havoc420ubuntu
852a948a6f
- Updated task_1.py to improve navigation logic and streamline movement functions. - Enhanced task_2.py with refined movement parameters for better execution and added logging for debugging. - Adjusted function calls in main.py to reflect changes in task execution flow.
106 lines
3.7 KiB
Python
106 lines
3.7 KiB
Python
import cv2
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import os
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import sys
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import time
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import argparse
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# 添加父目录到系统路径
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current_dir = os.path.dirname(os.path.abspath(__file__))
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project_root = os.path.dirname(os.path.dirname(current_dir))
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sys.path.append(project_root)
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from utils.yellow_area_analyzer import analyze_yellow_area_ratio
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def process_image(image_path, save_dir=None, show_steps=False):
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"""处理单张图像，分析黄色区域占比"""
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print(f"处理图像: {image_path}")
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# 分析黄色区域占比
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start_time = time.time()
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yellow_ratio = analyze_yellow_area_ratio(image_path, debug=show_steps, save_result=save_dir is not None)
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processing_time = time.time() - start_time
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# 输出结果
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print(f"处理时间: {processing_time:.3f}秒")
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print(f"黄色区域占比: {yellow_ratio:.2%}")
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if yellow_ratio > 0.5:
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print("警告: 图像中黄色区域占比超过50%")
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elif yellow_ratio > 0.3:
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print("注意: 图像中黄色区域占比较高")
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elif yellow_ratio < 0.05:
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print("注意: 图像中几乎没有黄色区域")
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print("-" * 30)
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# 如果保存结果，确保目录存在
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if save_dir and not os.path.exists(save_dir):
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os.makedirs(save_dir)
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return yellow_ratio
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def process_directory(dir_path, save_dir=None, show_steps=False):
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"""处理目录中的所有图像"""
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print(f"处理目录: {dir_path}")
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# 检查目录是否存在
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if not os.path.isdir(dir_path):
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print(f"错误: 目录 '{dir_path}' 不存在")
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return
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# 获取目录中的所有图像文件
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image_extensions = ['.jpg', '.jpeg', '.png', '.bmp']
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image_files = [f for f in os.listdir(dir_path)
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if os.path.isfile(os.path.join(dir_path, f)) and
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os.path.splitext(f)[1].lower() in image_extensions]
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if not image_files:
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print(f"错误: 目录 '{dir_path}' 中没有图像文件")
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return
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# 处理每个图像文件
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results = {}
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for image_file in image_files:
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image_path = os.path.join(dir_path, image_file)
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yellow_ratio = process_image(image_path, save_dir, show_steps)
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results[image_file] = yellow_ratio
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# 输出统计信息
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print("=" * 50)
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print(f"处理完成，共 {len(results)} 张图像")
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if results:
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avg_ratio = sum(results.values()) / len(results)
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max_ratio = max(results.values())
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min_ratio = min(results.values())
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max_file = max(results, key=results.get)
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min_file = min(results, key=results.get)
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print(f"平均黄色区域占比: {avg_ratio:.2%}")
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print(f"最大黄色区域占比: {max_ratio:.2%} (文件: {max_file})")
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print(f"最小黄色区域占比: {min_ratio:.2%} (文件: {min_file})")
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return results
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def main():
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parser = argparse.ArgumentParser(description='黄色区域分析演示程序')
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parser.add_argument('--input', type=str, default='captured_images/test/image_20250525_090252.png', help='输入图像或目录的路径')
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parser.add_argument('--output', type=str, default='./results', help='输出结果的保存路径')
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parser.add_argument('--show', default=True, action='store_true', help='显示处理步骤')
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args = parser.parse_args()
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# 检查输入路径
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if not os.path.exists(args.input):
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print(f"错误：路径 '{args.input}' 不存在")
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return
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# 根据输入类型处理
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if os.path.isfile(args.input):
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# 单个文件
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process_image(args.input, args.output, args.show)
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else:
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# 目录
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process_directory(args.input, args.output, args.show)
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if __name__ == "__main__":
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main() |