python计算机视觉编程学习 harris角点检测遇到错误IndexError: list index out of range

[BunryIce]

最近在学习图灵图书的Python计算机视觉编程，在第二章2.1.2 在图像间寻找对应点学习过程中遇到了问题，请大佬帮忙解决
这是我按照书中做的harris.py

from PIL import Image
from numpy import *
from numpy.core.multiarray import ndarray
from pylab import *
from scipy.ndimage import filters
def compute_harris_response(im, sigma = 3):
    """在一幅灰度图像中，对每个像素计算Harris脚点检测器响应函数"""

    #计算导数
    imx = zeros(im.shape)
    filters.gaussian_filter(im, (sigma, sigma), (0, 1), imx)
    imy = zeros(im.shape)
    filters.gaussian_filter(im, (sigma, sigma), (0, 1), imy)

    #计算harris矩阵的分量
    Wxx = filters.gaussian_filter(imx * imx, sigma)
    Wxy = filters.gaussian_filter(imx * imy, sigma)
    Wyy = filters.gaussian_filter(imy * imy, sigma)

    #计算特征值和迹
    Wdet = Wxx * Wyy - Wxy ** 2
    Wtr = Wxx + Wyy

    return Wdet / Wtr

def get_harris_points(harrisim, min_dist = 10, threshold = 0.1):
    """从一幅harris响应图像中返回角点。min_dist为分割角点和图像边界的最少像素数目"""

    #寻找高于阈值的候选角点
    corner_threshold = harrisim.max() * threshold
    harrisim_t = (harrisim > corner_threshold) * 1

    #得到候选点的坐标
    coords = array(harrisim_t.nonzero()).T

    #以及他们的Harris响应值
    candidate_values = [harrisim[c[0], c[1]] for c in coords]

    #对候选点按照Harris响应值进行排序
    index = argsort(candidate_values)

    #将可行点的位置保存到数组中
    allowed_locations = zeros(harrisim.shape)
    allowed_locations[min_dist:-min_dist, min_dist:-min_dist] = 1

    #按照min_distance原则，选择最佳Harris点
    filtered_coords = []
    for i in index:
        if allowed_locations[coords[i, 0], coords[i,1]] == 1:
            filtered_coords.append(coords[i])
            allowed_locations[(coords[i, 0] - min_dist) : (coords[i,
                                                                  0] +
                                                           min_dist),
            (coords[i, 1] - min_dist): (coords[i, 1] + min_dist)] = 0

    return filtered_coords

def plot_harris_points(image, filtered_coords):
    """绘制图像中检测到的角点"""

    figure()
    gray()
    imshow(image)
    plot([p[1] for p in filtered_coords], [p[0] for p in filtered_coords], '*')
    axis('off')
    show()

def get_descriptors(image, filtered_coords, wid = 5):
    """对于每个返回的点，返回点周围2*wid+1个像素的值（假设选取点的min_distance>wid)"""

    desc = []
    for coords in filtered_coords:
        patch = image[coords[0] - wid:coords[0] + wid + 1, coords[1] -
                                                           wid:coords[1] +
                                                               wid + 1].flatten()
        desc.append(patch)

    return desc

def match(desc1, desc2, threshold = 0.5):
    """对于第一幅图像中的每个角点描述子，使用归一化互相关，选取他在第二幅图像中的匹配角点"""

    n = len(desc1[0])

    #点对的距离
    d = -ones((len(desc1), len(desc2)))
    for i in range(len(desc1)):
        for j in range(len(desc2)):
            d1 = (desc1[i] - mean(desc1[i])) / std(desc1[i])
            d2 = (desc2[j] - mean(desc2[j])) / std(desc2[j])
            ncc_value = sum(d1 * d2) / (n - 1)
            if ncc_value > threshold:
                d[i, j] = ncc_value

    ndx = argsort(-d)
    matchscores = ndx[:, 0]

    return matchscores

def match_twosided(desc1, desc2, threshold = 0.5):
    """两边对称版本的match（）"""

    matches_12 = match(desc1, desc2, threshold)
    matches_21 = match(desc2, desc1, threshold)

    ndx_12 = where(matches_12 >= 0)[0]

    #去除非对称的匹配
    for n in ndx_12:
        if matches_21[matches_12[n]] != n:
            matches_12[n] = -1
    return matches_12

def appendimages(im1, im2):
    """返回将两幅图像并列拼接成一幅的新图像"""

    #选取具有最少行数的图像，然后填充足够的空行
    rows1 = im1.shape[0]
    rows2 = im2.shape[0]

    if rows1 < rows2:
        im1 = concatenate((im1,zeros((rows2 - rows1, im1.shape[1]))), axis = 0)
    else:
        im2 = concatenate((im2, zeros((rows1 - rows2, im2.shape[1]))), axis= 0)
    #如果这些情况都没有，那么他们的行数相同，不需要进行填充

    return concatenate((im1, im2), axis=1)

def plot_matches(im1, im2, locs1, locs2, matchscores, show_below = True):
    """显示一幅带有连接匹配之间连线的图片
    输入：im1，im2（数组图像），locs1，locs2（特征位置）,matchscores(match()的输出),
    show_below（如果图像应该先是在匹配的下方）"""

    im3 = appendimages(im1, im2)
    if show_below:
        im3 = vstack((im3, im3))

    imshow(im3)

    cols1 = im1.shape[1]
    for i, m in enumerate(matchscores):
        if m > 0:
            plot([locs1[i][1], locs2[m][1] + cols1], [locs1[i][0], locs2[m][
                0]],'c')
    axis('off')

下面是我进行图像间寻找对应点尝试的代码

from PIL import Image
from numpy import *
from pylab import *
from scipy.ndimage import filters
import harris
from imtools import imresize

im1 = array(Image.open("alcatraz1.jpg").convert('L'))
im2 = array(Image.open("alcatraz2.jpg").convert('L'))

#resize加快匹配的速度

im1 = imresize(im1, (im1.shape[1]//2, im1.shape[0]//2))
im2 = imresize(im2, (im2.shape[1]//2, im2.shape[0]//2))

wid = 5
harrisim = harris.compute_harris_response(im1, 5)
filtered_coords1 = harris.get_harris_points(harrisim, wid+1)
d1 = harris.get_descriptors(im1, filtered_coords1, wid)

harrisim = harris.compute_harris_response(im2, 5)
filtered_coords2 = harris.get_harris_points(harrisim, wid+1)
d2 = harris.get_descriptors(im2, filtered_coords2, wid)

print ('starting matching')
matches = harris.match_twosided(d1, d2)

figure()
gray()
harris.plot_matches(im1, im2, filtered_coords1, filtered_coords2, matches)
show()

在运行过程中出现了如下错误，目前不知道该怎么解决，请大佬们帮忙

[BunryIce]

请各位大佬帮帮我啊 实在不知道怎么回事啊