!

Can you suggest what kind of tracker is best to use with your detector?

Or maybe there is some kind of generic tracker incorporated with SIMD library?

Thank you!

I trained a custom model with yolov5 and export to onnx format, then convert to synet format.
The following code detected nothing, but the onnx model works fine with detect.py of yolov5.

   Net net;
    net.Load("test.xml", "test.bin");

    net.Reshape(1920, 1920, 1);

    Shape shape = net.NchwShape();

    View original;
    original.Load("test0.png");

    View resized(shape[3], shape[2], original.format);
    Simd::Resize(original, resized, ::SimdResizeMethodArea);

    net.SetInput(resized, 0.0f, 255.0f);

    net.Forward();

    Regions objects = net.GetRegions(original.width, original.height, 0.5f, 0.5f);
    uint32_t white = 0xFFFFFFFF;
    for (size_t i = 0; i < objects.size(); ++i)
    {
        const Region & object = objects[i];
        ptrdiff_t l = ptrdiff_t(object.x - object.w / 2);
        ptrdiff_t t = ptrdiff_t(object.y - object.h / 2);
        ptrdiff_t r = ptrdiff_t(object.x + object.w / 2);
        ptrdiff_t b = ptrdiff_t(object.y + object.h / 2);
        Simd::DrawRectangle(original, l, t, r, b, white);
    }
    original.Save("test0r.ppm");

    return 0;

Can't convert layer : id = 210 , name = Gather_199549/Cast_122100_const , type = Const , version = opset1 !
Can't convert IE model v10!

Unknown element_type = i32 !
Can't convert layer : id = 383 , name = up_sampling2d/Shape/GatherNCHWtoNHWC/Cast_123490_const , type = Const , version = opset1 !
Can't convert IE model v10!

Basically I can convert only the oldest, early 2019 models.

Hi. There is a problem: On visual studio 2019 and 2015 (32 bit, not tested on others, 64 bit works) it is impossible to convert and load synet network. Here is screenshot of converting error:

The error while trying load is similar.

In memory windows there is something strange: the pointer to virtual table begins with 4 byte offset. But after that there is a trash, and only after - there is a first "params" data. So, I think it is the compiler bug, but not sure. On gcc everything works fine. Can you test your framework on visual studio to investigate this bug?

Hello!

Is working with INT8 models currently supported?

In files perf.sh, test.sh, check.sh the quantization check is disabled, as well as test_003i and test_009i.
If I try to enable them manually, it start require file quant.xml, but it is missing from the project.

Hello,

How do grayscale frames (instead of bgra) affect performance and detection accuracy of Synet algorithms?

Thank you

https://storage.openvinotoolkit.org/repositories/open_model_zoo/2022.1/models_bin/3/person-detection-0303/FP32/

It says

Not implemented layer : name = Divide_4866 ; type = Divide ; id = 282
Can't convert layer : id = 285 , name = 610 , type = Interpolate , version = opset4 !
Can't convert IE model v11!
Result: 0

ggml.ai can quantize a model to int4/8, and can seed up the inference of a model.

Hello,

I get the following during the compilation under VS2019:

1>------ Rebuild All started: Project: Synet, Configuration: Release x64 ------
1>Synet.cpp
1>C:\Synet-master\src\Synet\Utils\Permute.h(88,30): error C2039: 'SimdTensorDataType': is not a member of '`global namespace''
1>C:\Synet-master\src\Synet\Utils\Permute.h(88,56): error C3646: 'Convert': unknown override specifier
1>C:\Synet-master\src\Synet\Utils\Permute.h(88,57): error C2275: 'Synet::TensorType': illegal use of this type as an expression
1>C:\Synet-master\src\Synet\Params.h(237): message : see declaration of 'Synet::TensorType'
1>C:\Synet-master\src\Synet\Utils\Permute.h(88,68): error C2146: syntax error: missing ')' before identifier 'type'
1>C:\Synet-master\src\Synet\Utils\Permute.h(89,9): error C2334: unexpected token(s) preceding '{'; skipping apparent function body
1>Done building project "Synet.vcxproj" -- FAILED.
========== Rebuild All: 0 succeeded, 1 failed, 0 skipped ==========

Hello, I am trying to compile Synet.sln in vs 2019, but I have an error and part of the project is not compiled.

