突如奇來的高科技電子零件

從公司的垃圾箱找到一個高科技電子零件

有LCD Screen, mini USB port, 4個 buttons

回家就著手將這個新玩具解體



4個buttons 的功能():
1.選擇+
2. 確定
3.選擇-
4.ReBoot

當device 與 mini USB, 連接後 一個相片photo upload software(DPFMate.exe)會自動打開

 打開device 的drive發現幾個file


包括autorun(真是一個超危險的傢伙)在內有4個file, 1個folder.
但是沒有一個存放相片的folder

暫時來看 把它改成其他用途要花的功夫應該不太大

先把 DPFMate.exe 和 MacDPFmate.zip 研究一下再下結論

留言

發佈留言

此網誌的熱門文章

[OpenCV] RAW rgb data to IplImage | 以rgb原始資料建立IplImage指標

Sometime we may only got rgb data from source, so we have to build valid IplImage pointer. This sample shows that how to change rgb data to IplImage. 有時我們只會收到rgb資料，所以要自己建立有效的IplImage，以下是將rgb資料轉成IplImage。 VARIABLE DEFINITION 變量定義 rgbtexture    raw rgb data get from the camera | 由視訊傳來的rgb原始資料 cpimg          IplImage to store the RAW rgb data | 用來存rgb原始資料的IplImage變量 arr                simple opencv data format | 基本的opencv的資料格式 According  to IplImage definition | 根據IplImage的定義 typedef struct _IplImage {     int  nSize;             /* sizeof(IplImage) */     int  ID;                /* version (=0)*/     int  nChannels;    /* Most of OpenCV functions support 1,2,3 or 4 channels */     int  alphaChannel;      /* Ignored by OpenCV */     int  depth;             /* Pixel depth in bits: IPL_DEPTH_8U, IPL_DEPTH_8S,                       IPL_DEPTH_16S,IPL_DEPTH_32S, IPL_DEPTH_32F and IPL_DEPTH_64F are supported.  */     char colorModel[4];     /* Ignored by OpenCV */    
閱讀更多

Monitoring System Spec.& IO Mapping

This is the sophie SEM2012 Monitoring System Spec.& IO Mapping sheet I/O Number of I/O Measure point Solar panel 6 VI Converter 3 VI Battery 1 VI Motor driver 1 VI Motor 1 V, speed( by reed switch ) Total 12 23+1 Arduino Number of Analog I/O Mega2560 16 X2 Total Mega2560 x2 32 Because of Arduino x2, need 2 analog I/O for I2C communication Total Analog I/O used Number of analog I/O 27+1 32 Radio Frequency Features ( data rate ) 4800bps -> 600Bps ->75chars ps 1 point of measurement( e.g. 15.34 ) = 4 digits + dot + space = 6 chars Total Measurement (chars) Data to stream (chars) 2
閱讀更多

face detection | 臉部偵測

This is the basic face detection method provided by OpenCV. The algorithm behind is Haar-like feature*. The database (haarcascade_frontalface_alt2.xml) that is needed is in the opencv directory that you installed. This database only can detect front face. Flow: 1. load database(.xml) -> 2. cvHaarDetectObjects() detect face -> 3. receive data in cvrect format 這裡的臉部偵測是用OpenCV提供的基本功能。演算法是哈爾特徵*，數據庫(haarcascade_frontalface_alt2.xml)在安裝opencv的位置內。 流程： 1. 讀入數據庫(.xml) -> 2. 用cvHaarDetectObjects()辯認臉部 -> 3. 以cvrect接收位置 1. OpenCV provide function to read in database, if data read in is failed, cvLoad will return 0, so we can use if(!cascade) to check. 讀入數據庫的話可以直接使用OpenCV函式，如果讀入不成功的話 cvLoad 會歸還 0， 所以可以用if(!cascade)檢查。 CvHaarClassifierCascade *cascade=NULL; cascade = (CvHaarClassifierCascade*)cvLoad( CASCADEPATH, 0, 0, 0 ); if (!cascade)      exit(0); 2. if cascade successfully loaded in, we can load our source, after that call cvHaarDetectObjects(), remem
閱讀更多