diff --git a/odm_preprocess.py b/odm_preprocess.py index 7d6ee2f..88e0263 100644 --- a/odm_preprocess.py +++ b/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, diff --git a/preprocess/__pycache__/command_runner.cpython-39.pyc b/preprocess/__pycache__/command_runner.cpython-39.pyc new file mode 100644 index 0000000..c8556e7 Binary files /dev/null and b/preprocess/__pycache__/command_runner.cpython-39.pyc differ diff --git a/preprocess/__pycache__/logger.cpython-39.pyc b/preprocess/__pycache__/logger.cpython-39.pyc new file mode 100644 index 0000000..c26b582 Binary files /dev/null and b/preprocess/__pycache__/logger.cpython-39.pyc differ diff --git a/show_GPS.py b/show_GPS.py deleted file mode 100644 index 955d712..0000000 --- a/show_GPS.py +++ /dev/null @@ -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() diff --git a/tools/odm_pip_time.py b/tools/odm_pip_time.py new file mode 100644 index 0000000..5ccab66 --- /dev/null +++ b/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) diff --git a/tools/show_GPS.py b/tools/show_GPS.py new file mode 100644 index 0000000..6b98da3 --- /dev/null +++ b/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()