Update README.md

Author: akshaybhatia10

README.md

@@ -17,6 +17,7 @@ Original Image             |Mask generated by the model|Mask overlaid on origina
 
 ### About
 In this work, we implement the U-Net segmentation architecture on the Mnih et. al. Massachusetts Roads Dataset for the task of road network extraction. The trained model achieves a mask accuracy of 96% on the test set. The model was trained on AWS P2.x instance.
+Inference time on a single K80 Tesla GPU(AWS P2.x instance) is 1.5 second and on CPU is 6 seconds.
 
 ### Massachusetts Roads Dataset Summary
 The Massachusetts Roads Dataset by Mnih et. al. is freely available at [here](https://www.cs.toronto.edu/~vmnih/data/). There is also a torrent link available [here](http://academictorrents.com/details/3b17f08ed5027ea24db04f460b7894d913f86c21).
@@ -42,7 +43,7 @@ chmod 777 setup.sh
 ./setup.sh
 ```
 
-To train the model, proceed with step 3. To test the pretrained model, skip to [Quick start](#quick-start) step 2.
+To train the model, proceed with step 3 and then [Quick start](#quick-start) step 1. To test the pretrained model, simply skip to [Quick start](#quick-start) step 2.
 
 3. Download the dataset from [here](http://academictorrents.com/details/3b17f08ed5027ea24db04f460b7894d913f86c21) or [here](https://www.cs.toronto.edu/~vmnih/data/). It is recommended to download the dataset using the torrent link since it downloads the files in the appropriate directories.