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Where can I find the numeric value for GenICam standard pixel formats?

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I'm trying to set up a case structure for reconstructing image formats in IMAQdx using the pixel format as output. Confirmed that the U32 numeric "Pixel Format" property in IMAQdx id consistent from camera to camera, but it's just a number, and I can only see the number for image formats used by the cameras I have (I need to code for other formats I haven't seen yet). The GenICam standard 1.1 provides support for 52 image formats, and presumably IMAQdx has a corresponding U32 value for each format. Where can I find this list? The .pdf for the GenICam standard only lists the available formats by name, and doesn't give a corresponding numeric value.
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Accepted by topic author Nasgul

Hi Nasgul,

 

The "PixelFormat" attribute is actually an enumeration consisting of name/value pairs. For GenICam cameras (such as GigE Vision) these names and values are determined by the camera's XML file, not IMAQdx. The names themselves are standardized by the "Standard Features Naming Convention" portion of GenICam (but their values are not).

 

I think you are referring to the Pixel Format property node. I think you are right that this is a numeric. This is likely because the available modes cannot be known before you actually run the code and LabVIEW enumeration values must be known at edit time, not compile time. The node itself as a numeric is likely there as a relic of the firewire interface. It would likely be more useful as a string I'd imagine.

 

You probably want to use the generic way of manipulating attributes instead. You first set the "Active Attribute" property to "PixelFormat" and then you can then query a list of available name/value pairs or simply set the value. IMAQdx lets you set the value directly as a string (using the standard names) rather than ever having to translate it to a numeric value.

 

Eric 

 

 

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The active attribute "PixelFormat" was the answer. I get a string with the pixel format output of the camera, which I can then feed to my case structure and reconstruct the image using the proper algorithm. Thanks!
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