Commit 39f0c107 authored by Jerome Flesch's avatar Jerome Flesch

README: Update Debian package name for Pillow

Signed-off-by: Jerome Flesch's avatarJerome Flesch <jflesch@openpaper.work>
parent 26f73090
......@@ -36,16 +36,16 @@ bmp, tiff, and others. It also support bounding box data.
## Installation
```sh
$ sudo pip install pyocr # Python 2.7
$ sudo pip3 install pyocr # Python 3.X
sudo pip install pyocr # Python 2.7
sudo pip3 install pyocr # Python 3.X
```
or the manual way:
```sh
$ mkdir -p ~/git ; cd git
$ git clone https://github.com/jflesch/pyocr.git
$ cd pyocr
$ sudo python ./setup.py install
mkdir -p ~/git ; cd git
git clone https://github.com/jflesch/pyocr.git
cd pyocr
sudo python ./setup.py install
```
......@@ -146,8 +146,9 @@ detected in the image.
* PyOCR requires python 2.7 or later. Python 3 is supported.
* You will need [Pillow](https://github.com/python-imaging/Pillow)
or Python Imaging Library (PIL). Under Debian/Ubuntu, PIL is in
the package "python-imaging".
or Python Imaging Library (PIL). Under Debian/Ubuntu, Pillow is in
the package ```python-pil``` (```python3-pil``` for the Python 3
version).
* Install an OCR:
* [libtesseract](http://code.google.com/p/tesseract-ocr/)
('libtesseract3' + 'tesseract-ocr-&lt;lang&gt;' in Debian).
......@@ -155,12 +156,14 @@ detected in the image.
('tesseract-ocr' + 'tesseract-ocr-&lt;lang&gt;' in Debian).
You must be able to invoke the tesseract command as "tesseract".
PyOCR is tested with Tesseract >= 3.01 only.
* or cuneiform
* or Cuneiform
## Tests
$ python ./run_tests.py
```sh
python ./run_tests.py
```
Tests are made to be run with the latest versions of Tesseract and Cuneiform.
the first tests verify that you're using the expected version.
......@@ -175,7 +178,8 @@ To run the tesseract tests, you will need the following lang data files:
If you want to run OCR on natural scenes (photos, etc), you will have to filter
the image first. There are many algorithms possible to do that. One of those
who gives the best results is [Stroke Width Transform](https://github.com/jflesch/libpillowfight#stroke-width-transformation).
who gives the best results is
[Stroke Width Transform](https://github.com/jflesch/libpillowfight#stroke-width-transformation).
## Contact
......
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