如何使用 dm 脚本从循环 ROI 中获取信息?
How can I get information from circular ROI using dm script?
在图像中制作圆形 ROI 后,如何使用脚本从该图像区域获取信息(平均值、标准差、方差)?
我可以link用原图在圆形ROI中的位置吗?
不幸的是,这项任务并不像人们希望的那样直接和容易。
虽然脚本支持使用方便的快捷方式将图像操作限制为矩形 ROI(使用 img[]
符号),但对于不规则 ROI 却没有类似的方法。
在这种情况下,必须手动创建 ROI 的二进制掩码并手动执行所需的操作。此 post 底部的示例脚本显示了如何计算不规则 ROI 的平均值。
CreateImageWithROI()
创建一个带有两个 ROI 的测试图像
GetFirstIrregularROIOfImage()
只是 returns 图像的第一个发现的不规则 ROI
GetROIMean()
就是实际例子
命令ROIAddToMask()
用于创建掩码。请注意,还有一个类似的命令可以同时执行图像显示的 all 个 ROI 的操作:ImageDisplayAccumulateROIsToMask()
到目前为止,还不错。
However, it turns out that the newly introduced Circular ROIs do not yet support the mask-creation commands correctly (Tested with GMS 3.1).
相反,他们总是使用 ROI 的边界矩形:
因此有必要退后一步并读取 ROI 的坐标以手动从中创建蒙版。获取 ROI 的边界框并使用椭圆的 icol
和 irow
表达式创建掩码。在下面的示例中:
GetFirstOvalROIOfImage()
只是 returns 图像的第一个找到的椭圆形 ROI
MyAddOvalROIToMask()
是椭圆形 ROIs 的手动掩码创建
示例代码:
image CreateImageWithROI()
{
// Create and show image
number sx = 256, sy = 256
image img := RealImage( "Image", 4, sx, sy )
img = sin( 0.1 * iradius ) * cos( 7 * itheta )
img.ShowImage()
// Create an irregular, closed ROI
ROI myIrRoi = NewROI()
myIrRoi.ROIAddVertex( 0.3 * sx, 0.1 * sy )
myIrRoi.ROIAddVertex( 0.7 * sx, 0.2 * sy )
myIrRoi.ROIAddVertex( 0.5 * sx, 0.6 * sy )
myIrRoi.ROIAddVertex( 0.1 * sx, 0.8 * sy )
myIrRoi.ROISetIsClosed(1)
myIRRoi.ROISetVolatile(0)
// Create an oval ROI
ROI myOvalROI = NewROI()
myOvalROI.ROISetOval( 0.7 * sy, 0.7 * sx, 0.9 * sy, 0.8 * sx )
myOvalROI.ROISetVolatile(0)
// AddROIs
imageDisplay disp = img.ImageGetImageDisplay( 0 )
disp.ImageDisplayAddROI( myIRRoi )
disp.ImageDisplayAddROI( myOvalROI )
return img
}
ROI GetFirstIrregularROIOfImage( image img )
{
if ( img.ImageIsValid() )
{
if ( 0 != img.ImageCountImageDisplays() )
{
imageDisplay disp = img.ImageGetImageDisplay( 0 )
number nRois = disp.ImageDisplayCountROIs()
for ( number i = 0; i < nRois; i++ )
{
ROI testROI = disp.ImageDisplayGetRoi( i )
number isIrregularClosed = 1
isIrregularClosed *= testROI.ROIIsClosed();
isIrregularClosed *= !testROI.ROIIsOval();
isIrregularClosed *= !testROI.ROIIsRectangle();
isIrregularClosed *= ( 2 < testROI.ROICountVertices());
if ( isIrregularClosed )
return testROI
}
}
}
Throw( "No irregular ROI found" )
}
ROI GetFirstOvalROIOfImage( image img )
{
if ( img.ImageIsValid() )
{
if ( 0 != img.ImageCountImageDisplays() )
{
imageDisplay disp = img.ImageGetImageDisplay( 0 )
number nRois = disp.ImageDisplayCountROIs()
for ( number i = 0; i < nRois; i++ )
{
ROI testROI = disp.ImageDisplayGetRoi( i )
if ( testROI.ROIIsOval() )
return testROI
}
}
}
Throw( "No oval ROI found" )
}
void MyAddOvalROIToMask( image img, ROI ovalROI )
{
number top, left, bottom, right
ovalROI.ROIGetOval( top, left, bottom, right )
number sx = ( right - left )
number sy = ( bottom - top )
number cx = sx/2 // Used as both center x coordiante and x radius!
number cy = sy/2 // Used as both center y coordiante and y radius!
