n06_pytorch_utils.py 文件源码

def randomFilter(img, limit=0.5, u=0.5):
    if random.random() < u:
        height, width, channel = img.shape

        alpha = limit * random.uniform(0, 1)

        ##kernel = np.ones((5,5),np.float32)/25
        kernel = np.ones((3, 3), np.float32) / 9 * 0.2

        # type = random.randint(0,1)
        # if type==0:
        #     kernel = np.ones((3,3),np.float32)/9*0.2
        # if type==1:
        #     kernel = np.array([[-1,-1,-1], [-1,9,-1], [-1,-1,-1]])*0.5

        # kernel = alpha *sharp +(1-alpha)*blur
        # kernel = np.random.randn(5, 5)
        # kernel = kernel/np.sum(kernel*kernel)**0.5

        img = alpha * cv2.filter2D(img, -1, kernel) + (1 - alpha) * img
        img = np.clip(img, 0., 1.)

    return img


##https://github.com/pytorch/vision/pull/27/commits/659c854c6971ecc5b94dca3f4459ef2b7e42fb70
## color augmentation

# brightness, contrast, saturation-------------
# from mxnet code, see: https://github.com/dmlc/mxnet/blob/master/python/mxnet/image.py

# def to_grayscle(img):
#     blue  = img[:,:,0]
#     green = img[:,:,1]
#     red   = img[:,:,2]
#     grey = 0.299*red + 0.587*green + 0.114*blue
#     return grey