去小黄点bug修复

.gitignore

@@ -7,6 +7,7 @@
 # Precompiled Headers
 *.gch
 *.pch
+*.pyc
 
 # Compiled Dynamic libraries
 *.so
@@ -37,3 +38,40 @@ CMakeSettings.json
 out/
 bin*/
 make*/
+libs/MVS/texture_output/texture_0.png
+libs/MVS/texture_output/texture_1.png
+libs/MVS/texture_output/texture_2.png
+libs/MVS/texture_output/texture_3.png
+libs/MVS/texture_output/texture_4.png
+libs/MVS/texture_output/texture_5.png
+libs/MVS/texture_output/texture_6.png
+libs/MVS/texture_output/texture_7.png
+libs/MVS/texture_output/texture_8.png
+libs/MVS/texture_output/texture_9.png
+libs/MVS/texture_output/texture_10.png
+libs/MVS/texture_output/texture_11.png
+libs/MVS/texture_output/texture_12.png
+libs/MVS/texture_output/texture_13.png
+libs/MVS/texture_output/texture_14.png
+libs/MVS/texture_output/texture_15.png
+libs/MVS/texture_output/texture_16.png
+libs/MVS/texture_output/texture_17.png
+libs/MVS/texture_output/texture_18.png
+libs/MVS/texture_output/texture_19.png
+libs/MVS/texture_output/texture_20.png
+libs/MVS/texture_output/texture_21.png
+libs/MVS/texture_output/texture_22.png
+libs/MVS/texture_output/texture_23.png
+libs/MVS/texture_output/texture_24.png
+libs/MVS/texture_output/texture_25.png
+libs/MVS/texture_output/texture_26.png
+libs/MVS/texture_output/texture_27.png
+libs/MVS/texture_output/texture_28.png
+libs/MVS/texture_output/texture_29.png
+libs/MVS/texture_output/texture_30.png
+libs/MVS/texture_output/texture_31.png
+libs/MVS/texture_output/texture_32.png
+libs/MVS/texture_output/texture_33.png
+libs/MVS/texture_output/texture_34.png
+libs/MVS/texture_output/texture_35.png
+texture_output/texture_0.png

fill_all_empty_faces_v1.2.py

@@ -323,7 +323,7 @@ def compute_regions_face_colors(
     return regions_face_color
 
 
-def update_uv_map_and_indices(
+def update_uv_map_and_indices2(
     uv_map: torch.Tensor,
     uvs: torch.Tensor,
     face_uv_indices: torch.Tensor,
@@ -394,6 +394,75 @@ def update_uv_map_and_indices(
 
