descriptors.py 文件源码

def gen_codebook(dataset, descriptors, k = 64):
    """
    Generate a k codebook for the dataset.

    Args:
        dataset (Dataset object): An object that stores information about the dataset.
        descriptors (list of integer arrays): The descriptors for every class.
        k (integer): The number of clusters that are going to be calculated.

    Returns:
        list of integer arrays: The k codewords for the dataset.
    """
    iterations = 10
    epsilon = 1.0
    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, iterations, epsilon)
    compactness, labels, centers = cv2.kmeans(descriptors, k , criteria, iterations, cv2.KMEANS_RANDOM_CENTERS)
    return centers