203 lines
5.1 KiB
Markdown
203 lines
5.1 KiB
Markdown
# ImageReproject Python版本
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这是原C++项目`ImageReproject_linux`的Python实现版本，提供图像重投影、目标定位和红线重投影功能。
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## 项目结构
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- `img_types.py`: 定义了各种数据结构，如点坐标、相机参数、外方位元素等
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- `dpal.py`: 数字摄影测量算法库，实现坐标转换和旋转矩阵计算等功能
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- `image_reproject.py`: 主要功能实现，包括目标定位、红线重投影和图像重投影
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- `test_image_reproject.py`: 测试脚本，用于测试各项功能
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## 功能说明
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### 1. 目标定位 (Target Positioning)
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根据图像上的点坐标，结合相机参数、云台角度、位置信息和DEM数据，计算该点在地面上的经纬度和高度。
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### 2. 红线重投影 (Red Line Reproject)
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将地面上的点坐标投影到图像上，并在图像上绘制这些点。
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### 3. 图像重投影 (Image Reproject)
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将地面上的点坐标投影到图像上，计算其在图像上的像素坐标。
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## 依赖库
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- NumPy: 用于数值计算
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- OpenCV (cv2): 用于图像处理
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- PyProj: 用于坐标转换
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- GDAL: 用于读取DEM数据
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## 安装依赖
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```bash
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pip install numpy opencv-python pyproj gdal
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```
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## 使用示例
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### 目标定位
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```python
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from img_types import CamParas
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from image_reproject import ir_target_positioning
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# 设置参数
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u = 1520 # 图像x坐标
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v = 2512 # 图像y坐标
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interval = 0.05 # 高程迭代间隔
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gimbal_yaw = 66.40 * math.pi / 180 # 云台偏航角(弧度)
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gimbal_pitch = -90 * math.pi / 180 # 云台俯仰角(弧度)
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gimbal_roll = 0 # 云台横滚角(弧度)
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h = 590.834 # 高度
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l = (103 + 59 / 60.0 + 26.07 / 3600.0) * math.pi / 180 # 经度(弧度)
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b = (30 + 45 / 60.0 + 46.48 / 3600.0) * math.pi / 180 # 纬度(弧度)
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img_width = 4032 # 图像宽度
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img_height = 3024 # 图像高度
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# 相机参数
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cam_paras = CamParas(
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fx=2795.68899,
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fy=2795.68899,
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cx=4.63568,
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cy=198.7387,
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k1=0.0199131,
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k2=-0.068595,
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k3=0.0568642,
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p1=-0.00119,
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p2=0.00124049
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)
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# DEM文件路径
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dem_file = "dem.tif"
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# 执行目标定位
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x, y, z = ir_target_positioning(
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u, v, interval, gimbal_pitch, gimbal_yaw, gimbal_roll,
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h, l, b, cam_paras, img_width, img_height, dem_file
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)
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# 输出结果
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print(f"目标位置: 经度={x * 180 / math.pi:.6f}°, 纬度={y * 180 / math.pi:.6f}°, 高度={z:.2f}m")
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```
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### 红线重投影
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```python
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from img_types import CamParas, Point
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from image_reproject import ir_red_line_reproject
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# 设置参数
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gimbal_yaw = 66.40 * math.pi / 180 # 云台偏航角(弧度)
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gimbal_pitch = -90 * math.pi / 180 # 云台俯仰角(弧度)
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gimbal_roll = 0 # 云台横滚角(弧度)
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h = 590.834 # 高度
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l = (103 + 59 / 60.0 + 26.07 / 3600.0) * math.pi / 180 # 经度(弧度)
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b = (30 + 45 / 60.0 + 46.48 / 3600.0) * math.pi / 180 # 纬度(弧度)
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img_width = 4032 # 图像宽度
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img_height = 3024 # 图像高度
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# 相机参数
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cam_paras = CamParas(
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fx=2795.68899,
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fy=2795.68899,
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cx=4.63568,
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cy=198.7387,
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k1=0.0199131,
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k2=-0.068595,
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k3=0.0568642,
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p1=-0.00119,
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p2=0.00124049
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)
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# 图像文件路径
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img_file = "test_image.jpg"
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img_save_file = "test_image_reprojected.jpg"
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# 点坐标列表
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points = [
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Point(103.990109 * math.pi / 180, 30.762915 * math.pi / 180, 481.64),
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# 添加更多点...
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]
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# 执行红线重投影
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ir_red_line_reproject(
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gimbal_pitch, gimbal_yaw, gimbal_roll, h, l, b,
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cam_paras, img_width, img_height, points, img_file, img_save_file
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)
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```
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### 图像重投影
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```python
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from img_types import CamParas
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from image_reproject import ir_img_reproject
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# 设置参数
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obj_longitude = 103.990109 # 目标点经度(度)
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obj_latitude = 30.762915 # 目标点纬度(度)
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obj_height = 481.64 # 目标点高度
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gimbal_yaw = 66.40 * math.pi / 180 # 云台偏航角(弧度)
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gimbal_pitch = -90 * math.pi / 180 # 云台俯仰角(弧度)
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gimbal_roll = 0 # 云台横滚角(弧度)
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h = 590.834 # 高度
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l = (103 + 59 / 60.0 + 26.07 / 3600.0) * math.pi / 180 # 经度(弧度)
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b = (30 + 45 / 60.0 + 46.48 / 3600.0) * math.pi / 180 # 纬度(弧度)
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img_width = 4032 # 图像宽度
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img_height = 3024 # 图像高度
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# 相机参数
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cam_paras = CamParas(
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fx=2795.68899,
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fy=2795.68899,
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cx=4.63568,
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cy=198.7387,
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k1=0.0199131,
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k2=-0.068595,
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k3=0.0568642,
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p1=-0.00119,
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p2=0.00124049
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)
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# 执行图像重投影
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pixel_x, pixel_y = ir_img_reproject(
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gimbal_pitch, gimbal_yaw, gimbal_roll, h, l, b,
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cam_paras, img_width, img_height, obj_longitude, obj_latitude, obj_height
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)
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# 输出结果
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print(f"目标点在图像上的坐标: x={pixel_x:.2f}, y={pixel_y:.2f}")
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```
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## 打包为动态库
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本项目支持通过 setuptools 打包为 Python 动态库（.so/.pyd）。
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### 打包命令
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```bash
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python setup.py bdist_wheel
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```
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或直接安装到本地环境：
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```bash
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pip install .
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```
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### 导入与调用
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安装后可直接在 Python 中导入：
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```python
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from imagereproject import ir_target_positioning, ir_red_line_reproject, ir_img_reproject, Point, CamParas
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```
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## 注意事项
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1. 使用前请确保已安装所有依赖库
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2. DEM文件和图像文件路径需要根据实际情况修改
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3. 相机参数和位置信息需要根据实际情况设置 |