     return new_uv_map, uvs_updated, face_uv_indices
 
+def update_uv_map_and_indices(
+    uv_map: torch.Tensor,
+    uvs: torch.Tensor,
+    face_uv_indices: torch.Tensor,
+    regions: List[Tuple[set, set]],
+    regions_face_color: Dict[int, torch.Tensor],
+    device: str
+) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+    """
+    根据计算得到的区域颜色，更新UV贴图及对应的UV坐标，并批量更新face_uv_indices。
+    """
+    total_regions = len(regions_face_color)
+    
+    # 1. 在CPU上创建新的UV贴图
+    new_height = int(uv_map.shape[0] + uv_map.shape[0] / 2)
+    new_width = uv_map.shape[1]
+    
+    # 将原始UV贴图移到CPU
+    uv_map_cpu = uv_map.cpu().numpy()
+    
+    # 创建新的UV贴图（在CPU上）
+    new_uv_map_cpu = np.zeros((new_height, new_width, 3), dtype=np.uint8)
+    new_uv_map_cpu[:uv_map.shape[0], :, :] = uv_map_cpu
+    
+    # 2. 在CPU上创建颜色块
+    grid_size = new_width // 3
+    for i, (region_index, color) in enumerate(regions_face_color.items()):
+        all_c = i // grid_size
+        all_r = i % grid_size
+        
+        # 计算3x3颜色块的位置
+        for dr in range(3):
+            for dc in range(3):
+                r = all_r * 3 + dr
+                c = all_c * 3 + dc + uv_map.shape[0]  # 偏移到下半部分
+                
+                if r < new_width and c < new_height:
+                    new_uv_map_cpu[c, r, :] = color.cpu().numpy()
+    
+    # 3. 更新UV坐标
+    uvs[:, 1] = uvs[:, 1] * (2 / 3) + 1 / 3
+    
+    # 计算新的UV坐标
+    new_uvs = []
+    for i, (region_index, _) in enumerate(sorted(regions_face_color.items(), key=lambda x: x[0])):
+        r = (i % grid_size) * 3 + 1
+        c = uv_map.shape[0] + (i // grid_size) * 3 + 1
+        
+        u_new = r / (new_width - 1)
+        v_new = (new_height - 1 - c) / (new_height - 1)
+        new_uvs.append([u_new, v_new])
+    
+    new_uvs_tensor = torch.tensor(new_uvs, device=device)
+    uvs_updated = torch.cat([uvs, new_uvs_tensor], dim=0)
+    uv_coordinates_start = uvs_updated.shape[0] - total_regions
+    
+    # 4. 批量更新face_uv_indices
+    for i, (region_index, _) in enumerate(sorted(regions_face_color.items(), key=lambda x: x[0])):
+        region_faces_indexes = torch.tensor(list(regions[region_index][0]), device=device)
+        face_uv_indices[region_faces_indexes] = torch.full(
+            (1, 3), uv_coordinates_start + i, 
+            device=device, dtype=face_uv_indices.dtype
+        )
+    
+    # 将结果转回GPU
+    new_uv_map = torch.from_numpy(new_uv_map_cpu).to(device)
+    
+    return new_uv_map, uvs_updated, face_uv_indices
+
 def group_regions_by_y_axis(
     regions: List[Tuple[set, set]],
     vertices: torch.Tensor,

libs/MVS/mask_face_occlusion.py

@@ -4,7 +4,8 @@ import os
 import numpy as np
 from scipy.spatial.transform import Rotation
 import sys
-sys.path.append("/home/algo/Documents/openMVS/openMVS/libs/MVS/utils")
+# sys.path.append("/home/algo/Documents/openMVS/openMVS/libs/MVS/utils")
+sys.path.append("/root/code/openMVS/libs/MVS/utils")
 from colmap_loader import read_cameras_text, read_images_text, read_int_text, write_int_text, read_indices_from_file
 # from get_pose_matrix import get_w2c
 import argparse
@@ -33,6 +34,7 @@ from typing import Dict, List, Set
 import struct
 import math
 # import os
+from pathlib import Path
 
 CameraModel = collections.namedtuple(
     "CameraModel", ["model_id", "model_name", "num_params"]
@@ -2175,6 +2177,8 @@ class ModelProcessor:
             base_path: 基础文件路径
         """
         
+        os.makedirs(base_path, exist_ok = True)
+
         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
@@ -2197,9 +2201,12 @@ class ModelProcessor:
         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:
+            file_name = "_visible_faces_map.txt"
+            file_path = Path(base_path) / file_name
+            with open(file_path, "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"
@@ -2209,7 +2216,9 @@ class ModelProcessor:
         
         # 保存 face_visible_relative
         try:
-            with open(base_path + "/_face_visible_relative.txt", "w", encoding='utf-8') as relative_file:
+            file_name = "_face_visible_relative.txt"
+            file_path = Path(base_path) / file_name
+            with open(file_path, "w", encoding='utf-8') as relative_file:
                 for face in face_visible_relative:
                     relative_file.write(str(face) + "\n")
         except IOError as e:
@@ -2217,7 +2226,9 @@ class ModelProcessor:
         
         # 保存 edge_faces_map
         try:
-            with open(base_path + "/_edge_faces_map.txt", "w", encoding='utf-8') as map_file2:
+            file_name = "_edge_faces_map.txt"
+            file_path = Path(base_path) / file_name
+            with open(file_path, "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)
@@ -2226,7 +2237,9 @@ class ModelProcessor:
         
         # 保存 delete_edge_faces_map
         try:
-            with open(base_path + "/_delete_edge_faces_map.txt", "w", encoding='utf-8') as map_file3:
+            file_name = "_delete_edge_faces_map.txt"
+            file_path = Path(base_path) / file_name
+            with open(file_path, "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)