April 2020
Intermediate to advanced
438 pages
12h 2m
English
Content preview from Python Image Processing Cookbook
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How it works...
Running a forward pass on the pretrained EAST model returns scores and geometry that are decoded using the decode_predictions() function to obtain the bounding boxes (ROIs) predicted to be containing text. Next, the texts inside these ROIs are to be extracted with the pytesseract image_to_string() method.
To extract texts as strings using Tesseract v4 OCR, the command-line arguments are needed to be passed as a configuration to the image_to_string() method of pytesseract (for example, we used "-l eng --oem 1 --psm 11" as the configuration):
- A language (English, configuration)
- An OEM flag=1 (use an LSTM(Long Short-Term Memory) model for OCR)
- An OEM value=11 (treat as sparse text, that is, find as much text as possible in no ...
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