reference
ubuntu
注：本人仅在ubuntu上进行了测试
安装
- sudo apt-get install graphviz
在ubuntu16.04上就这样安装好了，从源码上安装失败，少了scan.c，反正能用，所以不管了。
使用
- dot -Tjpg example.dot -oexample.jpg
- example.dot
graph graphname{
a
b
b
d
}
- 指明输出格式为jpg, -Tjpg, 所有输出格式
- 指明输出文件名为example.jpg -oexample.jpg
- example.jpg
- DotEditor: 编辑功能极弱，用法是用别的编辑器进行dot文件编辑，再复制到DotEditor中进行显示。
- [gedit plugin external tool]：自定义功能极强，可结合gedit 的编辑能力，非常好用。在下面的脚本和图示配置下，按
F5即可显示dot图像。
#!/bin/sh
format=jpg
fin=${GEDIT_CURRENT_DOCUMENT_NAME}
fout=${GEDIT_CURRENT_DOCUMENT_NAME}.${format}
touch ${fout}
echo ${fin}
echo ${fout}
dot -T${format} $fin -o${fout} & gnome-open ${fout}
High Level Summary
- for subgraph, the
cluster_i(i=0,1,2,…) is special
- we can use
{...} to set local environment
- set node
node [style=filled,color=lightpink];
- set edge
a->b [label='...']
- use set
{a,b,c}->c; a->{b,c,d}
- set edge direction
edge [dir=both/none/forward/back;penwidth=3] , digraph,graph
- set graph direction
rankdir="TB", "LR", "BT", "RL"
- for
dash,solid... see style at 高级API for style,type and other attributes
- for color
node [style=filled,color=lightyellow]; see color gallery
digraph G {
subgraph Ncluster_0 {
style=filled;
color=lightgrey;
node [style=filled,color=lightgray];
start -> "motion detection" -> "connected component analysis" -> "small area filter" -> "object feature extraction" -> "object association" -> "association graph" -> "find min tree";
class -> "IBGS.process()" -> "icvprCcaByTwoPass()" -> "QYzbxTrackingFeature.getObjectsFromMask()" -> "QYzbxTrackingFeature.getObjects()" -> "TrackingObjectAssociation.adjecentObjectAssociation()" -> "TrackingObjectAssociation.process()" -> "MotionBasedTracker.objectTracking()";
data -> "image:CV_8UC3" -> "mask:CV_8UC1" -> "vector<mask>" -> "vector<ObjectFeature>" -> "list<FrameFeature>" ->"DirectGraph"->"tracking record";
label="2016/08/20: Connected Component Analysis"
}
subgraph Ncluster_1 {
style=filled
color=blue
node [style=filled,color=lightpink];
"motion detection" -> "contour analysis" -> "kalman filter" -> "hungrian algorithm" -> "trakcking result"
data -> "image:CV_8UC3" -> "mask:CV_8UC1" -> "contour:vector<Point>" -> "vector<trackingObjectFeature>" -> "MultiObjectTracker:vector<singleObjectTracker>"
label="2016/08/22: findContour"
}
subgraph Ncluster_2 {
style=filled
color=red
node [style=filled,color=lightyellow];
"motion detection" -> "blob detection" -> "kalman filter" -> "hungrian algorithm" -> "trakcking result"
data -> "image:CV_8UC3" -> "mask:CV_8UC1" -> "blob feature" -> "vector<trackingObjectFeature>" -> "MultiObjectTracker:vector<singleObjectTracker>"
label="2016/08/23: blob detector"
}
}
digraph G{
{node[style=filled,color=lightyellow]
input
"QString:configFile"
"QString:videoFile"
"TrackingStatus*:status"
}
{node[style=filled,color=lightpink]
function
"void:process()"
"void:processOne()"
"vector<trackingObjectFeature>:getObjects()"
"void:Tracking()"
"void:run()"
"void:stop()"
}
{node[style=filled,color=lightblue]
explain
"show tracking result"
"init singleObjectTracker"
"update singleObjectTracker"
}
{"QString:configFile","QString:videoFile"}->"void:process()"
"void:process()"->{"Mat:img_input","Mat:img_foreground","Mat:img_background"}
"void:process()"->"void:processOne()"->"vector<trackingObjectFeature>:getObjects()"->"vector<trackingObjectFeature>"->"void:Tracking()"
"void:Tracking()"->"init singleObjectTracker"->"update singleObjectTracker"[label="kalman and hungrian"]
"void:processOne()"->"show tracking result"
"void:process()"->"void:run()"
{"Mat:img_input","Mat:img_foreground","Mat:img_background","TrackingStatus*:status"}->"void:processOne()"
{edge [dir=both;penwidth=3]
"TrackingStatus*:status"->"TrackingStatus*:globalTrackingStatus"[label="always equal to"]
{"TrackingStatus*:globalTrackingStatus","bool:globalStop"}->"void:run()"
"void:process()"->"TrackingStatus*:status"
}
"void:stop()"->"bool:globalStop"
}
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