INSTALLATION.md

# Installation Guide - Music Classification Dataset

<!--
/**
* Project: Music Classification Dataset
* Author: Molla Samser
* Company: RSK World
* Designer & Tester: Rima Khatun
* Website: https://rskworld.in
* Email: help@rskworld.in, support@rskworld.in
* Phone: +91 93305 39277
*/
-->

## 🚀 Installation Instructions

This guide will walk you through the installation process for the Music Classification Dataset project.

---

## System Requirements

### Minimum Requirements
- **Operating System**: Windows 10/11, macOS 10.14+, or Linux (Ubuntu 18.04+)
- **Python**: 3.8 or higher
- **RAM**: 4 GB minimum (8 GB recommended)
- **Disk Space**: 2 GB free space
- **Internet**: Required for package downloads

### Recommended Requirements
- **Python**: 3.10 or 3.11
- **RAM**: 8 GB or more
- **Disk Space**: 5 GB or more (for additional audio samples)
- **GPU**: Optional (for neural network models)

---

## Step-by-Step Installation

### Step 1: Install Python

#### Windows
1. Download Python from [python.org](https://python.org)
2. Run the installer
3. **Important**: Check "Add Python to PATH"
4. Click "Install Now"
5. Verify installation:
```bash
python --version
```

#### macOS
```bash
# Using Homebrew
brew install python@3.11

# Verify installation
python3 --version
```

#### Linux (Ubuntu/Debian)
```bash
sudo apt update
sudo apt install python3.11 python3-pip python3-venv

# Verify installation
python3 --version
```

### Step 2: Download the Project

#### Option A: Download ZIP
1. Download the project ZIP file
2. Extract to your desired location
3. Open terminal/command prompt in the extracted folder

#### Option B: Using Git (if available)
```bash
git clone <repository-url>
cd music-classification
```

### Step 3: Create Virtual Environment

**Why?** Virtual environments keep project dependencies isolated.

#### Windows
```bash
# Create virtual environment
python -m venv venv

# Activate virtual environment
venv\Scripts\activate

# You should see (venv) in your prompt
```

#### macOS/Linux
```bash
# Create virtual environment
python3 -m venv venv

# Activate virtual environment
source venv/bin/activate

# You should see (venv) in your prompt
```

### Step 4: Install Dependencies

```bash
# Upgrade pip (recommended)
pip install --upgrade pip

# Install all required packages
pip install -r requirements.txt
```

**This will install:**
- librosa (audio processing)
- numpy (numerical computing)
- pandas (data manipulation)
- scikit-learn (machine learning)
- matplotlib (visualization)
- seaborn (statistical visualization)
- tensorflow (deep learning) - optional
- And more...

### Step 5: Verify Installation

Run the quick start script:

```bash
python quick_start.py
```

This will:
- ✓ Check all dependencies
- ✓ Verify directory structure
- ✓ Test basic functionality
- ✓ Display next steps

---

## Installation Methods

### Method 1: Standard Installation (Recommended)

```bash
# 1. Create and activate virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate

# 2. Install dependencies
pip install -r requirements.txt

# 3. Verify installation
python quick_start.py
```

### Method 2: Development Installation

For developers who want to modify the code:

```bash
# 1. Create and activate virtual environment
python -m venv venv
source venv/bin/activate

# 2. Install in development mode
pip install -e .

# 3. Install development dependencies
pip install -r requirements.txt
pip install jupyter pytest
```

### Method 3: Using setup.py

```bash
# Install the package
python setup.py install

# Or in development mode
python setup.py develop
```

---

## Optional Components

### Installing Jupyter Notebook

```bash
pip install jupyter notebook ipython
```

### Installing Deep Learning Support

```bash
pip install tensorflow keras
```

### Installing GPU Support (NVIDIA CUDA)

For faster training with GPU:

```bash
# For TensorFlow with GPU
pip install tensorflow-gpu

# Requires NVIDIA CUDA Toolkit and cuDNN
# See: https://www.tensorflow.org/install/gpu
```

