Tesseract

Tesseract has proven to be a versatile solution for a wide range of use cases. Users have successfully utilized the software to extract text from line diagrams and tables in documents, achieving good accuracy by adjusting parameters in the configuration file. Its ability to train OCR models for fine-tuning and adding new characters has greatly improved accuracy and had a significant impact in specific use cases. The ease of training and data creation process has been praised, with the option to auto-create training data from text files in various fonts being a real timesaver.

Integration with automation tools such as autoit and UiPath has allowed organizations to automate processes like digitizing scanned documents and extracting data from PDFs to generate CSV files. Additionally, Tesseract has been found to be particularly useful in extracting text from various sources such as scanned documents, government IDs, truck containers, medical invoices, financial statements, and structured PDF documents written in different languages. Its ability to fetch coordinate level information for each word has provided value for training custom deep learning models for entity extraction and classification.

Moreover, Tesseract's applications extend beyond OCR tasks. It has been employed for document parsing, captcha processing, computer vision, and language conversion. Users have reported that implementing Tesseract has led to improvements within their companies, including increased revenue and efficient data extraction for analytics purposes. For example, its character recognition capabilities have been applied to scans of newspaper articles, assisting in digitizing large volumes of historical texts.