![]() Keras-ocr provides out-of-the-box OCR models and an end-to-end training pipeline to build new OCR models (see: ). The Implementation Brief overview of Keras-ocr Finally, apply an inpainting algorithm to inpaint the masked areas of the image, resulting in a text-free image, using cv2.Ī representation of the process from an image with text to a text-free image. ![]() For each bounding box, apply a mask to tell the algorithm which part of the image we should inpaint.Identify text in the image and obtain the bounding box coordinates of each text, using Keras-ocr.In order to erase text from images we will go through three steps: Removing text can be useful for a variety or reasons, for example we can use the text-free images for data augmentation as we can now pair the text-free image with a new text.įor this tutorial we will use OCR (Optical Character Recognition) to detect text inside images, and inpainting - the process where missing parts of a photo are filled in to produce a complete image - to remove the text we detected. In this article I will discuss how to quickly remove text from images as a pre-processing step for an image classifier or a multi-modal text and image classifier involving images with text such as memes (for instance the Hateful Memes Challenge by Facebook). Source: image by the author processing an image by morningbirdphoto from Pixabay. An example of before and after removing text using Cv2 and Keras.
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