What is an efficient way of counting groups of ones on 2D grid in python? [Figures below]

Question

I have a few hundred 2D numpy arrays. They contain zeros and ones. A few examples with plots, yellow indicates ones, purple indicates zeros:

grid1=np.array([[1, 1, 0, 0, 1, 1, 0, 0],
               [1, 1, 0, 1, 1, 1, 0, 0],
               [1, 1, 0, 1, 1, 1, 0, 0],
               [1, 0, 0, 0, 1, 0, 0, 0],
               [0, 0, 0, 0, 0, 0, 0, 0]])

plt.imshow(grid1)

grid2=np.array([[1, 1, 0, 0, 0, 0, 0, 0],
               [1, 1, 1, 1, 1, 0, 0, 0],
               [1, 1, 1, 1, 1, 0, 0, 0],
               [1, 0, 0, 1, 1, 0, 0, 0],
               [0, 0, 0, 0, 0, 0, 0, 0]])

plt.imshow(grid2)

grid3=np.array([[1, 1, 0, 0, 1, 0, 0, 1],
               [0, 1, 0, 1, 1, 0, 1, 1],
               [0, 1, 0, 1, 1, 0, 0, 0],
               [0, 0, 0, 0, 1, 1, 1, 0],
               [1, 1, 1, 0, 0, 0, 0, 0]])

plt.imshow(grid3)

I'm looking for an efficient way to count the number of yellow blobs on the images. 2, 1 and 4 blobs on the images above, from top to bottom.

Is there an easy way to do this or I have to check each yellow bit to be in the same blob as all the other yellows, and write a script for that? (That looks very painful.)

Answer 1

scipy.ndimage.measurements.label does what you need.