Hey there! I totally get how frustrating it can be when you're trying to train Tesseract for a custom font and hit a roadblock with creating box files—especially as someone new to programming. LabelImg is great for object detection, but it's not built for Tesseract's specific box file format, so that's definitely not the right fit here.

• Tesseract's built-in command line tool
  Don't sleep on the basics! Tesseract can generate a rough box file automatically, which you can then clean up to match your custom font. Run this command in your terminal:
  tesseract your_image.png your_output_file_base batch.nochop makebox
  You can tweak the page segmentation mode (PSM) to get better initial results—use --psm 7 for single-line text or --psm 8 for individual words. Then open the generated .box file in a text editor (like VS Code or Notepad++) to fix misaligned boxes or incorrect character labels. This is perfect for beginners since you don't need extra software beyond Tesseract itself.

• jTessBoxEditor
  This is the go-to GUI tool for Tesseract training workflows. It's specifically designed to handle box files: load your image and auto-generated box file, then visually adjust character bounding boxes, correct labels, and add missing characters. The visual interface makes it way easier to get precise annotations compared to editing text files manually—ideal if you're new to this process.

• LabelStudio (with Tesseract export support)
  If you prefer a modern, web-based interface, LabelStudio works well for annotating text for Tesseract. Set up a text recognition project, import your font images, and annotate characters or lines. You can export your annotations directly in Tesseract's box file format via its built-in features. It's a bit more setup than jTessBoxEditor, but it's great if you're working with larger datasets.

• GImageReader
  This is a lightweight, easy-to-use GUI tool that combines OCR functionality with basic annotation. Load your image, run Tesseract's OCR, then edit the recognized text and adjust bounding boxes right in the interface. You can export the corrected annotations as a box file when you're done. It's perfect for quick, small-scale annotation tasks.

Pro tip: Start with small, clear images (single characters or short lines of your custom font) when you're just starting out. This will make annotation faster and help you get comfortable with the tool before moving to longer text.

内容的提问来源于stack exchange，提问作者Anant Patankar