Update README.md

README.md

@@ -3,10 +3,17 @@ A project for the course Low-rank Approximation Techniques.
 
 ![le chat](img4_100.jpg?raw=true "Title") + ![le Big Ben](img2_100.jpg?raw=true "Title") = ![le chat dans le Big Ben](img42.jpg?raw=true "Title")
 
+## Code:
+- The notebook [main.ipynb](main.ipynb) contain all runnable code and output all the figures. Change the number of the images in the main to chose which original images you want to use.
+- The python file [sinkhorn.py](sinkhorn.py) contain the main function `Sinkhorn` for the sinkhorn algorithm and variations.
+- The python file [builders.py](builders.py) contain the builders functions used to manipulate images and initialize parameters of `Sinkhorn`.
+
+## Dependencies:
+- Numpy
+- Matplotlib
+- Sikit-Learn
+
 ## Main references:
 - [1] [Massively scalable Sinkhorn distances via the Nyström method](https://arxiv.org/pdf/1812.05189.pdf)
 - [2] [Computational Optimal Transport](https://arxiv.org/pdf/1803.00567.pdf)
 - [3] [Adaptive color transfer with relaxed optimal transport](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7025983)
-
-## Code:
-- The notebook [main.ipynb](main.ipynb) contain all runnable code and output all the figures. Change the number of the images in the main to chose which original images you want to use.