Update README.md

Author: Inbal-Schekler

README.md

@@ -17,21 +17,21 @@ We could only share the PPI images created from the original h5 radar files (and
 For running a demo with our data (radial velocity images) follow the bellow steps:
 
 ### Run Demo
-1- Download the train and test data from [this link](https://drive.google.com/file/d/1Hrb1F7lzfVPqyzXJq-WQ46zSClk7ks0F/view?usp=sharing) 
-2- Open 'UNET_Soaring birds_model_f.ipynb' 
-3- Copy the zip folder of the data to the colab files area and run the code training the UNET model with our data
-4- Run 'evaluate_performance_f.ipynb' for performance evalution with the best epoch from the previous code
+1- Download the train and test data from [this link](https://drive.google.com/file/d/1Hrb1F7lzfVPqyzXJq-WQ46zSClk7ks0F/view?usp=sharing)<br/> 
+2- Open 'UNET_Soaring birds_model_f.ipynb'<br/> 
+3- Copy the zip folder of the data to the colab files area and run the code<br/>
+4- Run 'evaluate_performance_f.ipynb' for performance evalution with the best epoch from the previous code<br/>
 
 
 For prediciting your data with our trainned model,follow the bellow steps:
 
-1- Create from your h5 radar files PPI images with 'creating_ppi.R' (in the 'prepare_data' folder). The model uses 2 previous images of each image we want to predict so you have to have consecutive images.
-2- Download our best epoch from [this link](https://drive.google.com/file/d/1hnWelWk0rSyUfAXgGJMQa_PCyip97_sc/view?usp=sharing)
-3- Run 'evaluate_performance_f.ipynb'
+1- Create from your h5 radar files PPI images with 'creating_ppi.R' (in the 'prepare_data' folder). The model uses 2 previous images for each image we want to detect flocks in, so you have to have consecutive images.<br/>
+2- Download our best epoch from [this link](https://drive.google.com/file/d/1hnWelWk0rSyUfAXgGJMQa_PCyip97_sc/view?usp=sharing)<br/>
+3- Run 'evaluate_performance_f.ipynb'<br/>
 
 
 In case you want to add more data for the training follow the bellow steps:
 
-1- Create PPI images with 'creating_ppi.R' in the 'prepare_data' folder.
-2- You need to tag the images. We used labal- studio https://labelstud.io/
-3- In case you did used label-studio, the program creates a few images if you tag the same image a few times (for adding/ correcting previous tag) and in addition, the mask name do not get the name of the origin image. The code prepare_img_mask.py in the 'prepare_data' folder concatanate masks of the same image and in addition, conact the image and mask names by their file names. 
+1- Create PPI images with 'creating_ppi.R' in the 'prepare_data' folder.<br/>
+2- You need to tag the images. We used labal- studio https://labelstud.io/<br/>
+3- In case you did used label-studio, the program creates a few images if you tag the same image a few times (for adding/ correcting previous tag) and in addition, the mask name do not get the name of the origin image. The code prepare_img_mask.py in the 'prepare_data' folder concatanate masks of the same image and in addition, conact the image and mask names by their file names.<br/>