To add to this, Tesseract's text recognition of identified lines of text uses a modern approach involving LSTM neural networks, but the text detection process which comes before this uses classical/heuristic (ie. non-ML) approaches which work well on clean-ish document images, but can struggle with photos of documents that have uneven lighting conditions and spotting text in a photo (eg. numberplates in a city scene).

I maintain a JavaScript build of Tesseract with an online demo that you can try with different images: https://robertknight.github.io/tesseract-wasm/