Halcon常用api背诵版
作者：互联网
时间计算
- count_seconds(s1)
- count_seconds(s2)
- Time := (s2-s1) * 1000 //Time单位是ms
循环控制
- for i := 0 to num -1 by 1
- endfor
- while()
- endwhile
- if()
- endif
控制变量赋值
- colors := [ 'red', 'yellow']
- row1 := []
- row2 := [ 323, 2, 3]
- column1 := []
- column2 := [ 32, 23]
- IndexS := []
- IndexE := []
- ModelIDs := []
- singleNums := 12312
- //追加元素
- IndexS := [IndexS, 12]
- //求数组长度
- num := |xjh| 这么做是错误的
- ||只能当作参数来用,比如 for i:= 0 to |xjh| -1 by 1 或者raw:=[raw, 12,|raw|]
图形变量
- //图形变量数组
- gen_empty_obj (Models)
- //追加元素,concat是合并的意思
- concat_obj(Objects1, Objects2 : ObjectsConcat : : )
- concat_obj(Models, xjh ,Models)
- //在Models追加xjh
- gen_empty_obj (EmptyObject)
- read_image(xjh, 'printer_chip/printer_chip_01')
- concat_obj(EmptyObject,xjh,EmptyObject)
- read_image (xjh1, 'printer_chip/printer_chip_02')
- concat_obj (xjh,xjh1,xjh)
- //计算个数
- count_obj()
窗口基本操作
每次新建文件时,最好写出如下操作,先设置好:
- 显示字体
- 填充方式
- 填充颜色
- 线型
- read_image()
- write_image()
- dev_close_window()
- dev_open_window()
- dev_open_window_fit_image()
- get_image_size(Image : : : Width, Height) //获取图像宽高
- dev_resize_window_fit_size()
- set_window_param()
- dev_clear_window()
- dev_set_part() //不修改图片分辨率,修改想要显示的部分
- dev_update_window()
- dev_update_off()
- set_display_font (WindowHandle, 16, 'mono', 'true', 'false')
- dev_update_off ()
- dev_set_draw( 'margin')
- dev_set_color( 'red')
- dev_set_line_width( 1)
画笔颜色,字体等
基本设置
- dev_set_draw(‘margin ') //绘画目标是区域还是轮廓等
- dev_display()
- dev_set_color() //绘制颜色
- dev_set_line_width()
- set_display_font()
- disp_message()
- disp_continue_message()
- write_string() //写字符道窗口
绘制
- set_display_font()
- disp_message()
- disp_continue_message()
- write_string() //写字符道窗口
- //在窗口中制定位置写字符串,
- set_tposition(WindowHandle, 20, 20)
- write_string(WindowHandle, "My string in the WindowHandle" + J$ 'd')
绘制图形,抠图
- gen_circle()
- gen_rectangle1()
- gen_rectangle2()
- area_center()
- //抠图
- reduce_domain(Image, Region : ImageReduced : : )
- gen_image_const() // 空图片
- unino1()
- union2()
阈值/区域/形态学/灰度化/色彩空间转换
- threshold()
- connection()
- select_shape()
- fill_up()
- dilation_circle()
- rgb1_to_gray(Image,grayImage)
- decompose(image,r,g,b)
- trans_from_rgb(image1,image2,image3,h,s,v, 'hsv')
提取区域转换轮廓
- //自动设置shape模版图像和自动分割区域,且创建区域金字塔
- inspect_shape_model (Image, ModelImages, ModelRegions, 1, 30)
- //合并相邻区域,独立不同区域
- connection (ModelRegions, ConnectedRegions)
- //选择目标区域
- select_shape (ConnectedRegions, SelectedRegions, 'area', 'and', 20, 100000)
- //联合需要区域
- union1 (SelectedRegions, ModelRegions)
- //区域骨架转换轮廓
- gen_contours_skeleton_xld (ModelRegions, ModelContours, 1, 'filter')
