Question

我试图将cv::Mat转换为Tensor，所以我构建了一个函数，它显示了问题：“。exe触发了断点”，并且在调试时我发现析构函数~my_buffer()和基类~TensorBuffer()可能不正确。它显示了一个名为ref_.load() = 2的函数。以下是my_buffer类。命令行输出：

Check failed: ref_.load() == 0 (2 vs. 0)

class my_buffer : public TensorBuffer {

public:
    float * data_;
    size_t  len_;

    ~my_buffer() override {
        //nothing to do

    }

    void* data() const override { return data_; }
    size_t size() const override { return len_; }
    bool OwnsMemory() const override { return false; }

    TensorBuffer* root_buffer() override { return this; }

    void FillAllocationDescription(AllocationDescription* proto) const override {
        tensorflow::int64 rb = size();
        proto->set_requested_bytes(rb);
        proto->set_allocator_name(tensorflow::cpu_allocator()->Name());
    }

以防万一，其余代码：

Tensor cv2tensor(const cv::Mat & img )
{
    int height = 1069;
    int width = 500;
    int chanel = 3;
    int bacth = 1;

    int input_size = height*width*chanel;

    std::vector<float> input_buffer(input_size);

    /*float * input_data = input_buffer.data();*/

    const int64_t dim[4] = { bacth, width, height, chanel };

    my_buffer tensor_buf;

    //////////////////////////////////////////////////////
    /*img.reshape(1);*/
    int count = 0;
    /*for (int i=0;i<)*/
    for (int i = 0; i < 3; i++)
    {
        for (int row = 0; row < img.rows; row++)
        {
            for (int col = 0; col < img.cols; col++)
            {
                input_buffer[count] = img.at<cv::Vec3b>(row, col)[0];
                count += 1;
            }
        }
    }
    ////////////////////////////////////////////////////////
    tensor_buf.data_ = (float *)input_buffer.data();
    tensor_buf.len_  = input_size;

    std::vector<tensorflow::int64> tensor_dim;

    for (int i = 0; i < 4; i++)
        tensor_dim.push_back(dim[i]);

    Tensor input_tensor = tensorflow::TensorCApi::create_tensor(DT_FLOAT, TensorShape(tensor_dim), &tensor_buf);
    //cv::resize()
    /*Tensor input_tensor;*/
    return input_tensor;
}

Answer 1

将OpenCV矩阵转换为张量实际上更直接（从here）：

// just for this answer:
using namespace tensorflow;

cv::Mat image;
cv::Mat image_float;
image.convertTo(image_float, CV_32FC3);
float *image_float_data = (float*)image_float.data;

TensorShape my_shape = TensorShape{1, image.rows, image.cols, image.channels()};
Tensor my_tensor = Tensor(DT_FLOAT, my_shape);
std::copy_n((char*) image_float_data, 
            my_shape.num_elements() * sizeof(float),
            const_cast<char*>(my_tensor.tensor_data().data()));

您为什么要迭代数据？为什么要创建自己的缓冲区类？

将cv :: Mat转换为TensorFlow Tensor时，“。exe触发了断点”

1 个答案: