donkey ui

Launch the Donkeycar graphical user interface

The donkey ui command launches a graphical user interface for managing your Donkeycar. The UI provides a visual way to interact with your car’s data, train models, and manage configurations.

Usage

donkey ui

Overview

The Donkeycar UI provides a graphical alternative to command-line tools, offering:

• Visual tub management and data review
• Model training with progress visualization
• Configuration editing
• Data visualization and analysis
• Model comparison and evaluation

The UI is a relatively new addition to Donkeycar and may not have all features available in the CLI tools. For advanced workflows, the command-line tools often provide more flexibility.

Features

The graphical interface typically includes:

Tub Management

• Browse and view recorded tubs
• Preview images from tub data
• Review driving sessions
• Delete or archive old tubs
• View tub metadata (record count, date, etc.)

Model Training

• Select training data (tubs)
• Configure training parameters
• Start training with progress bar
• View training metrics in real-time
• Save trained models

Data Visualization

• Plot steering and throttle distributions
• View histograms of recorded data
• Compare model predictions to user inputs
• Visualize training/validation loss curves

Configuration

• Edit config parameters
• Adjust model settings
• Configure hardware options
• Save configuration changes

Launching the UI

From your car directory:

cd ~/mycar
donkey ui

The UI will start and typically open in your default web browser or display a GUI window.

Example Session

$ donkey ui
Starting Donkeycar UI...
Loading configuration from: ./config.py
UI server running at: http://localhost:8887
Open your browser to: http://localhost:8887

The exact UI implementation may vary depending on your Donkeycar version. Refer to the UI’s built-in help or tooltips for specific features.

Use Cases

Quick Data Review

Visually review recorded data without command-line tools:

donkey ui
# Navigate to tub browser
# Click through images to review quality

Interactive Training

Train models with visual feedback:

donkey ui
# Select training tab
# Choose tubs
# Configure parameters
# Click "Train"
# Watch progress in real-time

Configuration Editing

Modify settings through forms instead of editing files:

donkey ui
# Navigate to config editor
# Adjust parameters with sliders/inputs
# Save changes

Model Comparison

Compare multiple models visually:

donkey ui
# Load model 1
# View predictions on test data
# Switch to model 2
# Compare results side-by-side

Benefits Over CLI

Visual Feedback

• See images directly instead of file paths
• Interactive plots and charts
• Real-time training progress
• Visual model comparison

Easier for Beginners

• No need to remember command syntax
• Guided workflows
• Form-based configuration
• Built-in help and tooltips

Batch Operations

• Select multiple tubs with checkboxes
• Bulk delete old data
• Compare multiple models at once

When to Use CLI Instead

The command-line tools are often better for:

• Automation: Scripting and batch processing
• Remote access: SSH sessions without display
• Advanced options: Full access to all parameters
• Performance: Lower overhead for large operations
• Documentation: Easier to document exact commands
• Reproducibility: Exact command history

Requirements

The UI may require additional dependencies:

pip install donkeycar[ui]

Or specifically:

pip install flask pillow matplotlib

Troubleshooting

UI won’t start

• Check that required dependencies are installed
• Verify no other service is using the port
• Look for error messages in terminal output
• Try running from car directory (where config.py exists)

Browser doesn’t open automatically

• Manually navigate to the URL shown in terminal (typically http://localhost:8887)
• Check if your firewall is blocking the port
• Try a different browser

Can’t see tubs or models

• Ensure you’re running from the correct directory
• Verify data/ and models/ directories exist
• Check file permissions
• Refresh the browser page

UI is slow or unresponsive

• Close other applications to free resources
• Try with smaller tubs first
• Check if training is running in background
• Restart the UI

Port already in use

Error: Port 8887 is already in use

• Stop other instances of the UI
• Kill the process using that port: lsof -ti:8887 | xargs kill
• Change the port in configuration

Remote access issues

• For remote access, you may need to bind to 0.0.0.0 instead of localhost
• Use SSH port forwarding: ssh -L 8887:localhost:8887 user@car-ip
• Configure firewall to allow the port

Comparison with Other Tools

Task	CLI Command	UI Equivalent
View tub data	ls data/	Tub browser
Train model	donkey train	Training tab
Plot predictions	donkey tubplot	Visualization tab
View histograms	donkey tubhist	Data analysis tab
Edit config	Edit myconfig.py	Config editor
Create movie	donkey makemovie	Video generator

Advanced Usage

Custom UI Port

If you need to run on a different port, check the UI documentation for configuration options or environment variables:

export DONKEY_UI_PORT=9000
donkey ui

Multiple Cars

Run UI for different car configurations:

# Car 1
cd ~/car1
donkey ui

# Car 2 (in different terminal, different port)
cd ~/car2  
export DONKEY_UI_PORT=8888
donkey ui

Remote Development

Access UI running on a remote car:

# On your local machine
ssh -L 8887:localhost:8887 [e-mail]

# On the remote car (in SSH session)
cd ~/mycar
donkey ui

# Now open http://localhost:8887 on your local machine

Best Practices

Security

• Don’t expose the UI to public internet without authentication
• Use SSH tunneling for remote access
• Keep Donkeycar updated for security patches

Performance

• Close UI when not in use to free resources
• Work with smaller datasets for faster response
• Train models via CLI for better performance

Workflow

• Use UI for exploration and quick tasks
• Use CLI for production workflows and automation
• Document important operations with CLI commands

Alternative Interfaces

Besides the donkey ui command, you can also:

Web Interface During Driving

python manage.py drive
# Access web interface at http://<car-ip>:8887

Provides driving controls and live camera feed.

Jupyter Notebooks

For data analysis:

import donkeycar as dk
from donkeycar.parts.tub_v2 import Tub

tub = Tub('./data/tub_1', read_only=True)
# Interactive exploration and visualization

Next Steps

After exploring the UI:

1. Learn CLI equivalents: Understand command-line versions for automation
2. Combine approaches: Use UI for exploration, CLI for production
3. Create workflows: Document your process using both tools
4. Contribute: Report UI bugs or suggest features to Donkeycar project

For more control and advanced features, explore the CLI commands:

• donkey createcar - Create new car projects
• donkey train - Train models with full options
• donkey tubplot - Advanced prediction analysis
• donkey makemovie - Create detailed videos