cv2.kmeans usage in Python

Question

I am considering to use OpenCV\'s Kmeans implementation since it says to be faster...

Now I am using package cv2 and function kmeans,

I can not understand the pa

Answer 1

the documentation on this function is almost impossible to find. I wrote the following Python code in a bit of a hurry, but it works on my machine. It generates two multi-variate Gaussian Distributions with different means and then classifies them using cv2.kmeans(). You may refer to this blog post to get some idea of the parameters.

Handle imports:

import cv
import cv2
import numpy as np
import numpy.random as r

Generate some random points and shape them appropriately:

samples = cv.CreateMat(50, 2, cv.CV_32FC1)
random_points = r.multivariate_normal((100,100), np.array([[150,400],[150,150]]), size=(25))
random_points_2 = r.multivariate_normal((300,300), np.array([[150,400],[150,150]]), size=(25))   
samples_list = np.append(random_points, random_points_2).reshape(50,2)  
random_points_list = np.array(samples_list, np.float32) 
samples = cv.fromarray(random_points_list)

Plot the points before and after classification:

blank_image = np.zeros((400,400,3))
blank_image_classified = np.zeros((400,400,3))

for point in random_points_list:
    cv2.circle(blank_image, (int(point[0]),int(point[1])), 1, (0,255,0),-1)

temp, classified_points, means = cv2.kmeans(data=np.asarray(samples), K=2, bestLabels=None,
criteria=(cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_MAX_ITER, 1, 10), attempts=1, 
flags=cv2.KMEANS_RANDOM_CENTERS)   #Let OpenCV choose random centers for the clusters

for point, allocation in zip(random_points_list, classified_points):
    if allocation == 0:
        color = (255,0,0)
    elif allocation == 1:
        color = (0,0,255)
    cv2.circle(blank_image_classified, (int(point[0]),int(point[1])), 1, color,-1)

cv2.imshow("Points", blank_image)
cv2.imshow("Points Classified", blank_image_classified)
cv2.waitKey()

Here you can see the original points:

Here are the points after they have been classified:

I hope that this answer may help you, it is not a complete guide to k-means, but it will at least show you how to pass the parameters to OpenCV.

Answer 2

The problem here is your data_1.transpose is not a numpy array.

OpenCV 2.3.1 and higher python bindings do not take anything except numpy array as image/array parameters. so, data_1.transpose has to be a numpy array.

Generally, all the points in OpenCV are of type numpy.ndarray

eg.

array([[[100., 433.]],
       [[157., 377.]],
       .
       .  
       [[147., 247.]], dtype=float32)

where each element of array is

array([[100., 433.]], dtype=float32)

and the element of that array is

array([100., 433.], dtype=float32)