xld轮廓相关
- fit_line_contour_xld()
- gen_contour_polygon_xld()
- gen_contour_polygon_rounded_xld() //亚像素轮廓
- paint_xld()
- //读取轮廓
- // 参数(输出读取的contours,文件路径,输入dxf文件控制参数名,控制参数值,Dxf文件被读取的状态信息)
- read_contour_xld_dxf (Contours, 'metal-part-' + J$ '02', [], [], DxfStatus)
数学运算
- // 计算标准差,就是看看离散程度,标准差=sqrt(方差)
- StdDevRows := deviation(Rows)
- StdDevCols := deviation(Cols)
- // 弧度
- AngleStart := -rad( 44)
- AngleEnd := -rad( 144)
模版匹配
ncc
- // ncc模版匹配
- /create_ncc_model(Template,输入单通道模版图片
- NumLevels,金字塔层数
- AngleStart, 模版最小旋转角度
- AngleExtent, 模版最大旋转角度
- AngleStep, 模版角度步长
- Metric,匹配算法
- ModelID输出模版模型句柄)
- /
- /find_ncc_model(Image,输入图片
- ModelID, 模版模型句柄
- AngleStart, 匹配旋转其实角度
- AngleExtent, 终止角度
- MinScore, 匹配得分最小值
- NumMatches, 匹配个数 0全要
- MaxOverlap, 最大重叠率 0 -1
- SubPixel, 是否采用亚像素
- NumLevels,使用模版模型中第几层金字塔
- Row, 输出匹配结果的行列坐标角度和得分
- Column, Angle, Score)
- /
- create_ncc_model(Template : : NumLevels, AngleStart, AngleExtent, AngleStep, Metric : ModelID)
- find_ncc_model(Image : : ModelID, AngleStart, AngleExtent, MinScore, NumMatches, MaxOverlap, SubPixel, NumLevels : Row, Column, Angle, Score)
- clear_ncc_model()
- dev_display_ncc_matching_results()
shape
- //主要的算子
- //不带缩放的模版
- create_shape_model()
- /create_scaled_shape_model(Template模版图片,
- NumbLevels模板金字塔层数,= 5
- AngleStart模板最小旋转角度,= 0
- AngleExtent模版旋转范围,= 360
- AngleStep旋转步长, 'auto'
- ScaleMin最小缩放比例,= 0.8
- ScaleMax最大缩放比例,= 1.1
- ScaleStep缩放步长, 'auto'
- Optimization优化方法,= 'none'
- Metric匹配标准,= 'ignore_global_polarity'
- Contrast对比度,= 40
- MinContrast最小对比度,= 10
- ModelID生成的形状模版模型句柄)
- 对比度小一点可能比较容易找到,但是容易带来干扰
- 这个算子会直接把模型坐标放到 0, 0角度调整到 0
- /
- create_scaled_shape_model (ImageReduced, 5, rad( -45), rad( 90), 'auto', 0.8, 1.0, 'auto', 'none', 'ignore_global_polarity', 40, 10, ModelID)
- create_scaled_shape_model()
- get_shape_model_contours() //所有的contours的位置都在0,0和angle:=0处
- find_shape_model()
- //带缩放的算子
- /find_scaled_shape_model(Image输入图片,
- ModelID模型句柄,
- AngleStart旋转初始角度,
- AngleExtent角度范围,
- ScaleMin最小缩放比例,
- ScaleMax最大缩放比例,
- MinScore匹配最小得分,
- NumMatches匹配个数,
- MaxOverlap重叠率,
- SubPixel亚像素级精度,
- NumLevels模版金字塔第几层,
- Greediness贪心度,
- Row, Column, Angle, Scale, Score匹配结果的行列坐标,缩放比例和得分值)
- /
- find_scaled_shape_model()
- clear_shape_model()
- create_aniso_shape_model() // 创建不等比例的模型匹配
- find_aniso_shape_model()
- clear_shape_model()
- //显示模版图片,和各个区域金字塔,层数按NumLevels指定
- //相当于自动求出了各个区域
- inspect_shape_model(Image : ModelImages, ModelRegions : NumLevels, Contrast : )
- //示例
- inspect_shape_model(ImageReduced, ModelImages, ModelRegions, 4, 30)
- // 标准套路
- dev_update_pc( 'off')
- dev_update_window( 'off')
- dev_update_var( 'off')
- read_image(Image, 'green-dot')
- get_image_size(Image, Width, Height)
- dev_close_window()
- dev_open_window( 0, 0, Width, Height, 'black', WindowHandle)
- dev_display(Image)
- dev_set_color( 'red')
- dev_set_draw( 'margin')
- dev_set_line_width ( 1)
- dev_set_colored( 12)
- threshold (Image, Region, 0, 128)
- connection(Region, ConnectedRegions)
- select_shape(ConnectedRegions, SelectedRegions, 'area', 'and', 13000, 16000)
- fill_up(SelectedRegions, RegionFillUp)
- dilation_circle(RegionFillUp, RegionDilation, 3.5)
- reduce_domain(Image, RegionDilation, ImageReduced)
- //create shape-contours model
- /create_scaled_shape_model (ImageReduced, 'auto', rad( 0), rad( 360), 'auto', 0.9, 1.1, 'auto', 'auto', 'use_polarity', 'auto', 'auto', ModelID)
- /
- //注释掉的只能检测出完全的目标,对于只有半个模版形状的目标,无法检测
- create_scaled_shape_model (ImageReduced, 5, rad( -45), rad( 90), 'auto', 0.8, 1.0, 'auto', 'none', 'ignore_global_polarity', 40, 10, ModelID)
- //获取轮廓的目的是为了显示匹配结果
- get_shape_model_contours (Model, ModelID, 1)
- read_image (Image1, 'green-dots')
- find_scaled_shape_model (Image1, ModelID, rad( 0), rad( 360), 0.8, 1.0, 0.5, 0, 0.5, 'least_squares', 5, 0.8, Row, Column, Angle, Scale, Score)
- for J:= 0 to |Score| -1 by 1
- vector_angle_to_rigid ( 0, 0, 0,Row[J], Column[J], Angle[J], HomMat2D)
- affine_trans_contour_xld (Model, ContoursAffineTrans, HomMat2D)
- dev_display (Image1)
- dev_display (ContoursAffineTrans)
- endfor
保存,读取,获得参数
- //读取
- raed_shape_model()
- read_shape_model (ModelFile, ReusedModelID)
- //获得参数
- get_shape_model_contours()
- get_shape_model_origin()
- get_shape_model_params()
- //示例
- get_shape_model_contours (ReusedShapeModel, ReusedModelID, 1)
- get_shape_model_origin (ReusedModelID, ReusedRefPointRow, ReusedRefPointCol)
- get_shape_model_params (ReusedModelID, NumLevels, AngleStart, AngleExtent, AngleStep, ScaleMin, ScaleMax, ScaleStep, Metric, MinContrast)
- //保存
- write_shape_model()
- write_shape_model (ModelID, 'green-dot.shm')
多对多模版匹配
- dev_open_window ( 0, 0, 646, 482, 'black', WindowHandle)
- dev_set_draw ( 'margin')
- Colors := [ 'red', 'green', 'cyan']
- Row1 := [ 135, 150, 185]
- Column1 := [ 250, 170, 220]
- Row2 := [ 375, 310, 335]
- Column2 := [ 355, 395, 375]
- gen_empty_obj (Models)
- IndexS := []
- IndexE := []
- ModelIDs := []
- for J := 1 to 3 by 1
- read_image (Image, 'metal-parts/metal-part-model-' + J$ '02d')
- gen_rectangle1 (Rectangle, Row1[J - 1], Column1[J - 1], Row2[J - 1], Column2[J - 1])
- area_center (Rectangle, Area, Row, Column)
- reduce_domain (Image, Rectangle, ImageReduced)
- inspect_shape_model (Image, ModelImages, ModelRegions, 1, 30)
