116 lines
4.6 KiB
Python
116 lines
4.6 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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import cv2
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import os
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import numpy as np
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import sys
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# 添加项目根目录到Python路径
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current_dir = os.path.dirname(os.path.abspath(__file__))
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project_root = os.path.dirname(current_dir)
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sys.path.append(project_root)
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from utils.detect_dual_track_lines import auto_detect_dual_track_lines
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def visualize_dual_track_detection():
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test_dir = 'res/path/dual'
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results = []
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# 创建结果保存目录
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result_dir = 'results/dual_track'
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os.makedirs(result_dir, exist_ok=True)
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for img_file in sorted(os.listdir(test_dir)):
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if img_file.endswith('.png'):
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img_path = os.path.join(test_dir, img_file)
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print(f'\n处理图片: {img_path}')
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# 读取图像
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img = cv2.imread(img_path)
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if img is None:
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print(f' 无法读取图像: {img_path}')
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continue
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# 调用自动检测函数，开启观察模式
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result = auto_detect_dual_track_lines(img, observe=True, delay=1000, save_log=True)
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# 检查检测结果
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if result[0] is not None:
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center_info, left_info, right_info = result
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# 创建结果图像
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result_img = img.copy()
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height, width = img.shape[:2]
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center_x = width // 2
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# 绘制左右轨迹线
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left_x1, left_y1, left_x2, left_y2 = left_info["line"]
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right_x1, right_y1, right_x2, right_y2 = right_info["line"]
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cv2.line(result_img, (int(left_x1), int(left_y1)), (int(left_x2), int(left_y2)), (255, 0, 0), 2)
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cv2.line(result_img, (int(right_x1), int(right_y1)), (int(right_x2), int(right_y2)), (0, 0, 255), 2)
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# 绘制中心线
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center_point = center_info["point"]
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center_line_x1 = (left_x1 + right_x1) // 2
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center_line_y1 = (left_y1 + right_y1) // 2
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cv2.line(result_img, (center_line_x1, center_line_y1), center_point, (0, 255, 0), 2)
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# 绘制图像中心线
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cv2.line(result_img, (center_x, 0), (center_x, height), (0, 0, 255), 1)
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# 标记中心点
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cv2.circle(result_img, center_point, 10, (255, 0, 255), -1)
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# 显示偏差信息
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deviation = center_info["deviation"]
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cv2.putText(result_img, f"偏差: {deviation}px", (10, 30),
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cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
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# 显示是否为石板路模式
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stone_path_mode = center_info["stone_path_mode"]
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mode_text = "石板路模式" if stone_path_mode else "标准模式"
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cv2.putText(result_img, mode_text, (10, 60),
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cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 2)
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# 显示检测结果
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cv2.imshow("双轨迹线检测结果", result_img)
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key = cv2.waitKey(0) # 等待按键
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# 保存结果图像
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result_path = os.path.join(result_dir, f"result_{img_file}")
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cv2.imwrite(result_path, result_img)
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print(f' 检测成功! 偏差: {deviation}px, 模式: {mode_text}')
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print(f' 结果已保存至: {result_path}')
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# 按ESC键退出
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if key == 27: # ESC键
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break
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results.append((img_file, True, deviation, stone_path_mode))
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else:
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print(f' 检测失败!')
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results.append((img_file, False, None, None))
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# 关闭所有窗口
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cv2.destroyAllWindows()
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# 打印检测结果汇总
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print('\n检测结果汇总:')
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success_count = 0
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for img_file, success, deviation, stone_path_mode in results:
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status = '成功' if success else '失败'
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if success:
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success_count += 1
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mode_text = "石板路模式" if stone_path_mode else "标准模式"
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dev_info = f'偏差: {deviation}px, 模式: {mode_text}'
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else:
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dev_info = ''
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print(f'{img_file}: {status} {dev_info}')
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success_rate = (success_count / len(results)) * 100 if results else 0
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print(f'\n总成功率: {success_rate:.2f}% ({success_count}/{len(results)})')
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if __name__ == "__main__":
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visualize_dual_track_detection()
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