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835\. Image Overlap
Medium
You are given two images, `img1` and `img2`, represented as binary, square matrices of size `n x n`. A binary matrix has only `0`s and `1`s as values.
We **translate** one image however we choose by sliding all the `1` bits left, right, up, and/or down any number of units. We then place it on top of the other image. We can then calculate the **overlap** by counting the number of positions that have a `1` in **both** images.
Note also that a translation does **not** include any kind of rotation. Any `1` bits that are translated outside of the matrix borders are erased.
Return _the largest possible overlap_.
**Example 1:**
![](https://assets.leetcode.com/uploads/2020/09/09/overlap1.jpg)
**Input:** img1 = [[1,1,0],[0,1,0],[0,1,0]], img2 = [[0,0,0],[0,1,1],[0,0,1]]
**Output:** 3
**Explanation:** We translate img1 to right by 1 unit and down by 1 unit. ![](https://assets.leetcode.com/uploads/2020/09/09/overlap_step1.jpg) The number of positions that have a 1 in both images is 3 (shown in red). ![](https://assets.leetcode.com/uploads/2020/09/09/overlap_step2.jpg)
**Example 2:**
**Input:** img1 = [[1]], img2 = [[1]]
**Output:** 1
**Example 3:**
**Input:** img1 = [[0]], img2 = [[0]]
**Output:** 0
**Constraints:**
* `n == img1.length == img1[i].length`
* `n == img2.length == img2[i].length`
* `1 <= n <= 30`
* `img1[i][j]` is either `0` or `1`.
* `img2[i][j]` is either `0` or `1`.
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