16>C:\Synet\src\Synet\Utils\Activation.h(175,11): error C2039: 'SimdSynetSwish32f': is not a member of 'global namespace''
16>C:\Synet\src\Synet\Utils\Activation.h(175,1): error C3861: 'SimdSynetSwish32f': identifier not found
16>C:\Synet\src\Synet\Converters\InferenceEngineV10.h(299,35): warning C4018: '<': signed/unsigned mismatch
17>C:\Synet\src\Synet\Utils\Activation.h(175,11): error C2039: 'SimdSynetSwish32f': is not a member of 'global namespace'' (compiling source file ..\..\src\Test\TestQuantization.cpp) 18>C:\Synet\src\Synet\Utils\Activation.h(175,11): error C2039: 'SimdSynetSwish32f': is not a member of 'global namespace'' (compiling source file ....\src\Test\TestPrecision.cpp)
17>C:\Synet\src\Synet\Utils\Activation.h(175,1): error C3861: 'SimdSynetSwish32f': identifier not found (compiling source file ....\src\Test\TestQuantization.cpp)
16>Done building project "UseFaceDetection.vcxproj" -- FAILED.
18>C:\Synet\src\Synet\Utils\Activation.h(175,1): error C3861: 'SimdSynetSwish32f': identifier not found (compiling source file ....\src\Test\TestPrecision.cpp)
20>------ Build started: Project: TestOnnx, Configuration: Release Win32 ------
19>C:\Synet\src\Synet\Utils\Activation.h(175,11): error C2039: 'SimdSynetSwish32f': is not a member of 'global namespace'' 17>C:\Synet\src\Synet\Converters\Deoptimizer.h(149,65): warning C4018: '<': signed/unsigned mismatch (compiling source file ..\..\src\Test\TestQuantization.cpp) 19>C:\Synet\src\Synet\Utils\Activation.h(175,1): error C3861: 'SimdSynetSwish32f': identifier not found 15>C:\Synet\src\Synet\Utils\Activation.h(175,11): error C2039: 'SimdSynetSwish32f': is not a member of 'global namespace'' (compiling source file ....\src\Test\TestInferenceEngine.cpp)
17>C:\Synet\src\Test\TestQuantization.h(333,39): warning C4018: '<=': signed/unsigned mismatch (compiling source file ....\src\Test\TestQuantization.cpp)
18>C:\Synet\src\Test\TestDetectionPrecision.h(475,13): warning C4018: '<': signed/unsigned mismatch (compiling source file ....\src\Test\TestPrecision.cpp)
15>C:\Synet\src\Synet\Utils\Activation.h(175,1): error C3861: 'SimdSynetSwish32f': identifier not found (compiling source file ....\src\Test\TestInferenceEngine.cpp)
17>Done building project "TestQuantization.vcxproj" -- FAILED.
18>Done building project "TestPrecision.vcxproj" -- FAILED.
19>Done building project "TestPerformanceDifference.vcxproj" -- FAILED.
14>C:\Synet\src\Synet\Utils\Activation.h(175,11): error C2039: 'SimdSynetSwish32f': is not a member of 'global namespace'' (compiling source file ..\..\src\Test\TestDarknet.cpp) 14>C:\Synet\src\Synet\Utils\Activation.h(175,1): error C3861: 'SimdSynetSwish32f': identifier not found (compiling source file ..\..\src\Test\TestDarknet.cpp) 20>TestOnnx.cpp 20>TestImage.cpp 14>Done building project "TestDarknet.vcxproj" -- FAILED. 15>C:\Synet\src\Synet\Converters\InferenceEngineV10.h(299,35): warning C4018: '<': signed/unsigned mismatch (compiling source file ..\..\src\Test\TestInferenceEngine.cpp) 15>Done building project "TestInferenceEngine.vcxproj" -- FAILED. 20>C:\Synet\src\Synet\Utils\Activation.h(175,11): error C2039: 'SimdSynetSwish32f': is not a member of 'global namespace'' (compiling source file ....\src\Test\TestOnnx.cpp)
20>C:\Synet\src\Synet\Utils\Activation.h(175,1): error C3861: 'SimdSynetSwish32f': identifier not found (compiling source file ....\src\Test\TestOnnx.cpp)
20>Done building project "TestOnnx.vcxproj" -- FAILED.
========== Build: 13 succeeded, 7 failed, 0 up-to-date, 0 skipped ==========`

I try to compile Synet on win10, and test_onnx can't recognize convert mode;

E:\projects\synet\bin\v143\x64\Release>.\TestOnnx.exe -m convert -fw best.onnx -sm best.xml -sw best.bin
[000] Error: Unknown mode :

Hello!
I'm trying to run the network on this model. I successfully converted the model, but when I run the network I receive the following error

Access violation writing location

in the file ImgToCol.h:194

As the title.

Hello Igor!

What do you think about making a brief instruction on how to annotate and train models to be compatible with Synet?
Which software to use for annotation, which for training, general recommendations/requirements, etc.

It would be awesome to have that.

Thank you!

When I try to load any model on Intel Celeron J4125 (x64) the function SynetConvolution32fNhwcDirect::OldReorderWeight() hangs on an infinite loop (looks like a.macroD parameter always equals to 0).

Hi. We run converted from OpenVino framework 'face-detection-retail-0005' network and get next inference results on aarch64:

For fp32: 243,4ms
For int8: 856ms.

It is strange that for int8 the calculation is slower. Is that how it should be?

Hello,

I am trying to convert the latest Face detection model and getting this error:
Unsupported version 11 of IE model
The model is here:
https://storage.openvinotoolkit.org/repositories/open_model_zoo/2022.1/models_bin/3/face-detection-0200/FP32/

Error C3861 '_mm_cvtsi64_si128': identifier not found

Reproduced in Release, Win32, VS2019 16.6.4

the im2col + gemm maybe a little slow.

Hello, is it possible to run a quantized YOLOv8 network without creating a custom layer?

Ошибка при конвертировании person-detection-retail-0002.bin/ person-detection-retail-0002.xml - https://download.01.org/opencv/2019/open_model_zoo/R1/models_bin/person-detection-retail-0002/FP32/

Cant't convert layer : type = Proposal, name = proposal, id = 222 !

VS 2019 Win32

An Improved One millisecond Mobile Backbone

https://arxiv.org/abs/2206.04040

https://github.com/facebookresearch/mobile-vision/blob/4d5207c/mobile_cv/arch/fbnet_v2/mobileone_block.py#L15