ML Trainer vs Foxglove WebSocket Bridge

Creating original training data for Image Classification machine learning models just got a little easier! ML Trainer allows developers to quickly capture and export thousands of images to the Photos app, allowing every image to be imported with iCloud or the built in Image Capture app on Mac. Press the Scan button to capture a preset amount of images as you move closer to or pivot around your subject, or Tap the Camera button to capture a single picture. Toggle the Flashlight to improve results in low light conditions, and tap the Save button to export any captured images to the Photos app. While each image is always captured at a speed of 3 Frames Per Second, you can adjust the Frame Count of each Scan in the Settings Menu. A larger Frame Count will save you time, while a lower Frame Count will help improve accuracy across different angles. Enabling Crosshairs and Guides in the Settings Menu can also help improve accuracy. This app was specifically designed to speed up the process of importing data into the Xcode Developer Tool named CreateML. Exported images should also be compatible with other platforms like TensorFlow and Azure Machine Learning. A wired connection to a macOS device with the Image Capture app open will always be the fastest way to import your data to desktop.

Stream sensor data from your iOS device to Foxglove. This app demonstrates how a custom server can use the Foxglove WebSocket Protocol to stream robotics data into Foxglove. Write your own server starting with the libraries and examples provided at https://github.com/foxglove/ws-protocol. View the source code for this app at https://github.com/foxglove/foxglove-ios-bridge. For further documentation on how to use Foxglove, visit https://docs.foxglove.dev/. ROS and the “nine dots” ROS logo are trademarks of Open Source Robotics Foundation.