I can't seem to understand these lines of code. Can someone please explain it to me?

Question

I came accros this piece of code and i cant seem to understand it.

label_seg = np.zeros(img.shape,dtype=np.uint8)
for i in range(mask_labels.shape[0]):
    label_seg[np.all(img == list(mask_labels.iloc[i, [1,2,3]]), axis=-1)] = i
    label_seg = label_seg[:,:,0]

i tried breaking it down but then ive still not come up with any good understanding

Answer 1

My (wild) guess, since your didn't provide an example of input.

This code takes a 3 channels image img (e.g. RGB) and compares it against known colors in a DataFrame mask_labels, then assigns the index of the color in a new array label_seg to identify the matches.

I believe there are some mistakes in the code:

• the last line shouldn't be part of the for loop
• the first row/color of the DataFrame is mapped to 0, which is also the default value in the input.

Example of use:

np.random.seed(0)

img = np.random.randint(0, 255, (5, 5, 3))

mask_labels = pd.DataFrame([[0,  58, 193, 230],
                            [0, 127,  32,  31],
                            [0, 193,   9, 185],
                           ])

# generate an output of the same shape as the input image
label_seg = np.zeros(img.shape, dtype=np.uint8)

# for each row in the DataFrame
for i in range(mask_labels.shape[0]):
    # take the columns 1,2,3
    # if all 3 values match in the img array (same x/y position, all 3 channels)
    # assign the row index in the output array at the same x/y position
    label_seg[np.all(img == list(mask_labels.iloc[i, [1,2,3]]), axis=-1)] = i

label_seg = label_seg[:,:,0]

Output label_seg:

array([[0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0],
       [0, 0, 2, 1, 0],
       [0, 0, 0, 0, 0]], dtype=uint8)

img (as image, each cell is a pixel):

masked_labels:

   0    1    2    3
0  0   58  193  230
1  0  127   32   31
2  0  193    9  185

as colors: