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