update

docs/source/index.rst

@@ -62,6 +62,7 @@ Supported datasets
 * IC03 from `ICDAR 2003 <http://www.iapr-tc11.org/mediawiki/index.php?title=ICDAR_2003_Robust_Reading_Competitions>`_.
 * IC13 from `ICDAR 2013 <http://dagdata.cvc.uab.es/icdar2013competition/>`_.
 * IMGUR5K from `"TextStyleBrush: Transfer of Text Aesthetics from a Single Example" <https://github.com/facebookresearch/IMGUR5K-Handwriting-Dataset>`_.
+* MJSynth from `"Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition" <https://www.robots.ox.ac.uk/~vgg/data/text/>`_.
 
 
 .. toctree::

doctr/datasets/mjsynth.py

@@ -17,18 +17,17 @@ class MJSynth(AbstractDataset):
     """MJSynth dataset from `"Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition"
     <https://www.robots.ox.ac.uk/~vgg/data/text/>`_.
 
-    Example::
-        >>> # NOTE: This is a pure recognition dataset without bounding box labels.
-        >>> # NOTE: You need to download the dataset.
-        >>> from doctr.datasets import MJSynth
-        >>> train_set = MJSynth(img_folder="/path/to/mjsynth/mnt/ramdisk/max/90kDICT32px",
-        >>>                     label_path="/path/to/mjsynth/mnt/ramdisk/max/90kDICT32px/imlist.txt",
-        >>>                     train=True)
-        >>> img, target = train_set[0]
-        >>> test_set = MJSynth(img_folder="/path/to/mjsynth/mnt/ramdisk/max/90kDICT32px",
-        >>>                    label_path="/path/to/mjsynth/mnt/ramdisk/max/90kDICT32px/imlist.txt")
-        >>>                    train=False)
-        >>> img, target = test_set[0]
+    >>> # NOTE: This is a pure recognition dataset without bounding box labels.
+    >>> # NOTE: You need to download the dataset.
+    >>> from doctr.datasets import MJSynth
+    >>> train_set = MJSynth(img_folder="/path/to/mjsynth/mnt/ramdisk/max/90kDICT32px",
+    >>>                     label_path="/path/to/mjsynth/mnt/ramdisk/max/90kDICT32px/imlist.txt",
+    >>>                     train=True)
+    >>> img, target = train_set[0]
+    >>> test_set = MJSynth(img_folder="/path/to/mjsynth/mnt/ramdisk/max/90kDICT32px",
+    >>>                    label_path="/path/to/mjsynth/mnt/ramdisk/max/90kDICT32px/imlist.txt")
+    >>>                    train=False)
+    >>> img, target = test_set[0]
 
     Args:
         img_folder: folder with all the images of the dataset