UAV/post_pro/merge_tif.py

from osgeo import gdal
import logging
import os
from typing import Dict
import pandas as pd


class MergeTif:
    def __init__(self, output_dir: str):
        self.output_dir = output_dir
        self.logger = logging.getLogger('UAV_Preprocess.MergeTif')

    def merge_two_tifs(self, input_tif1: str, input_tif2: str, output_tif: str):
        """合并两张TIF影像"""
        try:
            self.logger.info("开始合并TIF影像")
            self.logger.info(f"输入影像1: {input_tif1}")
            self.logger.info(f"输入影像2: {input_tif2}")
            self.logger.info(f"输出影像: {output_tif}")

            # 检查输入文件是否存在
            if not os.path.exists(input_tif1) or not os.path.exists(input_tif2):
                error_msg = "输入影像文件不存在"
                self.logger.error(error_msg)
                raise FileNotFoundError(error_msg)

            # 打开影像，检查投影是否一致
            datasets = [gdal.Open(tif) for tif in [input_tif1, input_tif2]]
            if None in datasets:
                error_msg = "无法打开输入影像文件"
                self.logger.error(error_msg)
                raise ValueError(error_msg)

            projections = [dataset.GetProjection() for dataset in datasets]
            self.logger.debug(f"影像1投影: {projections[0]}")
            self.logger.debug(f"影像2投影: {projections[1]}")

            # 检查投影是否一致
            if len(set(projections)) != 1:
                error_msg = "影像的投影不一致，请先进行重投影！"
                self.logger.error(error_msg)
                raise ValueError(error_msg)

            # 创建 GDAL Warp 选项
            warp_options = gdal.WarpOptions(
                format="GTiff",
                resampleAlg="average",
                srcNodata=0,
                dstNodata=0,
                multithread=True
            )

            self.logger.info("开始执行影像拼接...")
            result = gdal.Warp(
                output_tif, [input_tif1, input_tif2], options=warp_options)

            if result is None:
                error_msg = "影像拼接失败"
                self.logger.error(error_msg)
                raise RuntimeError(error_msg)

            # 获取输出影像的基本信息
            output_dataset = gdal.Open(output_tif)
            if output_dataset:
                width = output_dataset.RasterXSize
                height = output_dataset.RasterYSize
                bands = output_dataset.RasterCount
                self.logger.info(f"拼接完成，输出影像大小: {width}x{height}，波段数: {bands}")

            self.logger.info(f"影像拼接成功，输出文件保存至: {output_tif}")

        except Exception as e:
            self.logger.error(f"影像拼接过程中发生错误: {str(e)}", exc_info=True)
            raise

    def merge_grid_tif(self, grid_points: Dict[int, pd.DataFrame], product_info: dict):
        """合并指定产品的所有网格"""
        product_name = product_info['name']
        product_path = product_info['path']
        filename = product_info['filename']

        self.logger.info(f"开始合并{product_name}")

        if len(grid_points) < 2:
            self.logger.info("只有一个网格，无需合并")
            return

        input_tif1, input_tif2 = None, None
        merge_count = 0

        try:
            for grid_idx, points in grid_points.items():
                grid_tif = os.path.join(
                    self.output_dir,
                    f"grid_{grid_idx + 1}",
                    "project",
                    product_path,
                    filename
                )

                if not os.path.exists(grid_tif):
                    self.logger.warning(
                        f"网格 {grid_idx + 1} 的{product_name}不存在: {grid_tif}")
                    continue

                if input_tif1 is None:
                    input_tif1 = grid_tif
                    self.logger.info(f"设置第一个输入{product_name}: {input_tif1}")
                else:
                    input_tif2 = grid_tif
                    output_tif = os.path.join(
                        self.output_dir, f"merged_{product_info['output']}")

                    self.logger.info(
                        f"开始合并{product_name}第 {merge_count + 1} 次:\n"
                        f"输入1: {input_tif1}\n"
                        f"输入2: {input_tif2}\n"
                        f"输出: {output_tif}"
                    )

                    self.merge_two_tifs(input_tif1, input_tif2, output_tif)
                    merge_count += 1

                    input_tif1 = output_tif
                    input_tif2 = None

            self.logger.info(
                f"{product_name}合并完成，共执行 {merge_count} 次合并，"
                f"最终输出文件: {input_tif1}"
            )

        except Exception as e:
            self.logger.error(
                f"{product_name}合并过程中发生错误: {str(e)}", exc_info=True)
            raise

    def merge_all_tifs(self, grid_points: Dict[int, pd.DataFrame]):
        """合并所有产品（正射影像、DSM和DTM）"""
        try:
            products = [
                {
                    'name': '正射影像',
                    'path': 'odm_orthophoto',
                    'filename': 'odm_orthophoto.original.tif',
                    'output': 'orthophoto.tif'
                },
                {
                    'name': 'DSM',
                    'path': 'odm_dem',
                    'filename': 'dsm.original.tif',
                    'output': 'dsm.tif'
                },
                {
                    'name': 'DTM',
                    'path': 'odm_dem',
                    'filename': 'dtm.original.tif',
                    'output': 'dtm.tif'
                }
            ]

            for product in products:
                self.merge_grid_tif(grid_points, product)

            self.logger.info("所有产品合并完成")
        except Exception as e:
            self.logger.error(f"产品合并过程中发生错误: {str(e)}", exc_info=True)
            raise


if __name__ == "__main__":
    import sys
    sys.path.append(os.path.dirname(
        os.path.dirname(os.path.abspath(__file__))))
    from utils.logger import setup_logger
    import pandas as pd
    
    # 设置输出目录和日志
    output_dir = r"G:\ODM_output\1009"
    setup_logger(output_dir)

    # 构造测试用的grid_points字典
    # 假设我们有两个网格，每个网格包含一些GPS点的DataFrame
    grid_points = {
        0: pd.DataFrame({
            'latitude': [39.9, 39.91],
            'longitude': [116.3, 116.31],
            'altitude': [100, 101]
        }),
        1: pd.DataFrame({
            'latitude': [39.92, 39.93],
            'longitude': [116.32, 116.33],
            'altitude': [102, 103]
        })
    }

    # 创建MergeTif实例并执行合并
    merge_tif = MergeTif(output_dir)
    merge_tif.merge_all_tifs(grid_points)