Latex插圖

轉自:https://www.cnblogs.com/neverguveip/p/9457299.html

熟悉latex後真心覺得word好費事,一般latex論文都會有模板,只需要替換把原有內容替換一下,就會生成比較好看的文檔。

廢話不多說,總結一下使用後的體會

1、先說說插圖

        插圖的話,我插入的是".esp"格式。

 

        當然先導包\usepackage{graphicx},

        我把圖片都放在了fig2文件夾中,fig2的文件夾與latex文檔在同一目錄下。

(1) 、插入一張圖片

\begin{figure}[htbp]

\centering

\includegraphics[height=6.0cm,width=9.5cm]{fig2/Xbee.eps}%fig2文件夾下的xbee.esp圖片,

\caption{Campus environment detection system}

\end{figure}

寬度,高度自己調節。

(2)、 並排插入倆張圖片

\begin{figure}[htbp]

\begin{minipage}[t]{0.4\linewidth}

%並排插圖時,線寬很重要,自己慢慢試,倆張圖就不要超過0.5,三張圖不要超過0.33之類的,自己看着辦

\centering

\includegraphics[height=7.5cm,width=2.5cm]{fig2/xitong1.eps}

\caption{Fatiguedetection overview}

\end{minipage}

\hfill%分欄的意思吧

\begin{minipage}[t]{0.5\linewidth}

\centering

\includegraphics[height=7.5cm,width=5.5cm]{fig2/tupianchuli1.eps}

\caption{The imageprocessing}

\end{minipage}

\end{figure}

(3)、並排插入三張圖片,線寬很重要,要不然插不進去

\begin{figure}[htbp]

\begin{minipage}[t]{0.2\linewidth}

\centering

\includegraphics[height=7.5cm,width=2.5cm]{fig2/xitong1.eps}

\caption{Fatigue detection overview}

\end{minipage}

\hfill

\begin{minipage}[t]{0.2\linewidth}

\centering

\includegraphics[height=7.5cm,width=2.5cm]{fig2/tupianchuli1.eps}

\caption{The image processing}

\end{minipage}

\hfill

\begin{minipage}[t]{0.2\linewidth}

\centering

\includegraphics[height=7.5cm,width=2.5cm]{fig2/tupianchuli1.eps}

\caption{The image processing}

\end{minipage}

\end{figure}

(4)、 插入並排子圖

導包 \usepackage{graphicx}和\usepackage{subfigure}

\begin{figure}

\centering

\subfigure[圖1]{

\label{figa} %% label for first subfigure

\includegraphics[width=1.5in]{figs/tupianchuli1.eps}}

\hspace{1in}

\subfigure[圖2]{

\label{fig:subfig:b} %% label for secondsubfigure

\includegraphics[width=1.5in]{figs/tupianchuli1.eps}}

\caption{說明介紹}

\label{figb} %% label for entire figure

\end{figure}

(5)、 並排三張子圖,第一個佔一般空間

\begin{figure}

\centering

\subfigure[]{

\label{fig:a} %% label for first subfigure

\includegraphics[width=2cm]{fig2/Seeed_Stalker3.eps}}

\hspace{1in}%使第一個子圖佔一半空間

\subfigure[]{

\label{fig:subfig:b} %% label for secondsubfigure

\includegraphics[width=2cm]{fig2/temper_humidity_sensor1.eps}}

\subfigure[]{

\label{fig:subfig:c} %% label for secondsubfigure

\includegraphics[width=1.5cm]{fig2/xbee_s1.eps}}

\caption{bingpai}

\label{figb} %% label for entire figure

\end{figure}

5.2 並排三張子圖

\begin{figure}

\centering

\subfigure[]{

\label{fig:a} %% label for first subfigure

\includegraphics[width=2cm]{fig2/Seeed_Stalker3.eps}}

%\hspace{1in}%使第一個子圖佔一半空間

\subfigure[]{

\label{fig:subfig:b} %% label for secondsubfigure

\includegraphics[width=2cm]{fig2/temper_humidity_sensor1.eps}}

\subfigure[]{

\label{fig:subfig:c} %% label for secondsubfigure

\includegraphics[width=1.5cm]{fig2/xbee_s1.eps}}

\caption{bingpai}

\label{figb} %% label for entire figure

\end{figure}

5.3 四張子圖,分行

\begin{figure}

\centering

\subfigure[]{

\label{fig:a} %% label for first subfigure

\includegraphics[width=3cm]{fig2/Seeed_Stalker3.eps}}

%\hspace{1in}%使第一個子圖佔一半空間

\vfill%分行命令

\subfigure[]{

\label{fig:subfig:b} %% label for secondsubfigure

\includegraphics[width=2cm]{fig2/temper_humidity_sensor1.eps}}

\subfigure[]{

\label{fig:subfig:c} %% label for secondsubfigure

\includegraphics[width=2cm]{fig2/xbee_s1.eps}}

\subfigure[]{

\label{fig:a} %% label for first subfigure

\includegraphics[width=1.5cm]{fig2/ESP_01.eps}}

\caption{bingpai}

\label{figb} %% label for entire figure

\end{figure}

6.文本文檔分倆欄

導包\usepackage{multicol}

\begin{multicols}{2}

Viola-Jones algorithm [7] [10] is commonlyused for fast appearance-based detection of different kind of objects. Faceclassifier and eyes classifier are trained by using Haar-like features. TheHaar-like features are the input to the classifier and are specified by theirshapes, position within the region of interest, and the scale (Fig3). Toincrease the accuracy of eye detection, a classifier was used to detect botheyes. When judging the state of the eye, the system will read an image from thevideo, using the Viola-Jones algorithm to mark the face area from the originalimage, as in Fig (4-a) shows, using the same method, and then find out the eyesarea from the facial region, as Fig (4-b) shows. The eyes area will be croppedas a region of interest (ROI), as Fig (4-c) show. The subsequent binaryprocessing of the image and the use of the area ratio to determine the eyesstate will based on the ROI.

\end{multicols}

6.1文本文檔分三欄

\begin{multicols}{3}

。。。。。

\end{multicols}


 

分類: 必備小技能 , Office辦公技能

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