Hi, I'm very impressed with the progress made on scikits since its inception in 2009. I checked out the latest skimage from Git and tried running the HoG code on a non-square image, but it returns an error. Moreover, if I don't convert from RGB to gray, I get a shape mismatch error. In the latter case, a more user-friendly error message would be more informative. Alternatively, you can either convert it to grayscale or compute a gradient image for each channel and for each pixel use the largest. Here is how to reproduce the error: In [1]: import skimage.color In [2]: import skimage.data ** Message: pygobject_register_sinkfunc is deprecated (GstObject) In [3]: import skimage.feature In [4]: I=skimage.data.imread("motorbikes041.png") # see attached In [5]: I2=skimage.color.rgb2gray(I) In [6]: print I2.shape, I2.dtype (150, 200) float64 In [7]: skimage.feature.hog(I2) --------------------------------------------------------------------------- ValueError Traceback (most recent call last) /data/repo/scikits-image/skimage/<ipython console> in <module>() /usr/local/lib/python2.6/dist-packages/scikits_image-0.7dev-py2.6-linux-i686.egg/skimage/feature/hog.pyc in hog(image, orientations, pixels_per_cell, cells_per_block, visualise, normalise) 121 122 orientation_histogram[:, :, i] = uniform_filter(temp_mag, --> 123 size=(cy, cx))[cy / 2::cy, cx / 2::cx] 124 125 # now for each cell, compute the histogram ValueError: shape mismatch: objects cannot be broadcast to a single shape -------------- However, if I select a square subarray, it works fine. In [8]: x=skimage.feature.hog(I2[:128,:128]) Thanks, Damian -- Damian Eads, PhD Research Associate, Machine Intelligence Laboratory Engineering Department, University of Cambridge Trumpington Street, Cambridge, CB2 1PZ, ENGLAND Web: http://mi.eng.cam.ac.uk/~dre25
