示例#1
0
 Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
 read_cov_L(const Eigen::Array<T, Eigen::Dynamic, 1>& CPCs,
            const Eigen::Array<T, Eigen::Dynamic, 1>& sds,
            T& log_prob) {
   size_t K = sds.rows();
   // adjust due to transformation from correlations to covariances
   log_prob += (sds.log().sum() + LOG_2) * K;
   return sds.matrix().asDiagonal() * read_corr_L(CPCs, K, log_prob);
 }
示例#2
0
    Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
    read_corr_L(const Eigen::Array<T, Eigen::Dynamic, 1>& CPCs,
                size_t K,
                T& log_prob) {
      Eigen::Matrix<T, Eigen::Dynamic, 1> values(CPCs.rows() - 1);
      size_t pos = 0;
      // no need to abs() because this Jacobian determinant
      // is strictly positive (and triangular)
      // see inverse of Jacobian in equation 11 of LKJ paper
      for (size_t k = 1; k <= (K - 2); k++)
        for (size_t i = k + 1; i <= K; i++) {
          values(pos) = (K - k - 1) * log1m(square(CPCs(pos)));
          pos++;
        }

      log_prob += 0.5 * sum(values);
      return read_corr_L(CPCs, K);
    }
示例#3
0
文件: image.cpp 项目: ervanalb/ao
bool SavePng(std::string filename, const DepthImage& img)
{
    // Open up a file for writing
    FILE* output = fopen(filename.c_str(), "wb");
    if (output == NULL)
    {
        printf("Failed to open PNG file for writing (errno = %i)\n", errno);
        return false;
    }

    // Create a png pointer with the callbacks above
    png_structp png_ptr = png_create_write_struct(
        PNG_LIBPNG_VER_STRING, NULL, on_png_error, on_png_warn);
    if (png_ptr == NULL)
    {
        fprintf(stderr, "Failed to allocate png write_struct\n");
        fclose(output);
        return false;
    }

    // Create an info pointer
    png_infop info_ptr = png_create_info_struct(png_ptr);
    if (info_ptr == NULL)
    {
        fprintf(stderr, "Failed to create png info_struct");
        png_destroy_write_struct(&png_ptr, &info_ptr);
        fclose(output);
        return false;
    }

    // Set physical vars
    png_set_IHDR(png_ptr, info_ptr, img.cols(), img.rows(), 16,
                 PNG_COLOR_TYPE_GRAY, PNG_INTERLACE_NONE,
                 PNG_COMPRESSION_TYPE_BASE, PNG_FILTER_TYPE_BASE);

    png_init_io(png_ptr, output);

    const float zmax = img.maxCoeff();
    const float zmin = (img == -std::numeric_limits<float>::infinity())
            .select(DepthImage::Constant(img.rows(), img.cols(), zmax),
                    img)
            .minCoeff();

    auto scaled = (zmax == zmin)
        ? DepthImage((img - zmin) + 65535)
        : DepthImage((img - zmin) * 65534 / (zmax - zmin) + 1);
    Eigen::Array<uint16_t, Eigen::Dynamic, Eigen::Dynamic>
        pixels = scaled.cast<uint16_t>().transpose();

    std::vector<uint16_t*> rows;
    for (int i=pixels.cols() - 1; i >= 0; --i)
    {
        rows.push_back(pixels.data() + i * pixels.rows());
    }

    png_set_rows(png_ptr, info_ptr, reinterpret_cast<png_bytepp>(&rows[0]));
    png_write_png(png_ptr, info_ptr, PNG_TRANSFORM_SWAP_ENDIAN, NULL);
    fclose(output);

    png_destroy_write_struct(&png_ptr, &info_ptr);
    return true;
}