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LSTM: Non-dictionary words with combination of letters and numbers not recognized. #733
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On 22-Feb-2017 9:02 PM, "Amit D." ***@***.***> wrote:
The lstm engine is train on text-lines images. and learns from context, so
it does not surprise me that for a single glyph the OCR accuracy is not so
good.
So, is this another case where legacy engine is better than LSTM?
- excuse the brevity, sent from mobile
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Yes, the legacy engine (
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@zdenop Please label : accuracy. |
Another instance reported in forum, in context of recognizing license plates. Please see https://groups.google.com/forum/?utm_medium=email&utm_source=footer#!topic/tesseract-ocr/qxB-aCa3r6E Test image is |
numbers-dawg has patterns of numbers with punctuation and letters. However currently there is no way to specify patterns such as license plates, VIN, product IDs which are non-dictionary words and random combinations of numbers and letters. Here are the other two images from error reports: Is there a variable which can be set for better accuracy in such cases? |
Another issue, reported in the forum https://groups.google.com/forum/?utm_medium=email&utm_source=footer#!topic/tesseract-ocr/6a6sKOXdZsA I to 1
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Unfortunately, I've fallen into the same pit, is there any solution yet maybe? |
Same problem here |
Hello, do you have datasets somewhere available for testing? |
This thread has been open for 5 years. Has anyone come up with a method for reliably getting tesseract to read a combination of letters and numbers? |
https://groups.google.com/d/msgid/tesseract-ocr/1a3e8773-7151-48f9-92bb-fda888293eab%40googlegroups.com?utm_medium=email&utm_source=footer
Here is link to the test image:
https://03054610326450256607.googlegroups.com/attach/b8b86693ac072/2s.png?part=0.4&view=1
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