Create README.md

README.md

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+---
+dataset_info:
+  features:
+  - name: image
+    dtype: image
+  - name: label
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 12173747703
+    num_examples: 7224600
+  - name: val
+    num_bytes: 1352108669.283
+    num_examples: 802733
+  - name: test
+    num_bytes: 1484450563.896
+    num_examples: 891924
+  download_size: 12115256620
+  dataset_size: 15010306936.179
+task_categories:
+- image-to-text
+language:
+- en
+size_categories:
+- 1M<n<10M
+pretty_name: MJSynth
+---
+# Dataset Card for "MJSynth_text_recognition"
+
+This is the MJSynth dataset for text recognition on document images, synthetically generated, covering 90K English words.
+It includes training, validation and test splits.
+Source of the dataset: https://www.robots.ox.ac.uk/~vgg/data/text/
+
+Use dataset streaming functionality to try out the dataset quickly without downloading the entire dataset (refer: https://huggingface.co/docs/datasets/stream)
+
+Citation details provided on the source website (if you use the data please cite):
+
+@InProceedings{Jaderberg14c,
+  author       = "Max Jaderberg and Karen Simonyan and Andrea Vedaldi and Andrew Zisserman",
+  title        = "Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition",
+  booktitle    = "Workshop on Deep Learning, NIPS",
+  year         = "2014",
+}
+                
+@Article{Jaderberg16,
+  author       = "Max Jaderberg and Karen Simonyan and Andrea Vedaldi and Andrew Zisserman",
+  title        = "Reading Text in the Wild with Convolutional Neural Networks",
+  journal      = "International Journal of Computer Vision",
+  number       = "1",
+  volume       = "116",
+  pages        = "1--20",
+  month        = "jan",
+  year         = "2016",
+}