'error: (-215:Assertion failed) (int)_numAxes == inputs[0].size() in function 'getMemoryShapes'
im trying to use opencv to do face recognition using facenet512. 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.
Solution 1:[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='facenet512.onnx')
to this :
nchw_inputs_list = [model.inputs[0].name] model_proto, _ = tf2onnx.convert.from_keras(model, output_path='facenet512.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()
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
Solution | Source |
---|---|
Solution 1 | Abdessamad Abid |