So instead, you overlay an image with your site's contact information that covers any detected text in the uploaded images. It makes a good face for advertising that needs a 'typewriter' or obvious 'computer' look.
OCR-B is still the face that many OCR readers are happiest with. For revenue recognition purposes, it's important that the listings do not display private phone numbers or those of other real estate organizations. OCR-B was subsequently designed as a standard typeface that would be adequately readable by both human and machine. To do this, just add the fl_region_relative flag to your transformation, and specify the width of the overlay image as a percentage (1.0 = 100%) of the text element.įor example, suppose you run a real estate website where individuals or companies can list homes for sale. The relative width adjusts the size of the overlay image relative to the size of the detected text element. In most cases, it works best to specify a relative width instead of an absolute width for the overlay. When you specify ocr_text as the gravity, each detected text element is automatically covered with the specified image. Overlaying an image based on OCR text detection is similar to the process for overlaying images in other scenarios: you specify the image to overlay, the width of the overlay, and the gravity (location) for the overlay. When blurring or pixelating to hide content, you may want to take advantage of one of the access control options to prevent users from accessing the non-blurred or non-pixelated versions of the image.
The following example uses the normal mode of the OCR add-on to pixelate the license plate text in this car photograph: If you expect images to include non-latin characters, you can instruct the add-on to analyze the image for a specific language. You can use the add-on in normal mode for capturing text elements within a photograph or other graphical image, or in document mode for capturing dense text such as a scan of a document. You can also use the add-on to ensure that important texts aren't cut off when you crop your images. Additionally, you can take advantage of special OCR-based transformations, such as blurring, pixelating, or overlaying other images on all detected text with simple transformation parameters. You can use the extracted text directly for a variety of purposes, such as organizing or tagging images. It extracts all detected text from images, including multi-page documents like TIFFs and PDFs. Set the text to the font you want to use, and save it as font-name.doc. Ive attached a sample doc too, if that helps. Set your line spacing to at least 1.5, and space out the letters by about 1pt.
The OCR Text Detection and Extraction add-on, powered by the Google Vision API, integrates seamlessly with Cloudinary's upload and transformation functionality. This file contains the training text that is used by Tesseract for the included fonts. It offers a rich set of image transformation capabilities, including cropping, overlays, graphic improvements, and a large variety of special effects.