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C++和python剥离

master
hesuicong 2 months ago
parent
commit
2106969526
  1. 1
      libs/MVS/Scene.h
  2. 204
      libs/MVS/SceneTexture.cpp
  3. 79
      libs/MVS/mask_face_occlusion.py

1
libs/MVS/Scene.h

@ -171,6 +171,7 @@ public:
float fSharpnessWeight=0.5f, int ignoreMaskLabel=-1, int maxTextureSize=0, const IIndexArr& views=IIndexArr(), const SEACAVE::String& basename = "", bool bOriginFaceview = false, float fSharpnessWeight=0.5f, int ignoreMaskLabel=-1, int maxTextureSize=0, const IIndexArr& views=IIndexArr(), const SEACAVE::String& basename = "", bool bOriginFaceview = false,
const std::string& inputFileName = "", const std::string& meshFileName = ""); const std::string& inputFileName = "", const std::string& meshFileName = "");
std::string runPython(const std::string& command);
bool is_face_visible(const std::string& image_name, int face_index); bool is_face_visible(const std::string& image_name, int face_index);
bool is_face_visible_relative(int face_index); bool is_face_visible_relative(int face_index);
bool is_face_edge(const std::string& image_name, int face_index); bool is_face_edge(const std::string& image_name, int face_index);

