Update README.md

README.md

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-[![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.
+title: BirdCLEF 2024
+emoji: 👁
+colorFrom: yellow
+colorTo: pink
+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