diff --git a/image_method.py b/image_method.py
new file mode 100644
index 0000000..3ffb860
--- /dev/null
+++ b/image_method.py
@@ -0,0 +1,92 @@
+import cv2
+import numpy as np
+
+"""功能一:"""
+#1图像转换为灰度图像
+def grayscale(image):
+    return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+#1垂直镜像
+def mirror_vertical(image):
+    vertical = cv2.flip(image,0,dst=None) 
+    return vertical
+
+#1图像放缩（！）
+def change_size(image):
+    change_image = cv2.resize(image, (256, 256))
+    return change_image
+
+#1旋转画布
+def rotate(image):
+    rows, cols, depth = image.shape
+    rotation = cv2.getRotationMatrix2D((cols / 2, rows / 2), 90, 1) 
+    return rotation
+
+#1水平镜像
+def mirror_horizontal(image):
+    horizontal = cv2.flip(image,1,dst=None) 
+    return horizontal
+
+#1保持横纵比例
+def keep_shape(image):
+    # 获取图像的高度和宽度
+    height, width = image.shape[:2]
+    # 计算裁剪区域crop
+    target_aspect_ratio = 16 / 9
+    if width / height > target_aspect_ratio:
+        new_width = int(height * target_aspect_ratio)
+        offset = (width - new_width) // 2
+        crop = image[:, offset:offset + new_width]
+    else:
+        new_height = int(width / target_aspect_ratio)
+        offset = (height - new_height) // 2
+        crop = image[offset:offset + new_height, :]
+    return crop
+
+#1还原原始图像
+
+
+"""功能二"""
+#2高斯滤波模糊去噪
+def apply_blur(image):
+    blurred = cv2.GaussianBlur(image, (5, 5), 0)
+    return blurred
+
+#2肤色处理
+def skin(image):
+    # 将图像从BGR转换到HSV
+    hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
+    # 定义肤色的HSV范围
+    lower_skin = np.array([0, 20, 70], dtype=np.uint8)
+    upper_skin = np.array([20, 255, 255], dtype=np.uint8)
+    # 创建掩码
+    mask = cv2.inRange(hsv_image, lower_skin, upper_skin)
+    # 应用掩码到原始图像
+    skin_image = cv2.bitwise_and(image, image, mask=mask)
+    return skin_image
+
+#2腐蚀
+def center_erosion(image):
+    erode = cv2.imread(image, cv2.IMREAD_UNCHANGED)
+    # 使用一个5x5的交叉型结构元（核心在几何中心）对二值图片src进行腐蚀
+    kernel = cv2.getStructuringElement(cv2.MORPH_CROSS, (5, 5));
+    erosion = cv2.erode(erode,kernel)
+    return erosion
+
+
+"""功能三"""
+#边缘检测
+def detect_edges(image):
+    """使用Canny边缘检测算法检测图像的边缘"""
+    edges = cv2.Canny(image, 100, 200)
+    return edges
+
+
+
+
+# 更多自定义处理方法...
+
+#识别边缘
+
+    
+