204
libs/MVS/SceneTexture.cpp

@ -37,12 +37,13 @@
#include <boost/graph/connected_components.hpp> #include <boost/graph/connected_components.hpp>
#include <opencv2/ximgproc.hpp> #include <opencv2/ximgproc.hpp>
#include <pybind11/embed.h> // #include <pybind11/embed.h>
#include <pybind11/stl.h> // #include <pybind11/stl.h>
#include "ConfigEnv.h" #include "ConfigEnv.h"
#include "cuda/MeshTextureCUDA.h" #include "cuda/MeshTextureCUDA.h"
#include <sstream>
namespace py = pybind11; // namespace py = pybind11;
using namespace MVS; using namespace MVS;
@ -72,8 +73,6 @@ using namespace MVS;
#define TEXOPT_INFERENCE_TRWS 2 #define TEXOPT_INFERENCE_TRWS 2
#define TEXOPT_INFERENCE TEXOPT_INFERENCE_LBP #define TEXOPT_INFERENCE TEXOPT_INFERENCE_LBP
#define MASK_FACE_OCCLUSION #define MASK_FACE_OCCLUSION
// #define DISPLAY_DEMO
#define CACHE_MASK
#define USE_CUDA #define USE_CUDA
// inference algorithm // inference algorithm
@ -9590,40 +9589,6 @@ bool Scene::TextureMesh(unsigned nResolutionLevel, unsigned nMinResolution, unsi
printf("id=%s\n", id.c_str()); printf("id=%s\n", id.c_str());
#ifdef MASK_FACE_OCCLUSION #ifdef MASK_FACE_OCCLUSION
/*
// 创建遮挡数据
std::cout << "inputFileName: " << inputFileName << std::endl;
std::cout << "meshFileName: " << meshFileName << std::endl;
try {
py::scoped_interpreter guard{}; // 自动管理解释器生命周期
py::module_ sys = py::module_::import("sys");
// 设置命令行参数(模拟Python的argparse)
py::list argv;
argv.append("program_name");
argv.append("--sparse_dir");
argv.append(static_cast<std::string>(inputFileName));
argv.append("--mesh_path");
argv.append(static_cast<std::string>(meshFileName));
// argv.append("--mask_image");
// argv.append("63_2");
sys.attr("argv") = argv;
py::print(sys.attr("version")); // 打印Python版本
sys.attr("path").attr("append")("/root/miniconda3/lib/python3.10/site-packages");
sys.attr("path").attr("append")("/root/code/openMVS/libs/MVS");
// 调用自定义函数
py::module_ mymodule = py::module_::import("mask_face_occlusion");
// 获取ModelProcessor类
py::object ModelProcessor = mymodule.attr("ModelProcessor");
py::object processor = ModelProcessor();
py::dict result = processor.attr("process")().cast<py::dict>();
printf("result size=%d\n", result.size());
*/
std::string basePath = ""; std::string basePath = "";
size_t lastSlash = baseFileName.find_last_of('/'); size_t lastSlash = baseFileName.find_last_of('/');
size_t secondLastSlash = baseFileName.find_last_of('/', lastSlash - 1); size_t secondLastSlash = baseFileName.find_last_of('/', lastSlash - 1);
@ -9633,118 +9598,10 @@ bool Scene::TextureMesh(unsigned nResolutionLevel, unsigned nMinResolution, unsi
// printf("basePath=%s\n", basePath.c_str()); // printf("basePath=%s\n", basePath.c_str());
#ifdef CACHE_MASK
if (!LoadVisibleFacesData(visible_faces_map, face_visible_relative, edge_faces_map, delete_edge_faces_map, basePath)) if (!LoadVisibleFacesData(visible_faces_map, face_visible_relative, edge_faces_map, delete_edge_faces_map, basePath))
#endif
{
// 创建遮挡数据
try {
py::scoped_interpreter guard{}; // 自动管理解释器生命周期
py::module_ sys = py::module_::import("sys");
// 设置命令行参数(模拟Python的argparse)
py::list argv;
argv.append("program_name");
argv.append("--id");
// argv.append("274658"); // 274658 7613212046
argv.append(id);
argv.append("--base_path");
argv.append(basePath.c_str());
argv.append("--mesh_path");
argv.append(meshFileName.c_str());
argv.append("--sparse_dir");
argv.append(inputFileName.c_str());
sys.attr("argv") = argv;
py::print(sys.attr("version")); // 打印Python版本
printf("PYTHON_PATH=%s\n", PYTHON_PATH.c_str());
printf("MVS_PATH=%s\n", MVS_PATH.c_str());
// sys.attr("path").attr("append")("/home/algo/.conda/envs/py310_pyt210/lib/python3.10/site-packages");
// sys.attr("path").attr("append")("/home/algo/Documents/openMVS/openMVS/libs/MVS");
sys.attr("path").attr("append")(PYTHON_PATH.c_str());
sys.attr("path").attr("append")(MVS_PATH.c_str());
// 调用自定义函数
py::module_ mymodule = py::module_::import("mask_face_occlusion");
// 获取ModelProcessor类
py::object ModelProcessor = mymodule.attr("ModelProcessor");
py::object processor = ModelProcessor();
py::dict result = processor.attr("process")().cast<py::dict>();
py::dict dict1;
py::dict dict2;
if (result.contains("result1") && result.contains("result2")) {
dict1 = result["result1"].cast<py::dict>();
dict2 = result["result2"].cast<py::dict>();
}
py::dict dict3;
if (result.contains("result3")) {
dict3 = result["result3"].cast<py::dict>();
