ValueError While Clustering in Sklearn

Question

I have a RGB image of the following shape ((3L, 5L, 5L). It means 5 by 5 pixels image having 3 layers (R,G,andB).I want to cluster it using DBSCAN algorithm as follows. But I got an error message that ValueError: Found array with dim 3. Expected <= 2. Can not I use for my 3d image?

import numpy as np
from sklearn.cluster import DBSCAN
from collections import Counter

data = np.random.rand(3,5,5)
print np.shape(data)
print data

db = DBSCAN(eps=0.12, min_samples=3).fit(data)
print db
DBSCAN(algorithm='auto', eps=0.12, leaf_size=30, metric='euclidean',
    min_samples=1, p=None, random_state=None)
labels = db.labels_

print Counter(labels)

If you look at the documentation: X : array or sparse (CSR) matrix of shape (n_samples, n_features), or array of shape (n_samples, n_samples) — Moritz
– Moritz, Commented Aug 17, 2015 at 6:08
@yangjie I have no idea. Do you mean distance between two pixels over the channel (voxel)? — Roman
– Roman, Commented Aug 17, 2015 at 12:54

Andreas Mueller · Accepted Answer · 2015-08-17 14:31:54Z

2

To cluster you need to say what the distance between two points is. DBSCAN is not a graph clustering algorithm, it works with features. You need to represent each pixel as features, so that the distances are appropriate.

The features could just be RGB, in which case similar colors are clustered together. Or the features could also include x, y coordinates, which would mean spacial distances are also considered.

If you want to consider spatial distances, I'd suggest you take a look at scikit-image's segmentation module, which contains a couple of popular image segmentation methods.

answered Aug 17, 2015 at 14:31

Andreas Mueller

28.9k8 gold badges65 silver badges78 bronze badges

Sign up to request clarification or add additional context in comments.

2 Comments

Roman Over a year ago

So, yes RGB are the features, and x,y coordinates are the spatial distances. I have to cluster the data, i.e., RGB channel values with respect to the x,y coordinates. This means, the nearer the RGB values, the nearer the x,y coordinates, i.e., they would fall into one same cluster. In this case, does not DBSCAN work?

Andreas Mueller Over a year ago

It can work but you need to put all your data in to a 2d array where each row is one pixel and the first three columns are the RGB values and the next two columns are the x and y values. (and you probably need to multiply either of them by some value to get them to the same order of magnitude).

Collectives™ on Stack Overflow

ValueError While Clustering in Sklearn

1 Answer 1

2 Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

2 Comments

Your Answer

Sign up or log in

Post as a guest

Related