刪除模型中的頂點重複

以.obj格式導入模型時，很多多邊形共享頂點並因此耗盡內存，我想要執行的操作是僅保存唯一頂點來刪除重複項。與tinyobjcloader刪除模型中的頂點重複

Mesh Renderer::load_mesh_from_file(std::string filepath) { 
tinyobj::attrib_t attrib; 
std::vector<tinyobj::shape_t> shapes; 
std::vector<tinyobj::material_t> materials; 
std::string err; 
auto success = tinyobj::LoadObj(&attrib, &shapes, &materials, &err, filepath.c_str()); 
if (!success) { SDL_Log("Failed loading mesh %s: %s", filepath.c_str(), err.c_str()); return Mesh(); } 

std::unordered_map<Vertex<float>, size_t> unique_vertices{}; 
Mesh mesh{}; 
for (auto shape : shapes) { // Shapes 
    size_t index_offset = 0; 
    for (auto face : shape.mesh.num_face_vertices) { // Faces (polygon) 
     for (auto v = 0; v < face; v++) { 
      tinyobj::index_t idx = shape.mesh.indices[index_offset + v]; 
      Vertex<float> vertex{}; 
      float vx = attrib.vertices[3 * idx.vertex_index + 0]; 
      float vy = attrib.vertices[3 * idx.vertex_index + 1]; 
      float vz = attrib.vertices[3 * idx.vertex_index + 2]; 
      vertex.position = {vx, vy, vz}; 

      float tx = attrib.vertices[3 * idx.texcoord_index + 0]; 
      float ty = attrib.vertices[3 * idx.texcoord_index + 1]; 
      vertex.texCoord = {tx, ty}; 

      float nx = attrib.normals[3 * idx.normal_index + 0]; 
      float ny = attrib.normals[3 * idx.normal_index + 1]; 
      float nz = attrib.normals[3 * idx.normal_index + 2]; 
      vertex.normal = {nx, ny, nz}; 

      // These two lines work just fine (includes all vertices) 
      // mesh.vertices.push_back(vertex); 
      // mesh.indices.push_back(mesh.indices.size()); 

      // Check for unique vertices, models will contain duplicates 
      if (unique_vertices.count(vertex) == 0) { 
       unique_vertices[vertex] = mesh.indices.size(); 
       mesh.vertices.push_back(vertex); 
       mesh.indices.push_back(mesh.indices.size()); 
      } else { 
       mesh.indices.push_back(unique_vertices.at(vertex)); 
      } 
     } 
     index_offset += face; 
    } 
} 

SDL_Log("Number of vertices: %lu for model %s", mesh.vertices.size(), filepath.c_str()); 
return mesh; 
}

第一圖像頂點

/// Template specialization for hashing of a Vec3 
namespace std { 
template<typename T> 
struct hash<Vec3<T>> { 
    void hash_combine(size_t &seed, const size_t &hash) const { 
     seed ^= hash + 0x9e3779b9 + (seed << 6) + (seed >> 2); 
    } 

    size_t operator() (const Vec3<T> &vec) const { 
     auto hasher = hash<float>{}; 
     auto hashed_x = hasher(vertex.position.x); 
     auto hashed_y = hasher(vertex.position.y); 
     auto hashed_z = hasher(vertex.position.z); 
     auto hashed_color_r = hasher(vertex.color.r); 
     auto hashed_color_g = hasher(vertex.color.g); 
     auto hashed_color_b = hasher(vertex.color.b); 
     auto hashed_color_a = hasher(vertex.color.a); 
     auto hashed_texcoord_x = hasher(vertex.texCoord.x); 
     auto hashed_texcoord_y = hasher(vertex.texCoord.y); 
     auto hashed_normal_x = hasher(vertex.normal.x); 
     auto hashed_normal_y = hasher(vertex.normal.y); 
     auto hashed_normal_z = hasher(vertex.normal.z); 

     size_t seed = 0; 
     hash_combine(seed, hashed_x); 
     hash_combine(seed, hashed_y); 
     hash_combine(seed, hashed_z); 
     hash_combine(seed, hashed_texcoord_x); 
     hash_combine(seed, hashed_texcoord_y); 
     hash_combine(seed, hashed_normal_x); 
     hash_combine(seed, hashed_normal_y); 
     hash_combine(seed, hashed_normal_z); 
     return seed; 
    } 
}; 
}

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