pythonnumpyscikit-learncomputer-visionmean-shift

np.reshape(): Converting an image into a feature array based on rgb intensities

I am trying to segment a colour image using the Mean-Shift algorithm using sklearn. I have the following code:

import numpy as np
from sklearn.cluster import MeanShift, estimate_bandwidth
from sklearn.datasets.samples_generator import make_blobs
import matplotlib.pyplot as plt
from itertools import cycle
from PIL import Image

image = Image.open('sample_images/fruit_half.png')
image = np.array(image)

#need to convert image into feature array based on rgb intensities
flat_image = np.reshape(image, [-1,3])

I am trying to convert the image into a feature array based on rgb intensities so that I can do the clustering. However, I get the following error:

ValueError: cannot reshape array of size 3979976 into shape (3)

I am not sure why I am getting this error and how I can resolve this. Any insights are appreciated.

Solution

  • It's because the image you're loading does not have RGB values (if you look at the dimensions, the last one is 4.

    You need to first convert it to RGB like this:

    image = Image.open('sample_images/fruit_half.png').convert('RGB')
image = np.array(image)

# Now it works
flat_image = np.reshape(image, [-1,3])