add filter time_group_overlap
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@ -90,12 +90,8 @@ class TimeGroupOverlapFilter:
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return intersection_area / smaller_area
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return 0
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def filter_overlapping_groups(self, time_threshold=timedelta(minutes=5)):
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def filter_overlapping_groups(self, gps_points, time_threshold=timedelta(minutes=5)):
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"""过滤重叠的时间组"""
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# 提取GPS数据
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extractor = GPSExtractor(self.image_dir)
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gps_points = extractor.extract_all_gps()
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# 按时间分组
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time_groups = self._group_by_time(gps_points, time_threshold)
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@ -97,9 +97,8 @@ class ImagePreprocessor:
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extractor = GPSExtractor(self.config.image_dir)
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self.gps_points = extractor.extract_all_gps()
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self.logger.info(f"成功提取 {len(self.gps_points)} 个GPS点")
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return self.gps_points
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def cluster(self) -> pd.DataFrame:
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def cluster(self):
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"""使用DBSCAN对GPS点进行聚类，只保留最大的类"""
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self.logger.info("开始聚类")
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previous_points = self.gps_points.copy()
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@ -124,44 +123,10 @@ class ImagePreprocessor:
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self.visualizer.visualize_filter_step(
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self.gps_points, previous_points, "1-Clustering")
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return self.gps_points
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def filter_time_group_overlap(self) -> pd.DataFrame:
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"""过滤重叠的时间组"""
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self.logger.info("开始过滤重叠时间组")
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self.logger.info("开始过滤重叠时间组")
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previous_points = self.gps_points.copy()
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filter = TimeGroupOverlapFilter(
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self.config.image_dir,
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self.config.output_dir,
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overlap_threshold=self.config.time_group_overlap_threshold
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)
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deleted_files = filter.filter_overlapping_groups(
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time_threshold=self.config.time_group_interval
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)
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# 更新GPS点数据，移除被删除的图像
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self.gps_points = self.gps_points[~self.gps_points['file'].isin(
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deleted_files)]
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self.logger.info(f"重叠时间组过滤后剩余 {len(self.gps_points)} 个GPS点")
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# 可视化过滤结果
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self.visualizer.visualize_filter_step(
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self.gps_points, previous_points, "2-Time Group Overlap")
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return self.gps_points
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# TODO 过滤算法还需要更新
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def filter_points(self) -> pd.DataFrame:
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"""过滤GPS点"""
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self.logger.info("开始过滤GPS点")
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def filter_isolated_points(self):
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"""过滤孤立点"""
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self.logger.info("开始过滤孤立点")
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filter = GPSFilter(self.config.output_dir)
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# 过滤孤立点
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previous_points = self.gps_points.copy()
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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}, "
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@ -176,7 +141,36 @@ class ImagePreprocessor:
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# 可视化孤立点过滤结果
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self.visualizer.visualize_filter_step(
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self.gps_points, previous_points, "3-Isolated Points")
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self.gps_points, previous_points, "2-Isolated Points")
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def filter_time_group_overlap(self):
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"""过滤重叠的时间组"""
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self.logger.info("开始过滤重叠时间组")
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previous_points = self.gps_points.copy()
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filter = TimeGroupOverlapFilter(
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self.config.image_dir,
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self.config.output_dir,
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overlap_threshold=self.config.time_group_overlap_threshold
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)
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deleted_files = filter.filter_overlapping_groups(
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self.gps_points,
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time_threshold=self.config.time_group_interval
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)
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# 更新GPS点数据，移除被删除的图像
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self.gps_points = self.gps_points[~self.gps_points['file'].isin(
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deleted_files)]
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self.logger.info(f"重叠时间组过滤后剩余 {len(self.gps_points)} 个GPS点")
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# 可视化过滤结果
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self.visualizer.visualize_filter_step(
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self.gps_points, previous_points, "3-Time Group Overlap")
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# # TODO 过滤密集点算法还需要更新
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# def filter_points(self):
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# """过滤GPS点"""
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# # 过滤密集点
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# previous_points = self.gps_points.copy()
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@ -196,8 +190,6 @@ class ImagePreprocessor:
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# self.visualizer.visualize_filter_step(
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# self.gps_points, previous_points, "4-Dense Points")
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return self.gps_points
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def divide_grids(self) -> Tuple[Dict[tuple, pd.DataFrame], Dict[tuple, tuple]]:
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"""划分网格
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Returns:
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@ -262,8 +254,8 @@ class ImagePreprocessor:
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try:
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self.extract_gps()
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self.cluster()
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# self.filter_time_group_overlap()
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self.filter_points()
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self.filter_isolated_points()
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self.filter_time_group_overlap()
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grid_points, translations = self.divide_grids()
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self.copy_images(grid_points)
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self.logger.info("预处理任务完成")
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@ -280,8 +272,8 @@ 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"/home/cug/datasets/1815/project/images",
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output_dir=r"/home/cug/ODM_output/1815",
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image_dir=r"/home/cug/datasets/134/code/images",
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output_dir=r"/home/cug/ODM_output/134",
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cluster_eps=0.01,
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cluster_min_samples=5,
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