ls / static_cast(boundingBox.width)) įor (size_t i = 0 i < textLineSizes. A given word, sentence, or paragraph will look like gibberish to an OCR engine if the text is significantly rotated. ![]() ![]() * Calculate the line sizes and overall bounding boxĬv::Size lineSize = cv::getTextSize(line, fontFace, 1, thickness, &baseline) īoundingBox.width = std::max(boundingBox.width, lineSize.width) Ĭonst double scale = std::min(imgROI.rows / static_cast(boundingBox.height), Text orientation refers to the rotation angle of a piece of text in an image. Void ioxp::putText(cv::Mat imgROI, const std::string &text, const int fontFace = cv::FONT_HERSHEY_PLAIN,Ĭonst cv::Scalar color = cv::Scalar::all(255), const int thickness = 1, const int lineType = cv::LINE_8) And for that you need to detect the text, that is: you will need the text mask, where you need to apply the inpainting method. How To Display Images: In pillow we use imgage.show () whereas in OpenCV we use cv2.imshow (NameOFImage, image). 1 Here is simple because it is black on white, and the letters are not bold, so applying a blur there or even a similar white, it will not be seen, but normally you should do inpainting. Image Type Supported: In pillow PIL format & in OpenCV numpy.ndarray type format is preferred. The text is fitted inside the given image, even multiple lines are possible and everything is nicely centered. Method To Open An Image: In pillow we use Image.open (filepath) wherein OpenCV we use cv2.imread (filepath). Here is a wrapper function dealing with all of this for you. Image=imread("C:\\Users\\arjun\\Desktop\\opencv-logo.Using cv::putText is cumbersome and placing your text at the correct position with the correct size is hard. Opencv c++ code for Putting Text on an Image Import necessary packages and configure Pytesseract with the Tesseract engine. Pre-processing: You may need to pre-process the image to. Opencv c++ code for Overlaying a Text on an Image OpenCV: Scene Text Detection Classes Enumerations Functions Scene Text Detection Scene Text Detection and Recognition Detailed Description Class-specific Extremal Regions for Scene Text Detection The scene text detection algorithm described below has been initially proposed by Lukás Neumann & Jiri Matas 187. Load the image: You can use the imread() function in OpenCV to load an image from your computer. See the line for details.īottomLeftOrigin – When true, the image data origin is at the bottom-left corner. Thickness – Thickness of the lines used to draw a text. ![]() One of FONT_HERSHEY_SIMPLEX, FONT_HERSHEY_PLAIN, FONT_HERSHEY_DUPLEX, FONT_HERSHEY_COMPLEX, FONT_HERSHEY_TRIPLEX, FONT_HERSHEY_COMPLEX_SMALL, FONT_HERSHEY_SCRIPT_SIMPLEX, or FONT_HERSHEY_SCRIPT_COMPLEX, where each of the font ID’s can be combined with FONT_ITALIC to get the slanted letters.įontScale – Font scale factor that is multiplied by the font-specific base size. creatememstorage() create the destination. Put Text on Image in OpenCV Python using cv2. Org – Bottom-left corner of the text string in the image.įont – CvFont structure initialized using InitFont().įontFace – Font type. Convert RGB Image to Grayscale Image by Using OpenCV Importer. In Opencv we can put Text on an Image by using putText() function.Ĭ++: void putText(Mat& img, const string& text, Point org, int fontFace, double fontScale, Scalar color, int thickness=1, int lineType=8, bool bottomLeftOrigin=false ) Text detection using OpenCV extremal regions detector (Source: OpenCV project) Unlike manually adjusted image processing code, statistical or probabilistic models learn how to isolate and recognize text from data samples and generalize better on unseen images. Compare OCR accuracy before and after applying our image processing routine. Discover how to apply thresholding, distance transforms, and morphological operations to clean up images. This Opencv C++ Tutorial is about putting Text on an Image In this tutorial, you will: Learn how basic image processing can dramatically improve the accuracy of Tesseract OCR.
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