final touch

Author: ilyesdjerfaf

README.md

@@ -2,8 +2,12 @@
 
 Welcome to the QuickDraw API repository. This project encompasses the development of a machine learning model and its deployment through a user-friendly application. The complete project details are available [here](https://github.com/mlengineershub/QuickDraw-ML).
 
+![API](./endpoints/utils/website.png)
+
 ## Project Workflow
 
+![API](./endpoints/utils/pipeline.png)
+
 1. **Machine Learning Model Development**
     - The initial phase involved developing the machine learning model. Detailed information about the model can be found [here](https://github.com/mlengineershub/QuickDraw-ML).
 
@@ -12,6 +16,7 @@ Welcome to the QuickDraw API repository. This project encompasses the developmen
 
 3. **User Interface Development**
     - A user-friendly application interface was created using `HTML`, `CSS`, and `JavaScript`.
+    
 
 4. **Containerization**
     - The final application was containerized using `Docker`.
@@ -23,11 +28,33 @@ Welcome to the QuickDraw API repository. This project encompasses the developmen
 | `app/`             | Contains the files related to application development. |
 | `endpoints/`       | Contains the files for API endpoints.               |
 | `.gitignore`       | Specifies files and directories to be ignored by Git. |
+| `.dockerignore`       | Specifies files and directories to be ignored by Docker files. |
+| `docker-compose.yml` | The docker compose yaml file for app launching. |
+| `Dockerfile.txt` | The main docker file for the app. |
+| `README.md` | Short Documentation overview. |
 | `requirements.txt` | Lists all the dependencies required for the project. |
 
 ## Getting Started
 
-- [ ] TO DO
+1. Clone the repo or download the `docker-compose.yml` file
+
+* To clone the repo : 
+```bash
+git clone https://github.com/mlengineershub/QuickDraw-API.git
+cd QuickDraw-API
+```
+
+2. Run the `docker-compose.yml` :
+
+```bash
+docker-compose up -d
+```
+
+- Note : You can modify some parameters such as the port and the device directly in the `docker-compose.yml` 
+
+
+3. Go to : `localhost:PORT` (Default PORT = 5500) in your browser  
+
 
 ## Contributing