Tesseractocr Wrapper

Description

CLAMS app wraps around Tesseract OCR to perform OCR on images or video frames.

Input

The wrapper takes a VideoDocument with SWT TimeFrame annotations. The app specifically uses the representative TimePoint annotations from SWT v4 TimeFrame annotations to extract specific frames for OCR

tesseract Structured Output

From the tesseract documentation

The tesseract model returns a dict with pytesseract's image_to_data function

Here is the typical layout:

{'level': [], 'page_num': [], 'block_num': [],’par_num': [], 'line_num': [], 'word_num': [], 'left': [], 'top': [], 'width': [], 'height': [], 'conf': [], 'text': []}

The tesseract wrapper preserves this structured information in the output MMIF by creating lapps Paragraph Sentence and Token annotations corresponding to the Block, Line, and Word from the tesseract output.

User instruction

General user instruction for CLAMS apps is available at CLAMS Apps documentation.

Below is a list of additional information specific to this app.

System requirments

This tool relies on the tesseract ocr engine and the pytesseract python library.

• tesseract

(The container image is built with tesseract-ocr (version 5.3) on Debian Bookworm, see https://packages.debian.org/source/bookworm/tesseract)

• pytesseract
• Requires mmif-python[cv] for the VideoDocument helper functions

Configurable runtime parameter

For the full list of parameters, please refer to the app metadata from CLAMS App Directory or metadata.py file in this repository.