# find_first_non_zero_index()

```kero.ImageProcessing.photoBox.py

def find_first_non_zero_index(mat, row_start=0):
return i, j```
 mat 2D matrix. List of list or numpy array row_start Integer. The value row_start is the index of the row from which this function will start looking for the first non-zero element. This means the function will start searching from the (row_start + 1) row of the matrix. Default to zero, i.e. start searching from the first row. Return i, j The index (i, j) where the matrix has non-zero element, starting from row (row_start)-th index.

Example Usage 1

```import kero.ImageProcessing.photoBox as kip
import numpy as np

# gs_matrix = [
# [1,1,0,0,1 ],
# [1,0,0,1,1 ],
# [1,1,1,0,1 ]
# ]

gs_matrix = np.random.randint(2, size=(5, 10))
print(gs_matrix)

this_i, this_j = kip.find_first_non_zero_index(gs_matrix)
print("first non zero index: ", this_i, this_j)

start_entry = [this_i, this_j]
[row_index, column_index_list, out_mat, liber_mat] = kip.find_segment_index(gs_matrix, start_entry)
print("first segment index: ", row_index, " : ", column_index_list)```

The output:

```[[1 1 0 1 1 1 0 1 1 0]
[0 1 1 1 1 1 1 0 1 1]
[0 0 1 1 0 0 1 1 1 1]
[0 0 1 0 1 0 1 0 0 0]
[1 1 0 0 0 1 0 1 0 1]]
first non zero index: 0 0
first segment index: 0 : [0, 1]```

The first non zero index is bolded in blue.

kero version: 0.4 and above