数据增强

随机添加光点

class halo():
    """
    u：高斯分布的均值
    sigma：方差
    nums:在一张图片中随机添加几个光点
    prob:使用halo的概率
    """
    def __init__(self,nums,u=0,sigma=0.2,prob=0.5):
        self.u=u#均值
        self.sig=math.sqrt(sigma)#标准差
        self.nums=nums
        self.prob=prob
    def create_kernel(self,maxh=32,maxw=50):
        height_scope=[10,maxh]#高度范围
        weight_scope=[20,maxw]#宽度范围
        x=np.linspace(self.u-3*self.sig,self.u+3*self.sig,random.randint(*height_scope))
        y=np.linspace(self.u-3*self.sig,self.u+3*self.sig,random.randint(*weight_scope))
        Gauss_map=np.zeros((len(x),len(y)))
        for i in range(len(x)):
            for j in range(len(y)):
                Gauss_map[i,j]=np.exp(-((x[i]-self.u)**2+(y[j]-self.u)**2)/(2*self.sig**2))/(
                    math.sqrt(2*math.pi)*self.sig)
        return Gauss_map
    def __call__(self, img):
        if random.random()<self.prob:
            #初始化一个高斯核，32为高度方向的最大值，60为宽度方向的最大值
            Gauss_map=self.create_kernel(32,60)
            ###################################
            #PIL image转换为array
            img1=np.asarray(img)
            #修改图片的读取格式
            #img1.flags.writeable=True #将数组改写为读写模式
            ###################################
            nums=random.randint(1,self.nums) #随机生成[1,nums]个光点
            img1=img1.astype(np.float)#将img1变换成float类型
            for i in range(nums):
                #处理这nums个随机点
                img_h,img_w=img1.shape
                #在原图中随机找一个点
                pointx=random.randint(0,img_h-10)
                pointy=random.randint(0,img_w-10)
                #判断是否超出限制
                h,w=Gauss_map.shape
                endx=pointx+h
                endy=pointy+w
                if endx>img_h:
                    endx=img_h
                    Gauss_map=Gauss_map[1:img_h-pointx+1,:]
                if endy>img_w:
                    endy=img_w
                    Gauss_map=Gauss_map[:,1:img_w-pointy+1]

                #加上不均匀光照
                img1[pointx:endx,pointy:endy]+=Gauss_map*255.0
            img1[img1>255.0]=255.0#进行限幅，不然uint8会从0开始重新计数
            img=img1
               #将array转换为image
        return Image.fromarray(np.uint8(img))

    net=halo(100,0,0.2,0.5)
    pil_im=Image.open('D:/zwy.jpg').convert('L')
    img=net(pil_im)
    img.show()

随机增强图像亮度

class RandomBrightness(object):
    """
    随机改变亮度
    pil：pil格式的图片
    """
    def __init__(self,prob=1.5):
        self.prob=prob
    def __call__(self, pil):
        rgb=np.asarray(pil)
        if random.random()<self.prob:
            hsv=cv2.cvtColor(rgb,cv2.COLOR_RGB2HSV)
            h,s,v=cv2.split(hsv)
            adjust=random.choice([0.5,0.7,0.9,1.2,1.5,1.7])
            v=v*adjust
            #将v修改到[0,255]区间内
            v=np.clip(v,0,255).astype(hsv.dtype)
            hsv=cv2.merge((h,s,v))
            rgb=cv2.cvtColor(hsv,cv2.COLOR_HSV2RGB)
        return rgb

    net=RandomBrightness()
    img=cv2.imread("D:/hjb.jpg")
    img=net(img)
    cv2.imshow("rgb",img)
    cv2.waitKey(0)
    cv2.destroyWindow()