Python scipy.ndimage.filters.percentile_filter() Examples

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Example #1
Source File: image.py    From chinese_ocr with MIT License 5 votes vote down vote up 
def estimate_skew_angle(raw):
    """
    估计图像文字角度
    """
    
    def resize_im(im, scale, max_scale=None):
        f=float(scale)/min(im.shape[0], im.shape[1])
        if max_scale!=None and f*max(im.shape[0], im.shape[1])>max_scale:
            f=float(max_scale)/max(im.shape[0], im.shape[1])
        return cv2.resize(im, (0, 0), fx=f, fy=f)

    raw = resize_im(raw, scale=600, max_scale=900)
    image = raw-amin(raw)
    image = image/amax(image)
    m = interpolation.zoom(image,0.5)
    m = filters.percentile_filter(m,80,size=(20,2))
    m = filters.percentile_filter(m,80,size=(2,20))
    m = interpolation.zoom(m,1.0/0.5)

    w,h = min(image.shape[1],m.shape[1]),min(image.shape[0],m.shape[0])
    flat = np.clip(image[:h,:w]-m[:h,:w]+1,0,1)
    d0,d1 = flat.shape
    o0,o1 = int(0.1*d0),int(0.1*d1)
    flat = amax(flat)-flat
    flat -= amin(flat)
    est = flat[o0:d0-o0,o1:d1-o1]
    angles = range(-15,15)
    estimates = []
    for a in angles:
        roest =interpolation.rotate(est,a,order=0,mode='constant')
        v = np.mean(roest,axis=1)
        v = np.var(v)
        estimates.append((v,a))
    
    _,a = max(estimates)
    return a