Tesseract Reviews & Product Details

Tesseract is a great library for OCR, though there are different online and paid OCR libraries that do exist, that comes with a hefty cost, which is not affordable by the mid-scale organizations. The alternate is to look for a library that can work locally and is cost-effiecient. Tesseracts serves both the purpose. it's cost efficient and most accurate. Review collected by and hosted on G2.com.

The processing time of tesseract is slow when processing high-resolution large images. This can be reduced by doing some kinds of pre-processing on the image, and also sometimes the tesseract does not give us accurate results. Tesseract should also support the native language. such as Hindi. etc. It is mostly optimized for English characters. Tesseract should enhance the support for multiple languages. Review collected by and hosted on G2.com.

As compared to the other open-sourced OCR engines, tesseract provides a good amount of accuracy in terms of text extraction.

I also explored other OCR engines like Easy OCR,Keras OCR,but among them Tesseract proved to be the best. (Atleast for me) Review collected by and hosted on G2.com.

Working over tabular data is quite a tough task sometimes. Sometimes it completely miss the context of the statements and generates some random words.

Definitely that also depends upon the graphic quality of the documents.

For that I had to work alot in computer vision domain so as to get the documents ready so that the accuracy can be improved.

One additional suggestion that I can give to Tesseract community is that to implement a user friendly dictionary within the Tesseract so that some non tech guy can also use it very easily.

I implemented an additional dictionary where I wrote all the domain specific words so that while extracting text from any document ,I can be able to improve its accuracy.

Some of the computer vision attributes which I used were like Adaptive threshold,warp perspective,contrast .

I also used few libraries for autocorrection of the text which was extracted by the tesseract.

I would suggest tesseract to give out a feature of Domain specific dictionary where user can write some custom words which they believe would be there in the document.

So that while extracting the text atleast those domain specific words can be fetched correctly. Review collected by and hosted on G2.com.

The best thing about Tesseract is the amount of control it gives to users. Even if the base model gives less accurate OCR output, you can improve it by adjusting its parameters. There are a lot of parameters tesseract provides which can be changed in configuration file and if your data follows some kind of patterns, then these really come handy in improving results. Review collected by and hosted on G2.com.

Accuracy. The accuracy of the pre-trained models is less accurate than many other commercially available OCR models. If the images quality and text varies a lot, especially with lot of numerics and fractions, it becomes difficult to get a good accuracy. Second thing I disliked is there are so many parameters that can be adjusted, but use of all the parameters is not very clear. Review collected by and hosted on G2.com.

Tesseract is a powerful open source for ocr. I also have been used tesseract for several years and was happy for scanned document ocr with it. It is easy to use as well as easy installing. Accuracy is also available to use in many and many scanned documents Review collected by and hosted on G2.com.

Its accuracy is a bit low than cloud ocr engine like google visioin api or abbyy ocr api. But I think tesseract 5 version is better than old version and also I think it was improved in new version. So finally that's good for me with tesseract. Review collected by and hosted on G2.com.

The ability of the tool to easily extract text across different languages Review collected by and hosted on G2.com.

Parameter tuning requires a multiple iterations. This is the major drawback while using Tesseract. Other competitors like Microsoft Cognitive OCR and Textract provide easy ways to get optimal results Review collected by and hosted on G2.com.

The optical character recognition of Tesseract is very accurate. It works the best if we first use the Grayscale on it. The response time is also very optimal. Review collected by and hosted on G2.com.

There are non textual things as well on some screenshots, for example the dinosaur on Google Chrome which Tesseract messes up while converting image to text. It converted the dinosaur to number 10 for the chrome internet disconnect picture. So a bit of sanitization is required for the inputs. Review collected by and hosted on G2.com.

Excellent accuracy & the PSM feature makes extraction more accurate. Review collected by and hosted on G2.com.

In some cases, this will not able to extract properly if the document is handwritten. Review collected by and hosted on G2.com.

It makes OCR work really easy. It's open-source software so, can be used in any company without any issue. Review collected by and hosted on G2.com.

The functionalities present in the software, especially the parameters have quite a room for improvement. Review collected by and hosted on G2.com.

As a relatively new Python user, I found tesseract to be easy to use and I was able to get useful results in a short amount of time. Documentation was good and various methods and parameters have been easyt to understand. Review collected by and hosted on G2.com.

It can be a lot of work to pre-process large numbers of images to get them ready for Tesseract to work it's magic. Review collected by and hosted on G2.com.

It's easy to setup, and get it up and running.

Secondly, it is well-maintained by Google. Review collected by and hosted on G2.com.

Tesseract performs poorly in most of the scenarios that I deal with.

It has no support for handwritten text which is a must at this point.

Other research codes trained on very small data are sometimes better than tesseract when concerned with scene text detection. Review collected by and hosted on G2.com.