pyxpose.py 文件源码

def find_a_dominant_color(image):
    # K-mean clustering to find the k most dominant color, from:
    # http://stackoverflow.com/questions/3241929/python-find-dominant-most-common-color-in-an-image
    n_clusters = 5

    # Get image into a workable form
    im = image.copy()
    im = im.resize((150, 150))      # optional, to reduce time
    ar = scipy.misc.fromimage(im)
    im_shape = ar.shape
    ar = ar.reshape(scipy.product(im_shape[:2]), im_shape[2])
    ar = np.float_(ar)

    # Compute clusters
    codes, dist = scipy.cluster.vq.kmeans(ar, n_clusters)
    vecs, dist = scipy.cluster.vq.vq(ar, codes)         # assign codes
    counts, bins = scipy.histogram(vecs, len(codes))    # count occurrences

    # Get the indexes of the most frequent, 2nd most frequent, 3rd, ...
    sorted_idxs = np.argsort(counts)

    # Get the color
    peak = codes[sorted_idxs[1]] # get second most frequent color

    return [int(i) for i in peak.tolist()] # list comprehension to quickly cast everything to int