Character level recognition gives the same results as the word level recognition.

[Kishlay-notabot]

Tesseract.js version (version number for npm/GitHub release, or specific commit for repo)
Latest release version 5.0.4
Describe the bug
A clear and concise description of what the bug is.
Running Tesseract.js code in 2 different PSM modes gives the same output.
Is tesseract configured to give word level outputs only?
Am I guessing it right that PSMs just refine the recognition scope, but do not affect the output because it will always will be in words?
Running in SINGLE_CHAR and PSM_SINGLE_WORD gives the same output from the same sample.
I want to sort the result character by character and in order to do that, I want the bbox data of each character detected to be extracted, and used further. Is this possible?

Device Version:

• OS + Version: [e.g. iOS8.1, Windows 10] Windows 11
• Browser [e.g. chrome, safari] or Node version [e.g. Node v18] Edge

[Balearica]

Page segmentation mode (PSM) has no impact on the format or level of granularity of the output. Running with PSM SINGLE_WORD tells the Tesseract "I believe the input image contains a single word," and running with SINGLE_CHAR tells Tesseract "I believe the input image contains a single character."

If you want more granular output with character-level bounding boxes, look at the blocks output format.

[Kishlay-notabot]

Thankyou for giving an insight, will close after experimenting

o7