Textemage

When researching a thesis paper, various sections of materials your work is based on may need referencing for giving credit where it is due. As such, in order to speed up this process, an incredibly advanced Optical Character Recognition model can be used in a handy program known as Textemage that turns pictures with paragraphs into selectable text documents for your convenience.

Running the program’s executable greets users to a straightforward interface, where, after initializing the file picker and navigating to the directory of the image destined to be scanned, the conversion process can be triggered using its dedicated button, thus bypassing the need for extra menus or key presses to make full use of the available functionality. Unlike other command-line utilities, those with mouse-based workflows may find the user experience more palatable here.

Once the app is done with the character recognition, a simple text document is generated in the same folder as the source file so as to avoid tracking it down in a different location. The program has a custom naming scheme that works by adding the “_extracted” keyword at the end of a resulting text file’s title to have an easier time differentiating them while writing your projects.

In terms of improvements, while the app works well enough for its intended purposes, it could use the drag-and-drop ability to quicken workflows for certain users, alongside the option to select multiple items at once for scanning, in order to reduce the selection process for multiple batches of pictures meant to be analyzed. However, given its open-source license, those with programming experience have the opportunity to fork its code and add those features in a different version.

Whether you are dealing with scanned documents meant to be turned into a searchable digital archive, or you wish to extract a certain paragraph from the screenshot of a page with non-selectable text content, Textemage may be the right tool for you, given its fast processing speed and accessible user experience powered by the OCR model.