// Create mask of just the rect area
image maskCut := RealImage( "", 4, sx, sy )
maskCut = ( ((cx-icol)/cx)**2 + ((cy-irow)/cy)**2 <= 1 ) ? 1 : 0
// Apply mask to image
img[top, left, bottom, right] = maskCut
}
number GetROIMean( image img, ROI theRoi )
{
if ( !img.ImageIsValid() ) Throw( "Invalid image in GetROIMean()" )
if ( !theRoi.ROIIsValid() ) Throw( "Invalid roi in GetROIMean()" )
// Create a binary mask of "img" size using the ROI's coordinates
image mask = img * 0; // image of same size as "img" with 0 values
number sx, sy
img.GetSize( sx, sy )
// Oval ROIs are not supported by the command correctly
// Hence check and compute mask manually..
if ( theROI.ROIIsOval() )
MyAddOvalROIToMask( mask, theROI )
else
theROI.ROIAddToMask( mask, 0, 0, sx, sy )
if ( TwoButtonDialog( "Show mask?", "Yes", "No" ) )
mask.ShowImage()
// Do meanValue as sums of masked points
number maskedPoints = sum( mask )
number maskedSum
if ( 0 < maskedPoints )
maskedSum = sum( mask * img ) / maskedPoints
else
maskedSum = sum( img )
return maskedSum
}
Result( "\n Testing irregular and oval ROIs on image.\n" )
image testImg := CreateImageWithROI()
ROI testROIir = GetFirstIrregularROIOfImage( testImg )
number ROIirMean = GetROIMean( testImg, testROIir )
Result( "\n Mean value (irregular ROI): "+ ROIirMean )
ROI testROIoval = GetFirstOvalROIOfImage( testImg )
number ROIovalMean = GetROIMean( testImg, testROIoval )
Result( "\n Mean value (oval ROI) : "+ ROIovalMean )
在图像中制作圆形 ROI 后,如何使用脚本从该图像区域获取信息(平均值、标准差、方差)?
我可以link用原图在圆形ROI中的位置吗?
不幸的是,这项任务并不像人们希望的那样直接和容易。
虽然脚本支持使用方便的快捷方式将图像操作限制为矩形 ROI(使用 img[]
符号),但对于不规则 ROI 却没有类似的方法。
在这种情况下,必须手动创建 ROI 的二进制掩码并手动执行所需的操作。此 post 底部的示例脚本显示了如何计算不规则 ROI 的平均值。
CreateImageWithROI()
创建一个带有两个 ROI 的测试图像GetFirstIrregularROIOfImage()
只是 returns 图像的第一个发现的不规则 ROIGetROIMean()
就是实际例子
命令ROIAddToMask()
用于创建掩码。请注意,还有一个类似的命令可以同时执行图像显示的 all 个 ROI 的操作:ImageDisplayAccumulateROIsToMask()
到目前为止,还不错。
However, it turns out that the newly introduced Circular ROIs do not yet support the mask-creation commands correctly (Tested with GMS 3.1).
