The modular approach allows individual workflows to be used and individual steps to be exchanged. These models refer to the script and are largely independent of the actual language. Recent text recognition is based on recurrent neural networks LSTM and does not require a language model. This makes it possible to train language-independent models for which good recognition results for English, German and French have been shown at the same time. Very good detection rates can be achieved through an appropriate training. This extra effort is particularly worthwhile for difficult documents or scripts that are no longer common today, which are not in the focus of other OCR software.
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Yes, e. Binarization ocropus-nlbin: You can input colorful pictures and the output are a binarized black-white version. Page Segmentation ocropus-gpageseg: You can input a normalized grayscale or black-and-white picture any colorful picture will be automatically transformed to a grayscale picture.
The output are by default black-and-white lines, but with the option --gray it is possible to output also normalized grayscale lines. Text recognition ocropus-rpred: You can use either the binarized lines. Training ocropus-rtrain: You can use either the binarized lines. Tips on the usage: ocropus-rtrain was intended to be used with grayscale, but ocropus-rpred was not.
Grayscale images can be especially useful in cases where binarization leads to a loss of connectedness in glyph shapes. The line normalizer requires binary input. So, there are different options: you can run both recognition and normalization with binary input which is used for both normalization and recognition , you can supply a grayscale image and the library will generate a binary image for normalization, or you can supply both a grayscale and a binary input, in which case the binary input is used for normalization and the grayscale for recognition.
Furthermore, "grayscale" usually means "normalized grayscale", that is, something that looks nearly binary but may have gray pixels around the edges Should I use scans of single pages or can I also use scans of two pages in the same image? It is possible to use scans of two pages in the same image, which will then be handled equivalent as one page with two columns.
However, in most cases it is better to split the double-page into two single page images before continue with the OCR. What exactly is meant by dpi for digital images? The default parameters and settings of OCRopus assume dpi scanned images with black text on white pages and some standard font size 9pt to 14pt.
This is normally the first thing you should check when the recognition quality is not good. Pictures with low resolution or very hight resolution e. ALN is the result of decoding the alignment of the raw output with the ground truth. That is, ALN uses the ground truth. How to avoid the UserWarning: Matplotlib is building the font cache?
This may take a moment. How can the training been speed up? Is it possible to parallelize the training or to use GPU power for training? The training cannot be parallelized or otherwise easily speed up. What is the preferred name of this project? The project was started as OCRopus, then it was mostly used in the lowercase form ocropus and now this repository is simply named ocropy. In the earlier days there used to be a high level repository OCRopus that included other subrepos and contained a top-level driver and build script.
A subset of the tools implemented in Python is the content of this repository which is called ocropy. Nowadays, the names OCRopus, ocropus, and ocropy can be used interchangeable.
Great value for the long term, not just the fixed term.
Plain text has a number of advantages over images of text: you can search it, it can be stored more compactly and it can be reformatted to fit seamlessly into web UIs. The gist is that I found it to be: more transparent about what it was doing. Be strong! Ocropus Ocropus or Ocropy is a collection of tools for extracting text from scanned images.
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