diff --git a/README.md b/README.md
index 17b89b1..10f4c41 100644
--- a/README.md
+++ b/README.md
@@ -53,16 +53,16 @@ For training and testing the U-net model, open the `train_unet_predictor.ipynb`
 ## Pre-trained models
 1. Download the models from [google drive](https://drive.google.com/drive/folders/1XLehM5DYqLqiAsteO_h1PYZnavcCNOcR?usp=sharing).
 2. Put the pre-trained models inside `/thermal-facial-landmarks-detection/models` directory.
-3. dlib shape predictor
-- To make predictions on images:
+3. **dlib shape predictor**
+- Make predictions on images:
 ```
 python dlib_predict_image.py --images dataset/gray/test/images/ --models  models/ --upsample 1
 ```
-- To make predictions on a video:
+- Make predictions on a video:
 ```
 python dlib_predict_video.py --input video/2_0.avi --models  models/ --upsample 1 --output video/output.mp4
 ```
-4. U-net
+4. **U-net model**
 ```
 python unet_predict_image.py --dataset dataset/gray/test --model  models/ 
 ```