错误：(-215:断言失败) (int)_numAxes == inputs[0].size() in function 'getMemoryShapes'

Question

im trying to use opencv to do face recognition using fac.net512. i converted the model to onnx format using tf2onnx. i know that the input of the model should be an image like:(160,160,3). so i tried doing this using this script:

void convertDimention(cv::Mat input, cv::Mat &output)
{
    vector<cv::Mat> channels(3);
    cv::split(input, channels);

    int size[3] = { 160, 160, 3 };
    cv::Mat M(3, size, CV_32F, cv::Scalar(0));

    for (int i = 0; i < size[0]; i++) {
      for (int j = 0; j < size[1]; j++) {
        for (int k = 0; k < size[2]; k++) {
          M.at<float>(i,j,k) = channels[k].at<float>(i,j)/255;
        }
      }
    }
    M.copyTo(output);

}

after converting the image from (160,160) to (160,160,3) i still get this error:

error: (-215:Assertion failed) (int)_numAxes == inputs[0].size() in function 'getMemoryShapes'

full code:

#include <iostream>

#include <opencv2/dnn.hpp>
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"

#include <vector>

using namespace std;


void convertDimention(cv::Mat input, cv::Mat &output)
{
    vector<cv::Mat> channels(3);
    cv::split(input, channels);

    int size[3] = { 160, 160, 3 };
    cv::Mat M(3, size, CV_32F, cv::Scalar(0));

    for (int i = 0; i < size[0]; i++) {
      for (int j = 0; j < size[1]; j++) {
        for (int k = 0; k < size[2]; k++) {
          M.at<float>(i,j,k) = channels[k].at<float>(i,j)/255;
        }
      }
    }
    M.copyTo(output);

}



int main()
{ 
    cv::Mat input,input2, output;

    input = cv::imread("image.png");
    cv::resize(input,input, cv::Size(160,160));
    convertDimention(input,input2);

    cv::dnn::Net net = cv::dnn::readNetFromONNX("facenet512.onnx");
    net.setPreferableBackend(cv::dnn::DNN_BACKEND_CUDA);
    net.setPreferableTarget(cv::dnn::DNN_TARGET_CUDA);
    cout << input.size << endl;
    cout << input2.size << endl;


    net.setInput(input2);
    output = net.forward();



}

I know that i'm doing this in the wrong way(since i'm new to this). Is there any other way to change the dimensions so that it fits the model input?

thanks in advance.

Answer 1

using.netron i was able to visualize the input of the model:

the origin of the problem was from the conversion of the model i just had to change this:

model_proto, _ = tf2onnx.convert.from_keras(model, output_path='fac.net512.onnx')

to this:

nchw_inputs_list = [model.inputs[0].name] model_proto, _ = tf2onnx.convert.from_keras(model, output_path='fac.net512.onnx',inputs_as_nchw=nchw_inputs_list)

i checked again in.netron and the result were:

i can now use the model from opencv using cv::dnn::BlobFromImage()