优化可视化内容

odm_preprocess.py

@@ -185,7 +185,7 @@ class ImagePreprocessor:
 if __name__ == '__main__':
     # 创建配置
     config = PreprocessConfig(
-        image_dir=r'E:\datasets\UAV\1815',
+        image_dir=r'E:\datasets\UAV\1815\images',
         output_dir=r'E:\datasets\UAV\1815\output',
         filter_grid_size=0.001,
         filter_dense_distance_threshold=10,

show_GPS.py

@@ -1,44 +0,0 @@
-from gps_extractor import GPSExtractor
-from gps_filter import GPSFilter
-from grid_divider import GridDivider
-import os
-import pandas as pd
-import shutil
-import matplotlib.pyplot as plt
-
-DATASET = r'C:\datasets\1815\output\grid_5\grid_5\images'
-IS_ORIGIN = True
-
-if __name__ == '__main__':
-    if IS_ORIGIN:
-        extractor = GPSExtractor(DATASET)
-        gps_points = extractor.extract_all_gps()
-    else:
-        # 提取九宫格中的GPS数据
-        gps_points = []
-        for subdir in os.listdir(DATASET):
-            subdir_path = os.path.join(DATASET, subdir)
-            if os.path.isdir(subdir_path):
-                extractor = GPSExtractor(subdir_path)
-                sub_gps_points = extractor.extract_all_gps()
-                gps_points = gps_points + sub_gps_points
-                print(len(sub_gps_points))
-
-    longitudes = [p['lon'] for p in gps_points]
-    latitudes = [p['lat'] for p in gps_points]
-    # 绘制散点图
-    plt.figure(figsize=(10, 8))
-    plt.scatter(longitudes, latitudes, color='blue', marker='o')
-
-    # 添加标记，显示每个点的图像文件名
-    for i, image in enumerate(gps_points):
-        plt.text(longitudes[i], latitudes[i], image['file'], fontsize=9, ha='right')
-
-    # 添加图表标签
-    plt.title("GPS Coordinates of Images", fontsize=14)
-    plt.xlabel("Longitude", fontsize=12)
-    plt.ylabel("Latitude", fontsize=12)
-
-    # 显示图形
-    plt.grid(True)
-    plt.show()

tools/odm_pip_time.py

@@ -0,0 +1,55 @@
+from datetime import datetime
+import json
+
+
+def parse_args():
+    import argparse
+    parser = argparse.ArgumentParser(description="ODM log time")
+
+    parser.add_argument(
+        "--path", default=r"E:\datasets\UAV\1815\project\log.json")
+    args = parser.parse_args()
+    return args
+
+
+def main(args):
+    # 读取 JSON 文件
+    with open(args.path, 'r') as file:
+        data = json.load(file)
+
+    # 提取 "stages" 中每个步骤的开始时间和持续时间
+    stage_timings = []
+    for i, stage in enumerate(data.get("stages", [])):
+        stage_name = stage.get("name", "Unnamed Stage")
+        start_time = stage.get("startTime")
+
+        # 获取当前阶段的开始时间
+        if start_time:
+            start_dt = datetime.fromisoformat(start_time)
+
+            # 获取阶段的结束时间：可以是下一个阶段的开始时间，或当前阶段的 `endTime`（如果存在）
+            if i + 1 < len(data["stages"]):
+                end_time = data["stages"][i + 1].get("startTime")
+            else:
+                end_time = stage.get("endTime") or data.get("endTime")
+
+            if end_time:
+                end_dt = datetime.fromisoformat(end_time)
+                duration = (end_dt - start_dt).total_seconds()
+                stage_timings.append((stage_name, duration))
+
+    # 输出每个阶段的持续时间，调整为对齐格式
+    total_time = 0
+    print(f"{'Stage Name':<25} {'Duration (seconds)':>15}")
+    print("=" * 45)
+    for stage_name, duration in stage_timings:
+        print(f"{stage_name:<25} {duration:>15.2f}")
+        total_time += duration
+
+    print('Total Time:', total_time)
+
+
+if __name__ == '__main__':
+    args = parse_args()
+
+    main(args)

tools/show_GPS.py

@@ -0,0 +1,51 @@
+import os
+import sys
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+import matplotlib.pyplot as plt
+from preprocess.gps_extractor import GPSExtractor
+
+DATASET = r'E:\湖南省第二测绘院\11-06-项目移交文件（王辉给）\无人机二三维节点扩容生产影像\影像数据\1009'
+
+if __name__ == '__main__':
+    extractor = GPSExtractor(DATASET)
+    gps_points = extractor.extract_all_gps()
+    
+    # 创建两个子图
+    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(20, 8))
+    
+    # 左图：原始散点图
+    ax1.scatter(gps_points['lon'], gps_points['lat'], 
+               color='blue', marker='o', label='GPS Points')
+    ax1.set_title("GPS Coordinates of Images", fontsize=14)
+    ax1.set_xlabel("Longitude", fontsize=12)
+    ax1.set_ylabel("Latitude", fontsize=12)
+    ax1.grid(True)
+    ax1.legend()
+
+    # # 右图：按时间排序的轨迹图
+    # gps_points_sorted = gps_points.sort_values('date')
+    
+    # # 绘制飞行轨迹线
+    # ax2.plot(gps_points_sorted['lon'][300:600], gps_points_sorted['lat'][300:600], 
+    #         color='blue', linestyle='-', linewidth=1, alpha=0.6)
+    
+    # # 绘制GPS点
+    # ax2.scatter(gps_points_sorted['lon'][300:600], gps_points_sorted['lat'][300:600], 
+    #           color='red', marker='o', s=30, label='GPS Points')
+
+    # 标记起点和终点
+    # ax2.scatter(gps_points_sorted['lon'].iloc[0], gps_points_sorted['lat'].iloc[0], 
+    #           color='green', marker='^', s=100, label='Start')
+    # ax2.scatter(gps_points_sorted['lon'].iloc[-1], gps_points_sorted['lat'].iloc[-1], 
+    #           color='purple', marker='s', s=100, label='End')
+
+    ax2.set_title("UAV Flight Trajectory", fontsize=14)
+    ax2.set_xlabel("Longitude", fontsize=12)
+    ax2.set_ylabel("Latitude", fontsize=12)
+    ax2.grid(True)
+    ax2.legend()
+
+    # 调整子图之间的间距
+    plt.tight_layout()
+    plt.show()