规范代码格式
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@ -64,8 +64,8 @@ class ImagePreprocessor:
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self.logger.info("开始过滤GPS点")
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filter = GPSFilter(self.config.output_dir)
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self.logger.info(f"开始过滤孤立点 (距离阈值: {self.config.filter_distance_threshold}, 最小邻居数: {
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self.config.filter_min_neighbors})")
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self.logger.info(
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f"开始过滤孤立点(距离阈值: {self.config.filter_distance_threshold}, 最小邻居数: {self.config.filter_min_neighbors})")
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self.gps_points = filter.filter_isolated_points(
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self.gps_points,
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self.config.filter_distance_threshold,
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@ -73,8 +73,8 @@ class ImagePreprocessor:
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)
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self.logger.info(f"孤立点过滤后剩余 {len(self.gps_points)} 个GPS点")
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self.logger.info(f"开始过滤密集点 (网格大小: {self.config.filter_grid_size}, 距离阈值: {
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self.config.filter_dense_distance_threshold})")
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self.logger.info(
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f"开始过滤密集点(网格大小: {self.config.filter_grid_size}, 距离阈值: {self.config.filter_dense_distance_threshold})")
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self.gps_points = filter.filter_dense_points(
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self.gps_points,
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grid_size=self.config.filter_grid_size,
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@ -90,7 +90,8 @@ class ImagePreprocessor:
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self.logger.info(f"开始划分网格 (重叠率: {self.config.grid_overlap})")
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grid_divider = GridDivider(overlap=self.config.grid_overlap)
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grids = grid_divider.divide_grids(self.gps_points, grid_size=self.config.grid_size)
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grids = grid_divider.divide_grids(
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self.gps_points, grid_size=self.config.grid_size)
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grid_points = grid_divider.assign_to_grids(self.gps_points, grids)
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self.logger.info(f"成功划分为 {len(grid_points)} 个网格")
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return grid_points
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@ -104,9 +105,11 @@ class ImagePreprocessor:
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for grid_idx, points in grid_points.items():
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if self.config.enable_grid_division:
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output_dir = os.path.join(self.config.output_dir, f'grid_{grid_idx + 1}', 'project', 'images')
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output_dir = os.path.join(
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self.config.output_dir, f'grid_{grid_idx + 1}', 'project', 'images')
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else:
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output_dir = os.path.join(self.config.output_dir, 'project', 'images')
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output_dir = os.path.join(
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self.config.output_dir, 'project', 'images')
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os.makedirs(output_dir, exist_ok=True)
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@ -140,7 +143,8 @@ class ImagePreprocessor:
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alpha=0.6)
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# 绘制被过滤的点
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filtered_points_df = original_points_df[original_points_df['file'].isin(filtered_files)]
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filtered_points_df = original_points_df[original_points_df['file'].isin(
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filtered_files)]
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plt.scatter(filtered_points_df['lon'],
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filtered_points_df['lat'],
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color="red",
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@ -181,8 +185,8 @@ class ImagePreprocessor:
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if __name__ == '__main__':
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# 创建配置
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config = PreprocessConfig(
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image_dir=r'C:\datasets\1815\images',
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output_dir=r'C:\datasets\1815\output',
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image_dir=r'E:\datasets\UAV\1815',
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output_dir=r'E:\datasets\UAV\1815\output',
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filter_grid_size=0.001,
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filter_dense_distance_threshold=10,
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filter_distance_threshold=0.001,
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preprocess/__pycache__/time_filter.cpython-39.pyc
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preprocess/__pycache__/time_filter.cpython-39.pyc
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@ -4,6 +4,7 @@ import subprocess
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from typing import Dict
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import pandas as pd
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class CommandRunner:
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"""执行网格处理命令的类"""
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