square_marker_detect.py 文件源码

def get_close_markers(markers,centroids=None, min_distance=20):
    if centroids is None:
        centroids = [m['centroid']for m in markers]
    centroids = np.array(centroids)

    ti = np.triu_indices(centroids.shape[0], 1)
    def full_idx(i):
        #get the pair from condensed matrix index
        #defindend inline because ti changes every time
        return np.array([ti[0][i], ti[1][i]])

    #calculate pairwise distance, return dense distace matrix (upper triangle)
    distances =  pdist(centroids,'euclidean')

    close_pairs = np.where(distances<min_distance)
    return full_idx(close_pairs)