fgen.py 文件源码

def gauss_degrade(image,margin=1.0,change=None,noise=0.02,minmargin=0.5,inner=1.0):
    if image.ndim==3: image = mean(image,axis=2)
    m = mean([amin(image),amax(image)])
    image = 1*(image>m)
    if margin<minmargin: return 1.0*image
    pixels = sum(image)
    if change is not None:
        npixels = int((1.0+change)*pixels)
    else:
        edt = distance_transform_edt(image==0)
        npixels = sum(edt<=(margin+1e-4))
    r = int(max(1,2*margin+0.5))
    ri = int(margin+0.5-inner)
    if ri<=0: mask = binary_dilation(image,iterations=r)-image
    else: mask = binary_dilation(image,iterations=r)-binary_erosion(image,iterations=ri)
    image += mask*randn(*image.shape)*noise*min(1.0,margin**2)
    smoothed = gaussian_filter(1.0*image,margin)
    frac = max(0.0,min(1.0,npixels*1.0/prod(image.shape)))
    threshold = mquantiles(smoothed,prob=[1.0-frac])[0]
    result = (smoothed>threshold)
    return 1.0*result