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@ -20,7 +20,7 @@
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* [Examples](https://github.com/qurator-spk/eynollah/wiki#examples)
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* [Examples](https://github.com/qurator-spk/eynollah/wiki#examples)
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## Installation
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## Installation
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Python versions `3.8-3.11` with Tensorflow versions >=`2.12` on Linux are currently supported.
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Python versions `3.8-3.11` with Tensorflow version `2.13` on Linux are currently supported.
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For (limited) GPU support the CUDA toolkit needs to be installed.
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For (limited) GPU support the CUDA toolkit needs to be installed.
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@ -52,9 +52,9 @@ The command-line interface can be called like this:
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```sh
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```sh
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eynollah \
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eynollah \
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-i <single image file> | -di <path to directory containing image files> \
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-i <single image file> | -di <directory containing image files> \
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-o <output directory> \
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-o <output directory> \
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-m <path to directory containing model files> \
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-m <directory containing model files> \
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[OPTIONS]
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[OPTIONS]
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```
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```
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@ -71,7 +71,6 @@ The following options can be used to further configure the processing:
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| `-ib` | apply binarization (the resulting image is saved to the output directory) |
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| `-ib` | apply binarization (the resulting image is saved to the output directory) |
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| `-ep` | enable plotting (MUST always be used with `-sl`, `-sd`, `-sa`, `-si` or `-ae`) |
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| `-ep` | enable plotting (MUST always be used with `-sl`, `-sd`, `-sa`, `-si` or `-ae`) |
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| `-ho` | ignore headers for reading order dectection |
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| `-ho` | ignore headers for reading order dectection |
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| `-di <directory>` | process all images in a directory in batch mode |
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| `-si <directory>` | save image regions detected to this directory |
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| `-si <directory>` | save image regions detected to this directory |
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| `-sd <directory>` | save deskewed image to this directory |
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| `-sd <directory>` | save deskewed image to this directory |
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| `-sl <directory>` | save layout prediction as plot to this directory |
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| `-sl <directory>` | save layout prediction as plot to this directory |
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