[人工智能]opencv利用opencv对数据图像实现数据增强

# -*- coding: utf-8 -*-
"""
# 数据增强实现
"""
import cv2
import numpy as np


# 图像平移
def img_translation(image):
    # 图像平移 下、上、右、左平移
    M = np.float32([[1, 0, 0], [0, 1, 100]])
    img_down = cv2.warpAffine(image, M, (image.shape[1], image.shape[0]))

    M = np.float32([[1, 0, 0], [0, 1, -100]])
    img_up = cv2.warpAffine(image, M, (image.shape[1], image.shape[0]))

    M = np.float32([[1, 0, 100], [0, 1, 0]])
    img_right = cv2.warpAffine(image, M, (image.shape[1], image.shape[0]))

    M = np.float32([[1, 0, -100], [0, 1, 0]])
    img_left = cv2.warpAffine(image, M, (image.shape[1], image.shape[0]))

    # 显示图形
    cv2.imshow("down", img_down)
    cv2.imshow("up", img_up)
    cv2.imshow("right", img_right)
    cv2.imshow("left", img_left)


# 图像缩放
def img_scale(image):
    result = cv2.resize(image, (200, 100))
    cv2.imshow("scale", result)


# 图像翻转
def img_flip(image):
    # 0以X轴为对称轴翻转,>0以Y轴为对称轴翻转, <0X轴Y轴翻转
    horizontally = cv2.flip(image, 0)  # 水平镜像
    vertically = cv2.flip(image, 1)  # 垂直镜像
    hv = cv2.flip(image, -1)  # 水平垂直镜像

    # 显示图形
    cv2.imshow("Horizontally", horizontally)
    cv2.imshow("Vertically", vertically)
    cv2.imshow("Horizontally & Vertically", hv)


# 图像旋转
def img_rotation(image):
    # 原图的高、宽 以及通道数
    rows, cols, channel = image.shape

    # 绕图像的中心旋转
    # 参数：旋转中心 旋转度数 scale
    M = cv2.getRotationMatrix2D((cols / 2, rows / 2), 90, 1)
    # 参数：原始图像 旋转参数 元素图像宽高
    rotated = cv2.warpAffine(image, M, (cols, rows))

    # 显示图像
    cv2.imshow("rotated", rotated)


# 图像加噪
def img_noise(image, mean=0, var=0.001):
    '''
        添加高斯噪声
        mean : 均值
        var : 方差
    '''
    image = np.array(image / 255, dtype=float)
    noise = np.random.normal(mean, var ** 0.5, image.shape)
    out = image + noise
    if out.min() < 0:
        low_clip = -1.
    else:
        low_clip = 0.
    out = np.clip(out, low_clip, 1.0)
    out = np.uint8(out * 255)

    cv2.imshow("noise", out)


# 图像亮度调节
def img_brightness(image):
    contrast = 1  # 对比度
    brightness = 100  # 亮度
    pic_turn = cv2.addWeighted(image, contrast, image, 0, brightness)
    # cv2.addWeighted(对象,对比度,对象,对比度)
    '''cv2.addWeighted()实现的是图像透明度的改变与图像的叠加'''

    cv2.imshow('bright', pic_turn)  # 显示图片



if __name__ == '__main__':
    # src = cv2.imread('./images/jie1.jpg')
    src = cv2.imread('./images/luowen.jpg')
    src = cv2.imread('./green_dog.jpg')
    img_translation(src)
    img_scale(src)
    img_flip(src)
    img_rotation(src)
    img_noise(src)
    img_brightness(src)

    cv2.waitKey(0)
    cv2.destroyAllWindows()

显示效果如下所示：