Given a picture consisting of black and white pixels, find the number of black lonely pixels.

The picture is represented by a 2D char array consisting of 'B' and 'W', which means black and white pixels respectively.

A black lonely pixel is character 'B' that located at a specific position where the same row and same column don't have any other black pixels.

Example:

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

Note:

  1. The range of width and height of the input 2D array is [1,500].

给一个只含有黑白像素的图片,找出黑色孤独像素的数量。黑色孤独像素是这个像素所在的行和列都不含有黑色像素。

最基本的想法就是找出每一个黑色像素,然后对相应的行和列进行检查,看是否含有黑色像素。但这种方法肯定含有重复操作,效率肯定不高。

解法:利用数组rows,cols分别记录某行、某列'B'像素的个数。然后遍历一次picture找到符合条件的。

Java:

public int findLonelyPixel(char[][] picture) {
int n = picture.length, m = picture[0].length; int[] rowCount = new int[n], colCount = new int[m];
for (int i=0;i<n;i++)
for (int j=0;j<m;j++)
if (picture[i][j] == 'B') { rowCount[i]++; colCount[j]++; } int count = 0;
for (int i=0;i<n;i++)
for (int j=0;j<m;j++)
if (picture[i][j] == 'B' && rowCount[i] == 1 && colCount[j] == 1) count++; return count;
}

Java: DFS

public int findLonelyPixel(char[][] picture) {
int numLone = 0;
for (int row = 0; row < picture.length; row++) {
for (int col = 0; col < picture[row].length; col++) {
if (picture[row][col] == 'W') {
continue;
}
if (dfs(picture, row - 1, col, new int[] {-1, 0}) && dfs(picture, row + 1, col, new int[] {1, 0})
&& dfs(picture, row, col - 1, new int[] {0, -1}) && dfs(picture, row, col + 1, new int[] {0, 1})) {
numLone++;
}
}
}
return numLone;
} // use dfs to find if current pixel is lonely
private boolean dfs(char[][] picture, int row, int col, int[] increase) {
// base case
if (row < 0 || row >= picture.length || col < 0 || col >= picture[0].length) {
return true;
} else if (picture[row][col] == 'B') {
return false;
}
// recursion
return dfs(picture, row + increase[0], col + increase[1], increase);
}    

Python:

# Time:  O(m * n)
# Space: O(m + n)
class Solution(object):
def findLonelyPixel(self, picture):
"""
:type picture: List[List[str]]
:rtype: int
"""
rows, cols = [0] * len(picture), [0] * len(picture[0])
for i in xrange(len(picture)):
for j in xrange(len(picture[0])):
if picture[i][j] == 'B':
rows[i] += 1
cols[j] += 1 result = 0
for i in xrange(len(picture)):
if rows[i] == 1:
for j in xrange(len(picture[0])):
result += picture[i][j] == 'B' and cols[j] == 1
return result

Python:

class Solution(object):
def findLonelyPixel(self, picture):
"""
:type picture: List[List[str]]
:type N: int
:rtype: int
"""
return sum(col.count('B') == 1 == picture[col.index('B')].count('B') \
for col in zip(*picture))

Python:

class Solution(object):
def findLonelyPixel(self, picture):
"""
:type picture: List[List[str]]
:rtype: int
"""
w, h = len(picture), len(picture[0])
rows, cols = [0] * w, [0] * h
for x in range(w):
for y in range(h):
if picture[x][y] == 'B':
rows[x] += 1
cols[y] += 1
ans = 0
for x in range(w):
for y in range(h):
if picture[x][y] == 'B':
if rows[x] == 1:
if cols[y] == 1:
ans += 1
return ans  

Python:

class Solution(object):
def findLonelyPixel(self, picture):
""" :type picture: List[List[str]] :rtype: int """
row = self.find_row(picture)
column =self.find_colum(picture) result = 0
for x in row:
for y in column:
if picture[x][y] == "B":
result += 1
return result def find_row(self, picture):
result = []
for x in xrange(len(picture)):
num = 0
for y in xrange(len(picture[x])):
if picture[x][y] == "B":
num += 1
if num == 1:
result.append(x)
return result def find_colum(self, picture):
result = []
for y in xrange(len(picture[0])):
num = 0
for x in xrange(len(picture)):
if picture[x][y] == "B":
num += 1
if num == 1:
result.append(y)
return result  

C++:

class Solution {
public:
int findLonelyPixel(vector<vector<char>>& picture) {
vector<int> rows = vector<int>(picture.size());
vector<int> cols = vector<int>(picture[0].size()); for (int i = 0; i < picture.size(); ++i) {
for (int j = 0; j < picture[0].size(); ++j) {
rows[i] += picture[i][j] == 'B';
cols[j] += picture[i][j] == 'B';
}
} int result = 0;
for (int i = 0; i < picture.size(); ++i) {
if (rows[i] == 1) {
for (int j = 0; j < picture[0].size() && rows[i] > 0; ++j) {
result += picture[i][j] == 'B' && cols[j] == 1;
}
}
}
return result;
}
};

