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OpenCV vs Tesseract OCR: What are the differences?
Developers describe OpenCV as "Open Source Computer Vision Library". OpenCV was designed for computational efficiency and with a strong focus on real-time applications. Written in optimized C/C++, the library can take advantage of multi-core processing. Enabled with OpenCL, it can take advantage of the hardware acceleration of the underlying heterogeneous compute platform. On the other hand, Tesseract OCR is detailed as "Tesseract Open Source OCR Engine". Tesseract was originally developed at Hewlett-Packard Laboratories Bristol and at Hewlett-Packard Co, Greeley Colorado between 1985 and 1994, with some more changes made in 1996 to port to Windows, and some C++izing in 1998. In 2005 Tesseract was open sourced by HP. Since 2006 it is developed by Google.
OpenCV belongs to "Image Processing and Management" category of the tech stack, while Tesseract OCR can be primarily classified under "Image Analysis API".
OpenCV and Tesseract OCR are both open source tools. It seems that OpenCV with 36.3K GitHub stars and 26.6K forks on GitHub has more adoption than Tesseract OCR with 28.1K GitHub stars and 5.38K GitHub forks.
Lensley, Plickers, and Suggestic are some of the popular companies that use OpenCV, whereas Tesseract OCR is used by Shelf, ESCHR, and DLabs. OpenCV has a broader approval, being mentioned in 39 company stacks & 39 developers stacks; compared to Tesseract OCR, which is listed in 6 company stacks and 6 developer stacks.
AWS Rekognition has an OCR feature but can recognize only up to 50 words per image, which is a deal-breaker for us. (see my tweet).
Also, we discovered fantastic speed and quality improvements in the 4.x versions of Tesseract. Meanwhile, the quality of AWS Rekognition's OCR remains to be mediocre in comparison.
We run Tesseract serverlessly in AWS Lambda via aws-lambda-tesseract library that we made open-source.
Pros of OpenCV
- Computer Vision36
- Open Source17
- Face Detection9
- Machine Learning9
- Great community6
- Realtime Image Processing4
- Image Augmentation2
- Helping almost CV problem2
Pros of Tesseract OCR
- Building training set is easy4
- Very lightweight library1
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Cons of OpenCV
Cons of Tesseract OCR
- Works best with white background and black text1