用整数替换numpy数组中的RGB值非常慢

Question

我想将numpy数组的rgb值替换为单个整数表示.我的代码有效,但速度太慢,我正在迭代每个元素.我可以加快速度吗？我是numpy的新手.

from skimage import io

# dictionary of color codes for my rgb values
_color_codes = {
    (255, 200, 100): 1,
    (223, 219, 212): 2,
    ...
}

# get the corresponding color code for the rgb vector supplied
def replace_rgb_val(rgb_v):
    rgb_triple = (rgb_v[0], rgb_v[1], rgb_v[2])
    if rgb_triple in _color_codes:
        return _color_codes[rgb_triple]
    else:
        return -1

# function to replace, this is where I iterate
def img_array_to_single_val(arr):
    return np.array([[replace_rgb_val(arr[i][j]) for j in range(arr.shape[1])] for i in range(arr.shape[0])])


# my images are square so the shape of the array is (n,n,3)
# I want to change the arrays to (n,n,1)
img_arr = io.imread(filename)
# this takes from ~5-10 seconds, too slow!
result = img_array_to_single_val(img_arr)

Answer 1

反过来替换颜色值.查找每个RGB三元组,并在新数组中设置相应的索引:

def img_array_to_single_val(arr, color_codes):
    result = numpy.ndarray(shape=arr.shape[:2], dtype=int)
    result[:,:] = -1
    for rgb, idx in color_codes.items():
        result[(arr==rgb).all(2)] = idx
    return result

让我们将颜色索引分配分开:首先arr==rgb将每个像素rgb-rgb 值与列表进行比较,得到anxnx 3 - 布尔数组.只有当所有三个颜色部分都相同时,我们才会找到一个匹配,所以.all(2)减少了最后一个轴,True为每个像素匹配提供了焦虑 - 布尔数组rgb.最后一步是,使用此掩码设置相应像素的索引.

更快,可能是,首先将RGB数组转换为int32,然后进行索引转换:

def img_array_to_single_val(image, color_codes):
    image = image.dot(numpy.array([65536, 256, 1], dtype='int32'))
    result = numpy.ndarray(shape=image.shape, dtype=int)
    result[:,:] = -1
    for rgb, idx in color_codes.items():
        rgb = rgb[0] * 65536 + rgb[1] * 256 + rgb[2]
        result[arr==rgb] = idx
    return result

对于非常大或很多图像,您应首先创建直接颜色映射:

color_map = numpy.ndarray(shape=(256*256*256), dtype='int32')
color_map[:] = -1
for rgb, idx in color_codes.items():
    rgb = rgb[0] * 65536 + rgb[1] * 256 + rgb[2]
    color_map[rgb] = idx

def img_array_to_single_val(image, color_map):
    image = image.dot(numpy.array([65536, 256, 1], dtype='int32'))
    return color_map[image]