BinaryKits / BinaryKits.Zpl

BinaryKits.Zpl a set of .net libraries. The project supports you in the simple creation of zebra labels. It generates the ZPL data, it is a printer description language from Zebra Technologies. ZPL II is now emulated by many label printers from different manufacturers. So with this implementation you can create labels for most printers.
MIT License
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Issue with zpl viewer while rendering image #203

Closed VNMishra closed 6 months ago

VNMishra commented 11 months ago

If I add an image to a label and generate the prn file using Zebra Designer. The prn data works perfectly on labelary api but it shows nothing if I try this with BinaryKits Zpl Viewer. For reference below is my ZPL code:

CT~~CD,~CC^~CT~ ^XA ~TA000 ~JSN ^LT0 ^MNW ^MTT ^PON ^PMN ^LH0,0 ^JMA ^PR6,6 ~SD15 ^JUS ^LRN ^CI27 ^PA0,1,1,0 ^XZ ^XA ^MMT ^PW812 ^LL1218 ^LS0 ^FO38,122^GFA,9461,40388,92,:Z64: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:627F ^PQ1,0,1,Y ^XZ

primo-ppcg commented 11 months ago

Your ZPL contains two label definitions, the image is rendered on the second. Passing only the second will work as you expect:

^XA
^MMT
^PW812
^LL1218
^LS0
^FO38,122^GFA,9461,40388,92,:Z64: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:627F
^PQ1,0,1,Y
^XZ
VNMishra commented 11 months ago

Your ZPL contains two label definitions, the image is rendered on the second. Passing only the second will work as you expect:

^XA
^MMT
^PW812
^LL1218
^LS0
^FO38,122^GFA,9461,40388,92,:Z64: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:627F
^PQ1,0,1,Y
^XZ

Hi, Thanks for the response. I am still getting the below error in analyzerInfo.Errors Cannot analyze command ^GFA,9461,40388,92,:Z64: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:627F System.ArgumentOutOfRangeException: StartIndex cannot be less than zero. (Parameter 'startIndex') at System.String.Substring(Int32 startIndex, Int32 length) at BinaryKits.Zpl.Label.Helpers.ZebraHexCompressionHelper.Uncompress(String compressedHexData, Int32 bytesPerRow) at BinaryKits.Zpl.Viewer.CommandAnalyzers.GraphicFieldZplCommandAnalyzer.Analyze(String zplCommand) at System.Linq.Enumerable.WhereSelectListIterator2.MoveNext() at System.Linq.Enumerable.WhereEnumerableIterator1.MoveNext() at System.Collections.Generic.List1.InsertRange(Int32 index, IEnumerable1 collection) at BinaryKits.Zpl.Viewer.ZplAnalyzer.Analyze(String zplData)

primo-ppcg commented 6 months ago

I am still getting the below error in analyzerInfo.Errors

This issue does not appear to be present in the current release. Closing.