- connection (ModelRegions, ConnectedRegions)
- select_shape (ConnectedRegions, SelectedRegions, 'area', 'and', 20, 100000)
- union1 (SelectedRegions, ModelRegions)
- gen_contours_skeleton_xld (ModelRegions, ModelContours, 1, 'filter')
- create_shape_model (ImageReduced, 5, rad( 0), rad( 360), 'auto', 'pregeneration', 'use_polarity', 30, 7, ModelID)
- get_shape_model_contours (ModelCont, ModelID, 1)
- select_shape_xld (ModelCont, ModelContours, 'contlength', 'and', 20, 1000)
- count_obj (ModelContours, NumModel)
- count_obj (Models, NumModels)
- concat_obj (Models, ModelContours, Models)
- IndexS := [IndexS,NumModels + 1]
- IndexE := [IndexE,NumModels + NumModel]
- ModelIDs := [ModelIDs,ModelID]
- endfor
- Button := 0
- ImgNo := 1
- while (Button != 1)
- read_image (Image, 'metal-parts/metal-parts-' + ImgNo$ '02d')
- //返回的Row和Column是个数组,完全取决于匹配了几个目标
- find_shape_models (Image, ModelIDs, rad( 0), rad( 360), 0.5, 0, 0.5, 'least_squares', 0, 0.8, Row, Column, Angle, Score, Model)
- //根据匹配的目标个数来进行仿射变换用来显示匹配结果
- Num := |Score|
- for J := 0 to Num - 1 by 1
- copy_obj (Models, ModelSelected, IndexS[Model[J]], IndexE[Model[J]] - IndexS[Model[J]] + 1)
- vector_angle_to_rigid ( 0, 0, 0, Row[J], Column[J], Angle[J], HomMat2D)
- affine_trans_contour_xld (ModelSelected, ModelTrans, HomMat2D)
- dev_set_color (Colors[Model[J]])
- dev_display (ModelTrans)
- endfor
- ImgNo := ImgNo + 1
- if (ImgNo > 15)
- ImgNo := 1
- endif
- endwhile
- for J := 0 to |ModelIDs| - 1 by 1
- clear_shape_model (ModelIDs[J])
- endfor
仿射affine变换
通过点角度到点角度
- //从点和角度计算仿射变换
- /vector_angle_to_rigid(Row1, Column1, Angle1, Row2, Column2, Angle2 : HomMat2D)
- /
- vector_angle_to_rigid() //获得放射矩阵
- //将2维放射矩阵作用到区域中
- affine_trans_region(Region : RegionAffineTrans : HomMat2D, Interpolate : )
通过添加向量方法
直接input想要映射到的位置、角度、缩放量,会自动把对应向量添加到放射矩阵中
- // 平移,旋转,缩放
- // 生成一个齐次变换矩阵
- hom_mat2d_identity (HomMat2DIdentity)
- // 在矩阵中增加平移量
- hom_mat2d_translate (HomMat2DIdentity, Row[I], Column[I], HomMat2DTranslate)
- // 在矩阵中增加角度量
- hom_mat2d_rotate (HomMat2DTranslate, Angle[I], Row[I], Column[I], HomMat2DRotate)
- // 在矩阵中增加缩放量
- hom_mat2d_scale (HomMat2DRotate, Scale[I], Scale[I], Row[I], Column[I], HomMat2DScale)
- //作用到轮廓框架中
- affine_trans_contours_xld()
测量拟合
- // 基于边缘对
- gen_rectangle2()
- gen_measure_reactangle2()
- measure_pairs()
- close_measure()
- // 基于非边缘对
- gen_rectagnle2()
- gen_measure_ractangle2()
- measure_pos()
- close_measure()
- // 弧形测量
- get_points_ellipse()
- gen_measure_arc()
- measure_pos()
- close_measure()
- // 两点距离
- distance_pp()
标签：set,背诵,模版,Image,dev,Halcon,shape,api,model 来源： https://blog.csdn.net/hbspring007/article/details/120427583