Eyeware Data Recorder vs ML Trainer

Eyeware Data Recorder is an iOS app intended to be used as a data collection tool by the Eyeware team. The collected data is used to improve the eye tracking algorithms that are developed and distributed by Eyeware in their research projects and products. An example of such a product is the Eyeware Beam iOS app, which turns your iPhone into a head and eye tracking device for gamers and streamers. In this case, gamers and streamers would directly benefit from the data collected by testers using the Eyeware Data Recorder iOS app: Beam users will have a smoother and increasingly pleasant experience using their iPhone or iPad as a head and eye tracker. Eyeware Data Recorder is useful for scientific studies that will in the end increase the performance of eye tracking algorithms developed by Eyeware Tech. The app records the user’s face area while following a sequence of points appearing on the screen of the device. The user is asked to watch a set of points that will be used as ground-truth. The data, in the form of videos and non-personal metadata, will be uploaded to Eyeware’s servers, and will then be used to help improve the performance of Eyeware’s gaze tracking algorithms. All collected data is treated with the appropriate care in terms of confidentiality and security. The data is anonymized: users are asked for some personal details (name and email), but is stored on a separate server from the video data. Thus, no-one at Eyeware can have access to both the personal details and the video data. All collected data is not connected in any way to personal details of the data provider, i.e. the tester who is participating in the data collection activity. Collected data can be deleted at any moment by simply emailing us via the email address you provided for the sign up.

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.