### 解决 SyntaxWarning 无效转义序列问题 在 Python 中，反斜杠 `\` 是转义字符，当在字符串中使用路径时，可能会出现无效转义序列的警告。为避免此问题，可使用原始字符串（在字符串前加 `r`）或使用双反斜杠 `\\`。 ```python # 使用原始字符串 folder_path = r'D:\yepian\fan_blade_imag' # 或者使用双反斜杠 folder_path = 'D:\\yepian\\fan_blade_imag' ``` ### 解决 OpenCV imread 无法打开文件问题 `cv2.imread` 无法打开文件通常是由于文件路径错误或文件不存在。可以添加一些检查来确保文件存在，并且路径正确。 ```python import os import cv2 image_path = r'D:\yepian\fan_blade_imag\example.jpg' if os.path.exists(image_path): image = cv2.imread(image_path) if image is None: print(f"无法读取图像: {image_path}，可能是文件格式不支持。") else: print(f"文件不存在: {image_path}") ``` ### 解决高斯模糊源图像为空报错问题 高斯模糊操作时源图像为空通常是因为 `cv2.imread` 没有成功读取图像。在进行高斯模糊之前，需要确保图像已经成功读取。 ```python import cv2 image_path = r'D:\yepian\fan_blade_imag\example.jpg' image = cv2.imread(image_path) if image is not None: blurred = cv2.GaussianBlur(image, (7, 7), 0) else: print(f"无法读取图像: {image_path}") ``` ### 叶片裂纹检测代码优化 以下是对叶片裂纹检测代码的优化，包括更细致的预处理、不同的边缘检测算法尝试以及更合理的轮廓筛选： ```python import cv2 import numpy as np import os def preprocess_image(image): # 转换为灰度图 gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # 高斯模糊 blurred = cv2.GaussianBlur(gray, (5, 5), 0) # 直方图均衡化 equalized = cv2.equalizeHist(blurred) return equalized def detect_cracks(image): # Canny 边缘检测 edges = cv2.Canny(image, 50, 150) # 形态学处理 kernel = np.ones((3, 3), np.uint8) dilated = cv2.dilate(edges, kernel, iterations=1) eroded = cv2.erode(dilated, kernel, iterations=1) # 查找轮廓 contours, _ = cv2.findContours(eroded, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) return contours def filter_contours(contours, min_area=100, min_aspect=2): filtered_contours = [] for contour in contours: area = cv2.contourArea(contour) if area < min_area: continue rect = cv2.minAreaRect(contour) width, height = rect[1] if min(width, height) > 0: aspect = max(width, height) / min(width, height) if aspect > min_aspect: filtered_contours.append(contour) return filtered_contours def draw_cracks(original, contours): result = original.copy() cv2.drawContours(result, contours, -1, (0, 0, 255), 2) cv2.putText(result, f"Cracks: {len(contours)}", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2) return result def simple_crack_detection(image_path, sensitivity='medium'): image = cv2.imread(image_path) if image is None: print(f"无法读取图像: {image_path}") return None original = image.copy() preprocessed = preprocess_image(image) contours = detect_cracks(preprocessed) if sensitivity == 'low': min_area = 200 min_aspect = 4 elif sensitivity == 'medium': min_area = 80 min_aspect = 2.5 else: # high min_area = 50 min_aspect = 2 filtered_contours = filter_contours(contours, min_area, min_aspect) result = draw_cracks(original, filtered_contours) return result def batch_process_images(folder_path, sensitivity='medium'): image_extensions = ['.jpg', '.jpeg', '.png'] image_files = [os.path.join(folder_path, f) for f in os.listdir(folder_path) if any(f.lower().endswith(ext) for ext in image_extensions)] for image_path in image_files: result = simple_crack_detection(image_path, sensitivity) if result is not None: output_path = os.path.splitext(image_path)[0] + '_result.png' cv2.imwrite(output_path, result) print(f"处理结果已保存至: {output_path}") # 使用示例 folder_path = r'D:\yepian\fan_blade_imag' batch_process_images(folder_path, sensitivity='medium') ```