}
// printf("dict1 size=%d, dict2 size=%d, dict3 size=%d\n", dict1.size(), dict2.size(), dict3.size());
// 处理返回的可见面字典
for (auto item : dict1) {
std::string image_name = item.first.cast<std::string>();
// printf("dict1 mask image name=%s\n", image_name.c_str());
py::list visible_faces = item.second.cast<py::list>();
std::unordered_set<int> face_set;
for (auto face : visible_faces) {
face_set.insert(face.cast<int>());
}
visible_faces_map[image_name] = face_set;
}
for (const auto& entry : visible_faces_map)
{ {
face_visible_relative.insert(entry.second.begin(), entry.second.end()); printf("LoadVisibleFacesData error\n");
}
for (auto item : dict2) {
std::string image_name = item.first.cast<std::string>();
// printf("dict2 mask image name=%s\n", image_name.c_str());
py::list edge_faces = item.second.cast<py::list>();
std::unordered_set<int> face_set;
for (auto face : edge_faces) {
face_set.insert(face.cast<int>());
} }
edge_faces_map[image_name] = face_set;
}
for (auto item : dict3) {
std::string image_name = item.first.cast<std::string>();
// printf("dict3 mask image name=%s\n", image_name.c_str());
py::list delete_edge_faces = item.second.cast<py::list>();
std::unordered_set<int> face_set;
for (auto face : delete_edge_faces) {
face_set.insert(face.cast<int>());
}
delete_edge_faces_map[image_name] = face_set;
}
#ifdef CACHE_MASK
SaveVisibleFacesData(visible_faces_map, face_visible_relative, edge_faces_map, delete_edge_faces_map, basePath);
#endif
}
catch (const py::error_already_set &e) {
std::cerr << "Python error: " << e.what() << std::endl;
// 获取详细的Python错误信息
PyErr_Print();
return 1;
}
catch (const std::exception &e) {
std::cerr << "C++ error: " << e.what() << std::endl;
return 1;
}
}
#endif #endif
// assign the best view to each face // assign the best view to each face
@ -9812,50 +9669,21 @@ bool Scene::TextureMesh(unsigned nResolutionLevel, unsigned nMinResolution, unsi
texture.GenerateTexture(bGlobalSeamLeveling, bLocalSeamLeveling, nTextureSizeMultiple, nRectPackingHeuristic, colEmpty, fSharpnessWeight, maxTextureSize, baseFileName, bOriginFaceview); texture.GenerateTexture(bGlobalSeamLeveling, bLocalSeamLeveling, nTextureSizeMultiple, nRectPackingHeuristic, colEmpty, fSharpnessWeight, maxTextureSize, baseFileName, bOriginFaceview);
DEBUG_EXTRA("Generating texture atlas and image completed: %u patches, %u image size, %u textures (%s)", texture.texturePatches.size(), mesh.texturesDiffuse[0].width(), mesh.texturesDiffuse.size(), TD_TIMER_GET_FMT().c_str()); DEBUG_EXTRA("Generating texture atlas and image completed: %u patches, %u image size, %u textures (%s)", texture.texturePatches.size(), mesh.texturesDiffuse[0].width(), mesh.texturesDiffuse.size(), TD_TIMER_GET_FMT().c_str());
} }
#ifdef DISPLAY_DEMO
try {
py::scoped_interpreter guard{}; // 自动管理解释器生命周期
py::module_ sys = py::module_::import("sys");
// 设置命令行参数(模拟Python的argparse)
py::list argv;
argv.append("program_name");
argv.append("--id");
argv.append(id);
argv.append("--mask");
#ifdef MASK_FACE_OCCLUSION
argv.append(1);
#else
argv.append(0);
#endif
sys.attr("argv") = argv;
py::print(sys.attr("version")); // 打印Python版本 return true;
sys.attr("path").attr("append")("/home/algo/.conda/envs/py310_pyt210/lib/python3.10/site-packages"); } // TextureMesh
sys.attr("path").attr("append")("/home/algo/Documents/openMVS/openMVS/libs/MVS");
// 调用自定义函数
py::module_ mymodule = py::module_::import("display_demo");
// 获取ModelProcessor类 std::string Scene::runPython(const std::string& command) {
py::object DisplayProcessor = mymodule.attr("DisplayProcessor"); std::array<char, 128> buffer{};
std::string result;
std::unique_ptr<FILE, decltype(&pclose)> pipe(popen(command.c_str(), "r"), pclose);
if (!pipe) throw std::runtime_error("popen() failed!");
py::object processor = DisplayProcessor(); while (fgets(buffer.data(), buffer.size(), pipe.get()) != nullptr) {
processor.attr("load_and_show")(); result += buffer.data();
}
catch (const py::error_already_set &e) {
std::cerr << "Python error: " << e.what() << std::endl;
// 获取详细的Python错误信息
PyErr_Print();
return 1;
}
catch (const std::exception &e) {
std::cerr << "C++ error: " << e.what() << std::endl;
return 1;
} }
#endif return result;
}
return true;
} // TextureMesh
bool Scene::is_face_visible(const std::string& image_name, int face_index) { bool Scene::is_face_visible(const std::string& image_name, int face_index) {

