Update README.md

README.md

@@ -1,3 +1,4 @@
+---
 title: BirdCLEF 2024
 emoji: 👁
 colorFrom: yellow
@@ -6,4 +7,124 @@ sdk: gradio
 sdk_version: 4.36.0
 app_file: app.py
 pinned: false
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+[![Review Assignment Due Date](https://classroom.github.com/assets/deadline-readme-button-24ddc0f5d75046c5622901739e7c5dd533143b0c8e959d652212380cedb1ea36.svg)](https://classroom.github.com/a/rzFn0ERT)
+
+# BirdCLEF 2024: Bird Species Identification from Audio
+
+## Overview
+
+This project is part of the BirdCLEF 2024 competition, focusing on identifying bird species from audio recordings. The
+target region is the Western Ghats, a significant biodiversity hotspot in India. The goal is to develop a machine
+learning model capable of accurately predicting bird species from audio recordings, with a particular emphasis on
+under-studied species.
+
+## Author
+
+This project was created by:
+
+- **Name**: LAGHJAJ ABDELLATIF
+- **Email**: abdelatiflaghjaj@gmail.com
+
+## Screenshots
+
+|          **Sketch**          |       **Main App**        |       **Result**        |
+|:----------------------------:|:-------------------------:|:-----------------------:|
+| ![Sketch](images/sketch.png) | ![Main App](images/1.png) | ![Result](images/2.png) |
+
+## Project Components
+
+1. **Data Collection**
+2. **Preprocessing**
+3. **Model Training**
+4. **Prediction and Visualization**
+5. **User Interface**
+
+## Setup Instructions
+
+### Prerequisites
+
+Ensure you have the following installed:
+
+- Python 3.8 or higher
+- Required Python packages (specified below)
+
+### Installation
+
+1. Clone the repository:
+    ```bash
+    git clone https://github.com/ISEF-soft/introduction-to-machine-learning-challenge-abdellatif-laghjaj
+    cd introduction-to-machine-learning-challenge-abdellatif-laghjaj
+    ```
+
+2. Create and activate a virtual environment:
+    ```bash
+    python -m venv venv
+    source venv/bin/activate  # On Windows use `venv\Scripts\activate`
+    ```
+
+3. Install the required packages:
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+### Directory Structure
+
+Ensure your project directory is structured as follows:
+
+```
+birdclef2024/
+│
+├── sounds/
+│ ├── asbfly.ogg
+│ ├── bkwsti.ogg
+│ └── comros.ogg
+│
+|── .gitignore
+├── model.joblib
+├── data.csv
+├── app.py
+|── main.ipynb
+├── README.md
+└── requirements.txt
+```
+
+### Files Description
+
+- `sounds/`: Directory containing sample audio files.
+- `model.joblib`: Pre-trained machine learning model.
+- `data.csv`: CSV file containing bird species metadata.
+- `app.py`: Main Python script to run the project.
+- `main.ipynb`: Jupyter notebook containing the project code.
+- `README.md`: This readme file.
+- `requirements.txt`: List of Python packages required.
+
+### Running the Project
+
+1. Ensure you have the correct directory structure and all necessary files.
+2. Run the `app.py` script to start the Gradio interface:
+    ```bash
+    python apy.py
+    ```
+
+### Usage
+
+Once the Gradio interface is launched, you can:
+
+- **Upload an audio recording** of a bird to identify the species.
+- **Select a sample** from the provided audio files.
+
+The interface will display:
+
+- The **predicted bird species**.
+- The **prediction confidence**.
+- A **map** showing the location of the recording.
+- A **spectrogram** of the audio recording.
+
+## Acknowledgements
+
+This project is based on the BirdCLEF 2024 competition. Special thanks to the organizers and contributors who provided
+the dataset and resources.