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Description: c++ char字符的具体介绍。希望能有一些帮助 我会一步步上传。-introduction on c++ character. Hope it can be of any help. I will upload little by little.
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Size: 2731 |
Author: 张枫 |
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Description: 关于char的一个小程序,用VC编写的,CCP文件
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Size: 710 |
Author: sun |
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Description: powerpc内核mpc8241linux系统下char驱动程序
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Size: 2026668 |
Author: 杨艳锋 |
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Description: c#调用dll时char指针及结构参数的用法-call dll when char pointer and structural parameters of usage
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Size: 2427 |
Author: 狗狗 |
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Description: 簡介Linux的Char driver model,並提供範例
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Size: 1418117 |
Author: vinwangwork@gmail.com |
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Description: 联机数字、英文字符及汉字识别程序源码，做得很不错哟！-online figures, Chinese characters and English characters and source identification procedures done quite well yo!
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Size: 109568 |
Author: 刘英 |
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Description: vxworks char driver
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Size: 20480 |
Author: 林先贤 |
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Description: c#调用dll时char指针及结构参数的用法-call dll when char pointer and structural parameters of usage
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Size: 2048 |
Author: 狗狗 |
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Description: c++ char字符的具体介绍。希望能有一些帮助 我会一步步上传。-introduction on c++ character. Hope it can be of any help. I will upload little by little.
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Size: 2048 |
Author: 张枫 |
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Description: // Canny算子
void Canny(LPBYTE pGray, SIZE sz, double sigma, double dRatLow,
double dRatHigh, LPBYTE pResult)
{
//经过高斯滤波后的图像
LPBYTE pGaussSmooth
pGaussSmooth = new unsigned char[sz.cx*sz.cy]
//x方向导数的指针
int *pGradX
pGradX = new int[sz.cx*sz.cy]
//y方向
int *pGradY
pGradY = new int[sz.cx*sz.cy]
//梯度的幅度
int *pGradMag
pGradMag = new int[sz.cx*sz.cy]
//对原图高斯滤波
GaussianSmooth(sz,pGray,pGaussSmooth,sigma)
//计算方向导数和梯度的幅度
Grad(sz,pGaussSmooth,pGradX,pGradY,pGradMag)
//应用非最大抑制
NonmaxSuppress(pGradMag,pGradX,pGradY,sz,pResult)
//应用Hysteresis，找到所有边界
Hysteresis(pGradMag,sz,dRatLow,dRatHigh,pResult)
delete[] pGradX
pGradX = NULL
delete[] pGradY
pGradY = NULL
-//Canny operator void Canny (LPBYTE pGray. SIZE sz, double sigma, double dRatLow. double dRatHigh. LPBYTE pResult) (//after Gaussian filtering of images LPBYTE pGaussS mooth unsigned pGaussSmooth = new char [sz.cx* sz.cy]// x direction derivative indicators pGradX pGradX int* = new int [ sz.cx* sz.cy]// int* y direction pGradY pGradY = new int [sz.cx* sz.cy]// gradient magnitude int* pGradMag pGradMag = new int [sz.cx* sz.cy]// maximum Gaussian filter to GaussianSmo oth (sz, pGray, pGaussSmooth. sigma)// calculate derivative and the gradient range Grad (sz. pGaussSmooth, pGradX, pGradY. pGradMag)// non-application of the biggest inhibition NonmaxSuppress (pGradMa g, pGradX, pGradY, sz, pResult)// Application Hysteresis, find all border Hysteresis (pGradMag, sz, dRa
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Size: 54272 |
Author: 王学金 |
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Description: Linux 2.4内核字符设备驱动开发实例。
是Linux下驱动开发人员再好不过的参考源码。编译之后加载驱动，附有测试程序进行驱动的测试！
Linux kernel 2.4 char device driver
example.-character device driver development example. Linux is driven development staff a better reference source. After loading compiler- driven, with the testing process-driven test! Linux kernel 2.4 char device driver example.
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Size: 4096 |
Author: |
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Description: 这个是我写的MAX187驱动程序
unsigned char bdata Date,Adss
unsigned char idata point,gew,shw
sbit clk=P1^5
sbit cs187=P1^6
sbit dout=P1^7
sbit Abit=Adss^7
sbit Abit1=Adss^0
sbit Dbit=Date^7
sbit Dbit1=Date^0 -I wrote this is the MAX187 driver unsigned char bdata Dat e, Adss unsigned char idata point, gew. shw sbit clk P1 = ^ = 5 sbit cs187 P1 ^ 6 = P1 sbit dout ^ = 7 sbit Abit Adss sbit Abit1 ^ 7 ^ 0 = Adss sbit Dbi t = Date sbit Dbit1 ^ 7 ^ 0 = Date
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Size: 45056 |
Author: 胡勋 |
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Description: 可以在string, char *, wstring, wchar_t *之间任意转换！-In the string, char*, wstring, wchar_t* conversion between the arbitrary!
