Image quantization with Numpy

March 26, 2024

I wanted to have a look at the example code for image quantization from here
However, it’s rather old and Python and NP have changed since then.

from pylab import imread,imshow,figure,show,subplot
from numpy import reshape,uint8,flipud
from scipy.cluster.vq import kmeans,vq

img = imread('clearsky.jpg')

# reshaping the pixels matrix
pixel = reshape(img,(img.shape[0]*img.shape[1],3))

# performing the clustering
# print(type(pixel))
centroids,_ = kmeans(pixel,6) # six colors will be found
# quantization
qnt,_ = vq(pixel,centroids)

# reshaping the result of the quantization
centers_idx = reshape(qnt,(img.shape[0],img.shape[1]))
clustered = centroids[centers_idx]

figure(1)
subplot(211)
imshow(flipud(img))
subplot(212)
imshow(flipud(clustered))
show()

It’s falling over at line 12 centroids,_ = kmeans(pixel,6)

File "D:\Python30\lib\site-packages\scipy\cluster\vq.py", line 454, in kmeans
book, dist = _kmeans(obs, guess, thresh=thresh)
File "D:\Python30\lib\site-packages\scipy\cluster\vq.py", line 309, in _kmeans
code_book.shape[0])
File "_vq.pyx", line 340, in scipy.cluster._vq.update_cluster_means
TypeError: type other than float or double not supported

I can change 6 to 6.0, but confused as what to do for the NParray passing into kmeans.

What do I need to do to update the code to get the example up and running?

>Solution :

I think you just need to Convert Image Pixels to Floating Point: Before passing the pixels to kmeans, convert them to a floating-point type to ensure compatibility:

import matplotlib.pyplot as plt
import numpy as np
from scipy.cluster.vq import kmeans, vq

# Reading the image
img = plt.imread('clearsky.jpg')

# Convert image pixels to float
pixel = np.reshape(img, (img.shape[0]*img.shape[1], 3)).astype(float)

# Performing the clustering
centroids, _ = kmeans(pixel, 6.0)  # six colors will be found

# Quantization
qnt, _ = vq(pixel, centroids)

# Reshaping the result of the quantization
centers_idx = np.reshape(qnt, (img.shape[0], img.shape[1]))
clustered = centroids[centers_idx.astype(int)]

# Displaying the original and quantized images
plt.figure(figsize=(10, 5))
plt.subplot(121)
plt.imshow(img)
plt.title('Original Image')

plt.subplot(122)
plt.imshow(clustered.astype(np.uint8))
plt.title('Quantized Image')
plt.show()