C++:

class Solution {
public:
int findLonelyPixel(vector<vector<char>>& picture) {
if (picture.empty() || picture[0].empty()) return 0;
int m = picture.size(), n = picture[0].size(), res = 0;
vector<int> rowCnt(m, 0), colCnt(n, 0);
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
if (picture[i][j] == 'B') {
++rowCnt[i];
++colCnt[j];
}
}
}
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
if (picture[i][j] == 'B') {
if (rowCnt[i] == 1 && colCnt[j] == 1) {
++res;
}
}
}
}
return res;
}
};

  

  

类似题目:

[LeetCode] 533. Lonely Pixel II 孤独的像素 II  

 

All LeetCode Questions List 题目汇总

 

[LeetCode] 531. Lonely Pixel I 孤独的像素 I的更多相关文章

  1. [LeetCode] 533. Lonely Pixel II 孤独的像素 II

    Given a picture consisting of black and white pixels, and a positive integer N, find the number of b ...

  2. [LeetCode] Lonely Pixel II 孤独的像素之二

    Given a picture consisting of black and white pixels, and a positive integer N, find the number of b ...

  3. [LeetCode] Lonely Pixel I 孤独的像素之一

    Given a picture consisting of black and white pixels, find the number of black lonely pixels. The pi ...

  4. LeetCode 531. Lonely Pixel I

    原题链接在这里:https://leetcode.com/problems/lonely-pixel-i/ 题目: Given a picture consisting of black and wh ...

  5. LeetCode 531. Longly Pixel I (孤独的像素之一) $

    Given a picture consisting of black and white pixels, find the number of black lonely pixels. The pi ...

  6. 531. Lonely Pixel I

    Given a picture consisting of black and white pixels, find the number of black lonely pixels. The pi ...

  7. LeetCode 533. Lonely Pixel II (孤独的像素之二) $

    Given a picture consisting of black and white pixels, and a positive integer N, find the number of b ...

  8. 像素 PIXEL 图片的基本单位 像素非常小 图片是成千上万的像素组成 显示/屏幕分辨率 (DPI 屏幕分辨率)

    像素 PIXEL 图片的基本单位 像素非常小 图片是成千上万的像素组成 显示/屏幕分辨率 (DPI 屏幕分辨率) 图像分辨率 (PPI) 1920*1080是像素点长度1920个像素点 X1080个像 ...

  9. 533. Lonely Pixel II

    Given a picture consisting of black and white pixels, and a positive integer N, find the number of b ...

随机推荐

  1. Python+Appium学习之启动手机APP或者浏览器

    一.启动浏览器:pycharm中python脚本如下: from appium import webdriver desired_caps ={ 'platformName':'Android', ' ...

  2. APP测试之MONKEY安装、使用

    1.先下载java的jdk;配置java变量 安装好之后会有两个文件夹一个是jdk 一个是jre(运行)然后配置好java环境变量:JAVA_HOME:C:\Program Files\Java\jd ...

  3. NOIP2019 PJ 对称二叉树

    题目描述 一棵有点权的有根树如果满足以下条件,则被轩轩称为对称二叉树: 二叉树: 将这棵树所有节点的左右子树交换,新树和原树对应位置的结构相同且点权相等. 下图中节点内的数字为权值,节点外的 id 表 ...

  4. JAVA添加WORD文档批注

    本文将介绍在Java程序中如何给Word文档中的指定字符串添加批注.前文中,主要介绍的是针对某个段落来添加批注,以及回复.编辑.删除批注的方法,如果需要针对特定关键词或指定字符串来设置批注,可以参考本 ...

  5. 求x,y中的最大值

    分析: 输入——变量x,y存放输入的两个整数: 输出——变量m存放输入的两个整数的最大值,m为输出: 算法——如果x比y大,x赋给m,否则y赋给m. #include<stdio.h>vo ...

  6. 学习Spring-Data-Jpa(十七)---对Web模块的支持

    Spring-Data还提供了Web模块的支持,这要求Web组件Spring-MVC的jar包位于classpath下.通常通过使用@EnableSpringDataWebSupport注解来启用继承 ...

  7. [Javascript] Window.matchMedia()

    window.matchMedia() allow to listen to browser window size changes and trigger the callback for diff ...

  8. 20199302《Linux内核原理与分析》第十二周作业

    ShellShock攻击实验 什么是ShellShock? Shellshock,又称Bashdoor,是在Unix中广泛使用的Bash shell中的一个安全漏洞,首次于2014年9月24日公开.许 ...

  9. 【区间dp】P1063 能量项链

    一道区间dp的水题 题目链接 来快活啊! 思路 很简单的区间dp,思路和floyed差不多,就是需要把项链处理成环形 用\(f[l][r]\)表示以\(a[l]\)开头\(a[r]\)结尾的数串的最大 ...

  10. Codeforces & Atcoder神仙题做题记录

    鉴于Codeforces和atcoder上有很多神题,即使发呆了一整节数学课也是肝不出来,所以就记录一下. AGC033B LRUD Game 只要横坐标或者纵坐标超出范围就可以,所以我们只用看其中一 ...