OCR-Ops
Project description
ocr-ops
OCR-Ops is infrastructure to perform Optimal Character Recognition (OCR) at scale on a large number of images and videos. Built on top of the algo-ops framework, OCR-Ops is modular and extensible in its data processing operations.
Key Features:
- Supports building an OCRPipeline that can utilize multiple popular OCR annotation methods (e.g. PyTesseract, EasyOCR, etc.) and return the results in structured and efficient fashion within a unified framework.
- Enables multi-levels of information of the OCR application (e.g. text-only, bounding boxes, etc.)
- Allows definition of an image pre-processing pipeline (before OCR) and a text-cleaning pipeline (after OCR) of detected but noisy text to enable optimal and robust OCR performance.
- Supports several nice presets that are plug-and-play for the above purpose!
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
ocr-ops-0.0.0.4.2.tar.gz
(18.7 kB
view hashes)
Built Distribution
Close
Hashes for ocr_ops-0.0.0.4.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5211e3f30afe00e7dc25ed9aa1d83ae9f5c418f0f5ec366805fa6be9dceca084 |
|
MD5 | 0ed1dec38f505762fcbdb412a5263ece |
|
BLAKE2b-256 | 35944516e956322f86b061e06088845c3590ac5b365502f89cd231b8c8dfeeec |