Given an `m x n`

`picture`

consisting of black `'B'`

and white `'W'`

pixels, return *the number of black lonely pixels*.

A black lonely pixel is a character `'B'`

that located at a specific position where the same row and same column don't have **any other** black pixels.

**Example 1:**

Input:picture = [["W","W","B"],["W","B","W"],["B","W","W"]]Output:3Explanation:All the three 'B's are black lonely pixels.

**Example 2:**

Input:picture = [["B","B","B"],["B","B","B"],["B","B","B"]]Output:0

**Constraints:**

`m == picture.length`

`n == picture[i].length`

`1 <= m, n <= 500`

`picture[i][j]`

is`'W'`

or`'B'`

.

```
struct Solution;
impl Solution {
fn find_lonely_pixel(pictures: Vec<Vec<char>>) -> i32 {
let n = pictures.len();
let m = pictures[0].len();
let mut rows = vec![0; n];
let mut cols = vec![0; m];
for i in 0..n {
for j in 0..m {
if pictures[i][j] == 'B' {
rows[i] += 1;
cols[j] += 1;
}
}
}
let mut res = 0;
for i in 0..n {
for j in 0..m {
if pictures[i][j] == 'B' && rows[i] == 1 && cols[j] == 1 {
res += 1;
}
}
}
res
}
}
#[test]
fn test() {
let pictures = vec_vec_char![['W', 'W', 'B'], ['W', 'B', 'W'], ['B', 'W', 'W']];
let res = 3;
assert_eq!(Solution::find_lonely_pixel(pictures), res);
}
```