diff --git a/project/minimal_examples/README.md b/project/minimal_examples/README.md
index 627c8ff6736ea7552220f77a6803138426ba6009..5207370b65a14ae7c34ea19ad8f89a8a822efd5c 100644
--- a/project/minimal_examples/README.md
+++ b/project/minimal_examples/README.md
@@ -22,24 +22,28 @@ source venv/bin/activate
 pip install -r requirements.txt
 ```
 
-## 💻  Usage: `extract_features.py`
+## `extract_features.py`
 
+### 💻  Usage
 ```bash
 python extract_features.py
 ```
 
+### 📊 Outputs
 This will extract the RGB values from the image [`figures/examples_from_dataset/banana.jpg`](../figures/examples_from_dataset/banana.jpg) and create the following files:
 - `features-banana.txt` :arrow_right: contains the features (RGB values) of the image
 - `features-banana-flattened.txt` :arrow_right: contains the flattened features (RGB values) of the image
 - `features-banana-resized.txt`:arrow_right: contains the features (RGB values) of the banana image after resizing it to 50x50 pixels
 - `features-banana-resized-flattened.txt`:arrow_right: contains the flattened features (RGB values) of the banana image after resizing it to 50x50 pixels
 
-## 💻  `apply_filters.py`
+## `apply_filters.py`
 
+### 💻  Usage
 ```bash
 python apply_filters.py
 ```
 
+### 📊 Outputs
 This will apply the following filters to the image [`figures/examples_from_dataset/banana.jpg`](../figures/examples_from_dataset/banana.jpg) and create the following files in the folder [`figures/examples_from_dataset/`](../figures/examples_from_dataset/):
 
 - `banana-edges.jpg` :arrow_right: contains the image with applied Canny edge detection filter