Update Ocrs project link in README and reformat paragraphs

README.md

@@ -1,16 +1,20 @@
 # ocrs-models
 
-This project contains PyTorch models for the
-[**ocrs**](https://github.com/robertknight/rten/tree/main/ocrs) OCR engine.
+This project contains tools for training PyTorch models for use with the
+[**Ocrs**](https://github.com/robertknight/ocrs/) OCR engine.
 
 The ocrs engine splits text detection and recognition into three phases, each
 of which corresponds to a different model in this repository:
 
-1. **Text detection**: This is a semantic segmentation model which classifies 
-each pixel in a greyscale input image as text/non-text. Consumers then post-process clusters of text pixels to get oriented bounding boxes for words.
-2. **Layout analysis (VERY WIP)**: This is a graph model which takes word bounding boxes as input nodes and
-classifies each node's relation to nearby nodes (eg. start / middle / end of line)
-3. **Text recognition**: This is a CRNN model that takes a greyscale image of a text line as input and returns a sequence of characters.
+1. **Text detection**: This is a semantic segmentation model which classifies
+   each pixel in a greyscale input image as text/non-text. Consumers then
+   post-process clusters of text pixels to get oriented bounding boxes for
+   words.
+2. **Layout analysis (VERY WIP)**: This is a graph model which takes word
+   bounding boxes as input nodes and classifies each node's relation to nearby
+   nodes (eg. start / middle / end of line)
+3. **Text recognition**: This is a CRNN model that takes a greyscale image of a
+   text line as input and returns a sequence of characters.
 
 All models can be exported to ONNX for downstream use.