Add installation scripts and update documentation for Phase 3 features

README.md

@@ -7,19 +7,68 @@ Process OBS recordings or any video/audio files with AI-based transcription and
 - AI transcription using Whisper.
 - Summarization using Hugging Face Transformers.
 - File selection, resource validation, and error handling.
+- Speaker diarization to identify different speakers in recordings.
+- Language detection and translation capabilities.
+- Keyword extraction with timestamp linking.
+- Interactive transcript with keyword highlighting.
+- Export to TXT, SRT, VTT, and ASS subtitle formats with compression options.
+- GPU acceleration for faster processing.
+- Caching system for previously processed files.
 
 ## Installation
-1. Clone the repo.
-git clone [https://github.com/DataAnts-AI/VideoTranscriber.git
-cd VideoTranscriber
-2. Install dependencies:
- pip install -r requirements.txt
 
+### Easy Installation (Recommended)
+
+#### Windows
+1. Download or clone the repository
+2. Run `install.bat` by double-clicking it
+3. Follow the on-screen instructions
+
+#### Linux/macOS
+1. Download or clone the repository
+2. Open a terminal in the project directory
+3. Make the install script executable: `chmod +x install.sh`
+4. Run the script: `./install.sh`
+5. Follow the on-screen instructions
+
+### Manual Installation
+1. Clone the repo.
+```
+git clone https://github.com/DataAnts-AI/VideoTranscriber.git
+cd VideoTranscriber
+```
+
+2. Install dependencies:
+```
+pip install -r requirements.txt
+```
 
 Notes:
-Ensure that the versions align with the features you use and your system compatibility.
-torch version should match the capabilities of your hardware (e.g., CUDA support for GPUs).
-whisper might need to be installed from source or a GitHub repository if it's not available on PyPI.
-If you encounter any issues regarding compatibility, versions may need adjustments.
+- Ensure that the versions align with the features you use and your system compatibility.
+- torch version should match the capabilities of your hardware (e.g., CUDA support for GPUs).
+- For advanced features like speaker diarization, you'll need a HuggingFace token.
+- See `INSTALLATION.md` for detailed instructions and troubleshooting.
 
-3. streamlit run app.py
+3. Run the application:
+```
+streamlit run app.py
+```
+
+## Usage
+1. Set your base folder where OBS recordings are stored
+2. Select a recording from the dropdown
+3. Choose transcription and summarization models
+4. Configure performance settings (GPU acceleration, caching)
+5. Select export formats and compression options
+6. Click "Process Recording" to start
+
+## Advanced Features
+- **Speaker Diarization**: Identify and label different speakers in your recordings
+- **Translation**: Automatically detect language and translate to multiple languages
+- **Keyword Extraction**: Extract important keywords with timestamp links
+- **Interactive Transcript**: Navigate through the transcript with keyword highlighting
+- **GPU Acceleration**: Utilize your GPU for faster processing
+- **Caching**: Save processing time by caching results
+
+## Contributing
+Contributions are welcome! Please feel free to submit a Pull Request.