175 lines
5.7 KiB
Python
175 lines
5.7 KiB
Python
import numpy as np
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import time
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import math
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import os
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from Ai_tottle.touying.ImageReproject_python import ir_target_positioning, ir_red_line_reproject, ir_img_reproject, \
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CamParas,Point
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# from img_types import Point, CamParas
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# from image_reproject import ir_target_positioning, ir_red_line_reproject, ir_img_reproject
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os.environ['GDAL_DISABLE_EXCEPTIONS'] = 'NO' # 显式启用异常处理
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# 定义常量
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pi = math.pi
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def test_target_positioning():
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"""测试目标定位功能"""
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# 输入参数
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u = 1520 # 示例图像u坐标
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v = 2512 # 示例图像v坐标
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interval = 0.05 # 高程迭代间隔
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gimbal_yaw = 66.40 * pi / 180 # 示例云台偏航角
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gimbal_pitch = -90 * pi / 180 # 示例云台俯仰角
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gimbal_roll = 0 * pi / 180 # 示例云台横滚角
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h = 590.834 # 示例相机高度
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l = (103 + 59 / 60.0 + 26.07 / 3600.0) * pi / 180 # 示例相机经度
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b = (30 + 45 / 60.0 + 46.48 / 3600.0) * pi / 180 # 示例相机纬度
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img_width = 4032 # 示例图像宽度
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img_height = 3024 # 示例图像高度
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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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)
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# DEM文件路径
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# dem_file = "/home/GW/ImageReproject_python/dem.tif" # 确保此文件存在
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dem_file = r"D:\project\test-touying\ImageReproject_python\dem.tif" # 确保此文件存在
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# 测量执行时间
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start_time = time.time()
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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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# 计算执行时间
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elapsed_time = (time.time() - start_time) * 1000 # 转换为毫秒
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# 输出结果
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print(f"目标定位耗时: {elapsed_time:.2f} ms")
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print(f"目标位置: 经度={x }°, 纬度={y }°, 高度={z:.2f}m")
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def read_txt(filename):
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"""从文本文件读取点坐标"""
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points = []
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try:
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with open(filename, 'r') as f:
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for line in f:
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parts = line.strip().split()
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if len(parts) >= 4: # 标签 x y z
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label = parts[0]
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x = float(parts[1])
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y = float(parts[2])
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z = float(parts[3])
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point = Point(x, y, z)
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points.append(point)
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except Exception as e:
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print(f"读取文件失败: {filename}, 错误: {e}")
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return points
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def test_red_line_reproject():
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"""测试红线重投影功能"""
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# 输入参数
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gimbal_yaw = 66.40 * pi / 180 # 示例云台偏航角
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gimbal_pitch = -90 * pi / 180 # 示例云台俯仰角
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gimbal_roll = 0 * pi / 180 # 示例云台横滚角
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h = 590.834 # 示例相机高度
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l = (103 + 59 / 60.0 + 26.07 / 3600.0) * pi / 180 # 示例相机经度
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b = (30 + 45 / 60.0 + 46.48 / 3600.0) * pi / 180 # 示例相机纬度
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img_width = 4032 # 示例图像宽度
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img_height = 3024 # 示例图像高度
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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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)
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# 图像文件路径
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img_file = r"D:\project\test-touying\ImageReproject_python\test_image.jpeg" # 确保此文件存在
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img_save_file = r"D:\project\test-touying\ImageReproject_python\test_image_reprojected.jpg"
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# 读取点坐标
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points = [] # 如果有点坐标文件，可以使用read_txt函数读取
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points =read_txt(r"D:\project\test-touying\ImageReproject_python\points.txt")
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# 测量执行时间
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start_time = time.time()
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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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# 计算执行时间
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elapsed_time = (time.time() - start_time) * 1000 # 转换为毫秒
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# 输出结果
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print(f"红线重投影耗时: {elapsed_time:.2f} ms")
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def test_img_reproject():
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"""测试图像重投影功能"""
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# 输入参数
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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 * pi / 180 # 示例云台偏航角
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gimbal_pitch = -90 * pi / 180 # 示例云台俯仰角
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gimbal_roll = 0 * pi / 180 # 示例云台横滚角
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h = 590.834 # 示例相机高度
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l = (103 + 59 / 60.0 + 26.07 / 3600.0)* pi / 180 # 示例相机经度
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b = (30 + 45 / 60.0 + 46.48 / 3600.0)* pi / 180 # 示例相机纬度
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img_width = 4032 # 示例图像宽度
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img_height = 3024 # 示例图像高度
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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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)
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# 测量执行时间
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start_time = time.time()
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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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# 计算执行时间
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elapsed_time = (time.time() - start_time) * 1000 # 转换为毫秒
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# 输出结果
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print(f"图像重投影耗时: {elapsed_time:.2f} ms")
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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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def main():
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"""主函数"""
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# # 测试目标定位功能
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# try:
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# test_target_positioning()
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# except Exception as e:
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# print(f"目标定位测试失败: {e}")
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# # # 测试红线重投影功能
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# try:
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# test_red_line_reproject()
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# except Exception as e:
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# print(f"红线重投影测试失败: {e}")
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# # 测试图像重投影功能
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try:
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test_img_reproject()
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except Exception as e:
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print(f"图像重投影测试失败: {e}")
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if __name__ == "__main__":
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main() |