I am attempting to read a 4-band (red, green, blue, near-infrared) geotiff (example data) and perform a quickshift segmentation using the scikit-image
module in Python.
I have created the following script (based on the scikit example):
from __future__ import print_function
from osgeo import gdal
import matplotlib.pyplot as plt
import numpy as np
from skimage.segmentation import felzenszwalb, slic, quickshift
from skimage.segmentation import mark_boundaries
from skimage.util import img_as_float
image = r'C:\path\to\my\geotiff.tif'
img = io.imread(image, as_grey=False, plugin="gdal")
segments_quick = quickshift(img, kernel_size=3, max_dist=6, ratio=0.5)
I get the following error:
ValueError: the input array must be have a shape == (.., ..,[ ..,] 3)), got (4, 436, 553)
I am pretty sure the numpy array needs to be reshaped somehow. How can I properly read the multiband geotiff into a numpy array and perform the image segmentation?
I believe your problem is that quickshift()
thinks your image is rgb
. I downloaded a random image from the link you provided and read it into skimage.
img = io.imread('./m_4111722_ne_11_1_20100704.tif')
I resized it to 128x128x4 (to make computation easy)
img = transform.resize(img, (128, 128, 4))
then ran quickshift()
segments = quickshift(img, kernel_size=3, max_dist=6, ratio=0.5)
and got the same error.
ValueError: the input array must be have a shape == (.., ..,[ ..,] 3)), got (128, 128, 4)
Higher up in the stack trace it says
skimage/segmentation/_quickshift.pyx inskimage.segmentation._quickshift.\
quickshift (skimage/segmentation/_quickshift.c:1710)()
/****/****/anaconda/lib/python2.7/site-packages/skimage/color/colorconv.pyc in rgb2lab(rgb)
901 This function uses rgb2xyz and xyz2lab.
902 """
--> 903 return xyz2lab(rgb2xyz(rgb))
So you can see _quickshift.pyx
is trying to convert rgb --> xyz
and then xyz --> lab
. So its assuming your image is rgb
. The skimage docs for quickshift()
shows it has a flag convert2lab
that defaults to True
.
convert2lab : bool, optional (default True) Whether the input should be converted to Lab colorspace prior to segmentation. For this purpose, the input is assumed to be RGB.
If I re-run your function with that flag set to False
segments = quickshift(img, kernel_size=3, convert2lab=False, max_dist=6, ratio=0.5)
it runs.
plt.imshow(segments);
Edit:
Just as an aside, I noticed your image shape is (4, 436, 553)
which is also problematic. skimage
expects the color channel to be last. This can be remedied with
img = img.transpose(1, 2, 0)