修改后处理
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@ -14,17 +14,6 @@ class MergePly:
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def merge_grid_laz(self, grid_points: Dict[tuple, pd.DataFrame]):
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"""合并所有网格的点云数据"""
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if len(grid_points) == 1:
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grid_id = list(grid_points.keys())[0]
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shutil.copy2(os.path.join(self.output_dir,
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f"grid_{grid_id[0]}_{grid_id[1]}",
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"project",
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"odm_georeferencing",
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"odm_georeferenced_model.laz"),
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os.path.join(self.output_dir,
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"pointcloud.laz")
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)
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try:
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# 获取所有点云文件路径
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laz_files = []
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@ -240,12 +240,15 @@ class MergeObj:
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# 计算新的尺寸(长宽各变为1/4)
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new_size = (img.shape[1] // 4, img.shape[0] // 4)
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# 使用双三次插值进行下采样
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resized_img = cv2.resize(img, new_size, interpolation=cv2.INTER_CUBIC)
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resized_img = cv2.resize(
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img, new_size, interpolation=cv2.INTER_CUBIC)
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# 保存压缩后的图像
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if file.lower().endswith('.png'):
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cv2.imwrite(dst_path, resized_img, [cv2.IMWRITE_PNG_COMPRESSION, 9])
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cv2.imwrite(dst_path, resized_img, [
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cv2.IMWRITE_PNG_COMPRESSION, 9])
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else:
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cv2.imwrite(dst_path, resized_img, [cv2.IMWRITE_JPEG_QUALITY, 95])
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cv2.imwrite(dst_path, resized_img, [
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cv2.IMWRITE_JPEG_QUALITY, 95])
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else:
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self.logger.warning(f"无法读取图像文件: {src_path}")
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shutil.copy2(src_path, dst_path)
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@ -289,16 +292,6 @@ class MergeObj:
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def merge_grid_obj(self, grid_points: Dict[tuple, pd.DataFrame], translations: Dict[tuple, tuple]):
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"""合并所有网格的OBJ模型"""
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if len(grid_points) == 1:
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grid_id = list(grid_points.keys())[0]
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shutil.copytree(os.path.join(self.output_dir,
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f"grid_{grid_id[0]}_{grid_id[1]}",
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"project",
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"odm_texturing"),
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os.path.join(self.output_dir, "texturing"))
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os.rename(os.path.join(self.output_dir, "texturing", "odm_textured_model_geo.obj"),
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os.path.join(self.output_dir, "texturing", "textured_model.obj"))
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try:
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# 创建输出目录
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output_model_dir = os.path.join(self.output_dir, "texturing")
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@ -106,17 +106,6 @@ class MergeTif:
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self.logger.info(f"开始合并{product_name}")
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if len(grid_points) < 2:
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grid_id = list(grid_points.keys())[0]
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shutil.copy2(os.path.join(self.output_dir,
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f"grid_{grid_id[0]}_{grid_id[1]}",
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"project",
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product_path,
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filename),
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os.path.join(self.output_dir,
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product_info['output'])
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)
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input_tif1, input_tif2 = None, None
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merge_count = 0
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