79
libs/MVS/mask_face_occlusion.py

@ -14,6 +14,9 @@ import torch
import torch.nn.functional as F import torch.nn.functional as F
from torch.utils.dlpack import to_dlpack, from_dlpack from torch.utils.dlpack import to_dlpack, from_dlpack
import os
from typing import Dict, List, Set
class ModelProcessor: class ModelProcessor:
def __init__(self): def __init__(self):
@ -455,6 +458,8 @@ class ModelProcessor:
print(f"所有图像处理完成,总耗时: {total_time:.2f}") print(f"所有图像处理完成,总耗时: {total_time:.2f}")
print(f"平均每张图像耗时: {total_time/len(images):.2f}") print(f"平均每张图像耗时: {total_time/len(images):.2f}")
self.save_occlusion_data(visible_faces_dict, edge_faces_dict, delete_edge_faces_dict, self.asset_dir)
return { return {
"result1": visible_faces_dict, "result1": visible_faces_dict,
"result2": edge_faces_dict, "result2": edge_faces_dict,
@ -1183,8 +1188,82 @@ class ModelProcessor:
print(f"所有图像处理完成,总耗时: {total_time:.2f}") print(f"所有图像处理完成,总耗时: {total_time:.2f}")
print(f"平均每张图像耗时: {total_time/len(images):.2f}") print(f"平均每张图像耗时: {total_time/len(images):.2f}")
self.save_occlusion_data(visible_faces_dict, edge_faces_dict, delete_edge_faces_dict, self.asset_dir)
return {"result1": visible_faces_dict, "result2": edge_faces_dict, "result3": delete_edge_faces_dict} return {"result1": visible_faces_dict, "result2": edge_faces_dict, "result3": delete_edge_faces_dict}
def save_occlusion_data(self, result1: Dict[str, List[int]],
result2: Dict[str, List[int]],
result3: Dict[str, List[int]],
base_path: str) -> None:
"""
保存遮挡数据到文件
Args:
result1: 可见面字典包含图像名称和对应的可见面列表
result2: 边面字典包含图像名称和对应的边面列表
result3: 删除边面字典包含图像名称和对应的删除边面列表
base_path: 基础文件路径
"""
print(f"save_occlusion_data {base_path}, {len(result1)}, {len(result2)}, {len(result3)}")
# 处理返回的可见面字典 - 转换为图像名到面编号集合的映射
visible_faces_map: Dict[str, Set[int]] = {}
for image_name, face_list in result1.items():
visible_faces_map[image_name] = set(face_list)
# 计算所有可见面的并集
face_visible_relative: Set[int] = set()
for face_set in visible_faces_map.values():
face_visible_relative.update(face_set)
# 处理边面字典
edge_faces_map: Dict[str, Set[int]] = {}
for image_name, face_list in result2.items():
edge_faces_map[image_name] = set(face_list)
# 处理删除边面字典
delete_edge_faces_map: Dict[str, Set[int]] = {}
for image_name, face_list in result3.items():
delete_edge_faces_map[image_name] = set(face_list)
# 保存 visible_faces_map
try:
with open(base_path + "_visible_faces_map.txt", "w", encoding='utf-8') as map_file:
for image_name, face_set in visible_faces_map.items():
# 写入图像名称和所有面ID,用空格分隔
line = image_name + " " + " ".join(str(face) for face in face_set) + "\n"
map_file.write(line)
except IOError as e:
print(f"Error writing visible_faces_map file: {e}")
# 保存 face_visible_relative
try:
with open(base_path + "_face_visible_relative.txt", "w", encoding='utf-8') as relative_file:
for face in face_visible_relative:
relative_file.write(str(face) + "\n")
except IOError as e:
print(f"Error writing face_visible_relative file: {e}")
# 保存 edge_faces_map
try:
with open(base_path + "_edge_faces_map.txt", "w", encoding='utf-8') as map_file2:
for image_name, face_set in edge_faces_map.items():
line = image_name + " " + " ".join(str(face) for face in face_set) + "\n"
map_file2.write(line)
except IOError as e:
print(f"Error writing edge_faces_map file: {e}")
# 保存 delete_edge_faces_map
try:
with open(base_path + "_delete_edge_faces_map.txt", "w", encoding='utf-8') as map_file3:
for image_name, face_set in delete_edge_faces_map.items():
line = image_name + " " + " ".join(str(face) for face in face_set) + "\n"
map_file3.write(line)
except IOError as e:
print(f"Error writing delete_edge_faces_map file: {e}")
def process(self): def process(self):
print("process") print("process")

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