As a nice bonus if you pass on an already existing Mat object, which has already allocated the required space for the matrix, this will be reused. While doing this is still a possibility, most of the OpenCV functions will allocate its output data automatically. The first thing you need to know about Mat is that you no longer need to manually allocate its memory and release it as soon as you do not need it. Therefore, unless you are targeting embedded platforms, there's no point to using the old methods (unless you're a masochist programmer and you're asking for trouble). The main downside of the C++ interface is that many embedded development systems at the moment support only C. Therefore, OpenCV 2.0 introduced a new C++ interface which offered a new way of doing things which means you do not need to fiddle with memory management, making your code concise (less to write, to achieve more). The good news is that C++ is fully compatible with C so no compatibility issues can arise from making the change. Luckily C++ came around and introduced the concept of classes making easier for the user through automatic memory management (more or less). While this is not a problem with smaller programs, once your code base grows it will be more of a struggle to handle all this rather than focusing on solving your development goal. It builds on the assumption that the user is responsible for taking care of memory allocation and deallocation. The biggest issue is the manual memory management. The problem with this is that it brings to the table all the minuses of the C language. This is the one you'll see in most of the older tutorials and educational materials. In those days the library was built around a C interface and to store the image in the memory they used a C structure called IplImage. Therefore, the first thing you need to be familiar with is how OpenCV stores and handles images. OpenCV is a computer vision library whose main focus is to process and manipulate this information. How we get and store the pixels values may vary according to our needs, but in the end all images inside a computer world may be reduced to numerical matrices and other information describing the matrix itself. (new example in the above image you can see that the mirror of the car is nothing more than a matrix containing all the intensity values of the pixel points. Open the result for demonstration purposes. To show the result save our msDocxResult into file.įile.WriteAllBytes(outputDocxFile, msDocxResult.ToArray()) Using (MemoryStream msDocxResult = new MemoryStream())ĭc.Save(msDocxResult, new DocxSaveOptions()) Save our document into DOCX format using MemoryStream. (pict.Layout as FloatingLayout).WrappingStyle = WrappingStyle.Tight Pict = new Picture(dc, fl, msPict, PictureFormat.Jpeg) Using (MemoryStream msPict = new MemoryStream(pictBytes)) New VerticalPosition(fromTopMm, LengthUnit.Millimeter, VerticalPositionAnchor.TopMargin), size) Floating layout means that the Picture (or Shape) is positioned by coordinates.įloatingLayout fl = new FloatingLayout(new HorizontalPosition(fromLeftMm, LengthUnit.Millimeter, HorizontalPositionAnchor.Page), Set the picture layout from the (left, top) page corner. LengthUnitConverter.Convert(height, LengthUnit.Millimeter, LengthUnit.Point)) Size size = new Size(LengthUnitConverter.Convert(width, LengthUnit.Millimeter, LengthUnit.Point), Create new Memory Stream, and Picture object for the picture. Using (MemoryStream msDocx = new MemoryStream(inputDocxBytes))ĭc = DocumentCore.Load(msDocx, new DocxLoadOptions()) Create new MemoryStream with DOCX and load it into DocumentCore. Load the input data into memory (from DOCX document and the picture).īyte inputDocxBytes = File.ReadAllBytes(inputFile) īyte pictBytes = File.ReadAllBytes(pictPath) String inputFile = outputDocxFile = outputPdfFile = pictPath = 1. The whole process will be done completely in memory using MemoryStream. We're using files here only to retrieve the data from them and show the results. Public static void AddPictureToDocxInMemory() / How to add picture into an existing DOCX document using MemoryStream.
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