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Size: 1024 |
Author: xinshiqing |
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Description: linux char device driver programming
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Size: 20480 |
Author: XD |
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Description: 非常优秀的文字识别程序，基于bp神经网络的，准确率高达99％，下载后修改有什么改进最好能公开给大家学习。-Excellent character recognition process, based on bp neural network, the accuracy rate as high as 99 percent, after downloading any modifications to improve the best we can be open to learning.
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Size: 45056 |
Author: 啊啊 |
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Description: CharAndCString,Char和CString-CharAndCString, Char and CString
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Size: 4187136 |
Author: lijunmin |
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Description: 很完整的51串口程序
包括如下：
串口中断服务程序，仅需做简单调用即可完成串口输入输出的处理
出入均设有缓冲区，大小可任意设置。
可供使用的函数名:
char getbyte(void) 从接收缓冲区取一个byte,如不想等待则在调用前检测inbufsign是否为1。
getline(char idata *line, unsigned char n) 获取一行数据回车结束，必须定义最大输入字符数
putbyte(char c) 放入一个字节到发送缓冲区
putbytes(unsigned char *outplace,j) 放一串数据到发送缓冲区，自定义长度
putstring(unsigned char code *puts) 发送一个定义在程序存储区的字符串到串口
puthex(unsigned char c) 发送一个字节的hex码，分成两个字节发。
putchar(uchar c,uchar j) 输出一个无符号字符数的十进制表示，必须标示小数点的位置,自动删除前面无用的零
putint(uint ui,uchar j) 输出一个无符号整型数的十进制表示，必须标示小数点的位置,自动删除前面无用的零
delay(unsigned char d) 延时n x 100ns
putinbuf(uchar c) 人工输入一个字符到输入缓冲区
CR 发送一个回车换行-err
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Size: 3072 |
Author: eacho |
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Description: Linux下对char device driver的实现以及用户层的测试程序。-A implementation of linux char device driver and its test program from application.
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Size: 2048 |
Author: HelloNet |
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Description: UNICODE下宽字符的CString转换为const char 和char到WCHAR的相互转换-Under the wide character UNICODE CString convert to WCHAR const char and char conversion between
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Size: 2048 |
Author: hillriver |
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Description: # Char-RNN-PyTorch
使用字符级别的RNN进行文本生成，使用PyTorch框架。[Gluon实现]
## Requirements
- PyTorch 0.2
- numpy
## Basic Usage
如果希望训练网络，使用如下的代码
```bash
python main.py \
--state train \
--txt './data/poetry.txt' \ # 训练用的txt文本
--batch 128 \ # batch_size
--epoch 1000 \
--len 100 \ # 输入RNN的序列长度
--max_vocab 5000 \ # 最大的字符数量
--embed 512 \ # 词向量的维度
--hidden 512 \ # 网络的输出维度
--n_layer 2 \ # RNN的层数
--dropout 0.5
```
如果希望使用训练好的网络进行文本生成，使用下面的代码
```bash
python main.py \
--state eval \
--begin '我' \ # 生成文本的开始，可以是一个字符，也可以一段话
--pred_len 100 \ # 希望生成文本的长度
--checkpoint './checkpoint/model_100.pth' # 读取训练模型的位置
```(# Char-RNN-PyTorch
Use the character level RNN for text generation, using the PyTorch framework. [Gluon
## Requirements
- PyTorch 0.2
- numpy
## Basic Usage
If you want to train the network, use the following code
```bash
Python main.py \
--state train \
TXT text --txt'./data/poetry.txt'\ # for training
--batch 128, batch_size #
--epoch 1000 \
The length of the sequence --len 100 \ # input RNN
--max_vocab 5000, # maximum number of characters
--embed 512 \ # word vector dimension
The output dimension --hidden 512 \ # network
--n_layer 2 # \ RNN layers
--dropout 0.5
.
If you want to use a trained network for text generation, use the following code
```bash
Python main.py \
--state Eval \
I \ '--begin' # generated text, can be a character, can also be a paragraph
--pred_len 100, # want to generate text length
--checkpoint'./checkpoint/model_100.pth'# reading training model position
.)
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Size: 1477632 |
Author: 特别的晴天
|
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