---

## Platform-Specific Instructions

### Windows-Specific

**Install Visual C++ Build Tools** (if needed for some packages):
1. Download from [visualstudio.microsoft.com](https://visualstudio.microsoft.com/downloads/)
2. Install "Desktop development with C++"

**Using Anaconda (Alternative):**
```bash
conda create -n music-classification python=3.10
conda activate music-classification
pip install -r requirements.txt
```

### macOS-Specific

**Install Homebrew** (if not installed):
```bash
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
```

**Install audio libraries:**
```bash
brew install portaudio
brew install ffmpeg
```

### Linux-Specific

**Install system dependencies:**

```bash
# Ubuntu/Debian
sudo apt update
sudo apt install -y python3-dev python3-pip python3-venv
sudo apt install -y libsndfile1 ffmpeg portaudio19-dev

# Fedora
sudo dnf install python3-devel python3-pip
sudo dnf install libsndfile ffmpeg portaudio-devel

# Arch Linux
sudo pacman -S python python-pip
sudo pacman -S libsndfile ffmpeg portaudio
```

---

## Troubleshooting

### Common Issues

#### Issue 1: pip not found
```bash
# Windows
python -m ensurepip --upgrade

# Linux/macOS
sudo apt install python3-pip # Ubuntu
```

#### Issue 2: Permission denied
```bash
# Don't use sudo with pip in virtual environment
# Instead, activate venv first
source venv/bin/activate
pip install -r requirements.txt
```

#### Issue 3: librosa installation fails
```bash
# Install system audio libraries first
# Ubuntu:
sudo apt install libsndfile1 ffmpeg

# macOS:
brew install libsndfile ffmpeg
```

#### Issue 4: numpy/scipy build errors
```bash
# Install build dependencies
# Ubuntu:
sudo apt install python3-dev build-essential

# Then retry:
pip install numpy scipy
```

#### Issue 5: Virtual environment activation not working

**Windows:**
```bash
# If PowerShell execution policy blocks activation
Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
```

**Linux/macOS:**
```bash
# Make sure you're using the correct shell
echo $SHELL

# For bash:
source venv/bin/activate

# For fish:
source venv/bin/activate.fish
```

---

## Verification Checklist

After installation, verify:

- [ ] Python 3.8+ installed
- [ ] Virtual environment created and activated
- [ ] All packages from requirements.txt installed
- [ ] quick_start.py runs without errors
- [ ] Can import librosa: `python -c "import librosa; print(librosa.__version__)"`
- [ ] Can import sklearn: `python -c "import sklearn; print(sklearn.__version__)"`
- [ ] Directory structure is intact

---

## Getting Help

If you encounter issues:

### 1. Check the Error Message
Most error messages indicate what's missing or wrong.

### 2. Search Documentation
- Check USAGE_GUIDE.md
- Check README.md
- Check PROJECT_STRUCTURE.md

### 3. Contact Support

**Author:** Molla Samser
**Company:** RSK World
**Designer & Tester:** Rima Khatun

**Contact Information:**
- 📧 Email: help@rskworld.in, support@rskworld.in
- 📱 Phone: +91 93305 39277
- 🌐 Website: [https://rskworld.in](https://rskworld.in)
- 📞 Contact Form: [https://rskworld.in/contact.php](https://rskworld.in/contact.php)

---

## Next Steps

After successful installation:

1. **Explore the Dataset**
```bash
jupyter notebook notebooks/exploratory_analysis.ipynb
```

2. **Train a Model**
```bash
python models/train_model.py --model random_forest
```

3. **Read Documentation**
- USAGE_GUIDE.md - Detailed usage instructions
- DATASET_INFO.md - Dataset information
- README.md - Project overview

---

## Uninstallation

To remove the project:

```bash
# Deactivate virtual environment
deactivate

# Delete the project folder
# Windows:
rmdir /s music-classification

# Linux/macOS:
rm -rf music-classification
```

---

**© 2026 RSK World - Free Programming Resources & Source Code**

*Founded by Molla Samser with Designer & Tester Rima Khatun*

---

For installation support, please contact: **help@rskworld.in** or call **+91 93305 39277**