相反,他们总是使用 ROI 的边界矩形:
因此有必要退后一步并读取 ROI 的坐标以手动从中创建蒙版。获取 ROI 的边界框并使用椭圆的 icol
和 irow
表达式创建掩码。在下面的示例中:
GetFirstOvalROIOfImage()
只是 returns 图像的第一个找到的椭圆形 ROIMyAddOvalROIToMask()
是椭圆形 ROIs 的手动掩码创建
示例代码:
image CreateImageWithROI()
{
// Create and show image
number sx = 256, sy = 256
image img := RealImage( "Image", 4, sx, sy )
img = sin( 0.1 * iradius ) * cos( 7 * itheta )
img.ShowImage()
// Create an irregular, closed ROI
ROI myIrRoi = NewROI()
myIrRoi.ROIAddVertex( 0.3 * sx, 0.1 * sy )
myIrRoi.ROIAddVertex( 0.7 * sx, 0.2 * sy )
myIrRoi.ROIAddVertex( 0.5 * sx, 0.6 * sy )
myIrRoi.ROIAddVertex( 0.1 * sx, 0.8 * sy )
myIrRoi.ROISetIsClosed(1)
myIRRoi.ROISetVolatile(0)
// Create an oval ROI
ROI myOvalROI = NewROI()
myOvalROI.ROISetOval( 0.7 * sy, 0.7 * sx, 0.9 * sy, 0.8 * sx )
myOvalROI.ROISetVolatile(0)
// AddROIs
imageDisplay disp = img.ImageGetImageDisplay( 0 )
disp.ImageDisplayAddROI( myIRRoi )
disp.ImageDisplayAddROI( myOvalROI )
return img
}
ROI GetFirstIrregularROIOfImage( image img )
{
if ( img.ImageIsValid() )
{
if ( 0 != img.ImageCountImageDisplays() )
{
imageDisplay disp = img.ImageGetImageDisplay( 0 )
number nRois = disp.ImageDisplayCountROIs()
for ( number i = 0; i < nRois; i++ )
{
ROI testROI = disp.ImageDisplayGetRoi( i )
number isIrregularClosed = 1
isIrregularClosed *= testROI.ROIIsClosed();
isIrregularClosed *= !testROI.ROIIsOval();
isIrregularClosed *= !testROI.ROIIsRectangle();
isIrregularClosed *= ( 2 < testROI.ROICountVertices());
if ( isIrregularClosed )
return testROI
}
}
}
Throw( "No irregular ROI found" )
}
ROI GetFirstOvalROIOfImage( image img )
{
if ( img.ImageIsValid() )
{
if ( 0 != img.ImageCountImageDisplays() )
{
imageDisplay disp = img.ImageGetImageDisplay( 0 )
number nRois = disp.ImageDisplayCountROIs()
for ( number i = 0; i < nRois; i++ )
{
ROI testROI = disp.ImageDisplayGetRoi( i )
if ( testROI.ROIIsOval() )
return testROI
}
}
}
Throw( "No oval ROI found" )
}
void MyAddOvalROIToMask( image img, ROI ovalROI )
{
number top, left, bottom, right
ovalROI.ROIGetOval( top, left, bottom, right )
number sx = ( right - left )
number sy = ( bottom - top )
number cx = sx/2 // Used as both center x coordiante and x radius!
number cy = sy/2 // Used as both center y coordiante and y radius!
// Create mask of just the rect area
image maskCut := RealImage( "", 4, sx, sy )
maskCut = ( ((cx-icol)/cx)**2 + ((cy-irow)/cy)**2 <= 1 ) ? 1 : 0
// Apply mask to image
img[top, left, bottom, right] = maskCut
}
number GetROIMean( image img, ROI theRoi )
{
if ( !img.ImageIsValid() ) Throw( "Invalid image in GetROIMean()" )
if ( !theRoi.ROIIsValid() ) Throw( "Invalid roi in GetROIMean()" )
// Create a binary mask of "img" size using the ROI's coordinates
image mask = img * 0; // image of same size as "img" with 0 values
number sx, sy
img.GetSize( sx, sy )
// Oval ROIs are not supported by the command correctly
// Hence check and compute mask manually..
if ( theROI.ROIIsOval() )
MyAddOvalROIToMask( mask, theROI )
else
theROI.ROIAddToMask( mask, 0, 0, sx, sy )
if ( TwoButtonDialog( "Show mask?", "Yes", "No" ) )
mask.ShowImage()
// Do meanValue as sums of masked points
number maskedPoints = sum( mask )
number maskedSum
if ( 0 < maskedPoints )
maskedSum = sum( mask * img ) / maskedPoints
else
maskedSum = sum( img )
return maskedSum
}
Result( "\n Testing irregular and oval ROIs on image.\n" )
image testImg := CreateImageWithROI()
ROI testROIir = GetFirstIrregularROIOfImage( testImg )
number ROIirMean = GetROIMean( testImg, testROIir )
Result( "\n Mean value (irregular ROI): "+ ROIirMean )
ROI testROIoval = GetFirstOvalROIOfImage( testImg )
number ROIovalMean = GetROIMean( testImg, testROIoval )
Result( "\n Mean value (oval ROI) : "+ ROIovalMean )