Vision Detector 4+

Unlock the power of CoreML on video streams with Vision Detector, simplifying model execution without the need for Xcode previews or application builds.

Vision Detector performs image processing using a CoreML model on Mac.
To use the app, first prepare a machine learning model in CoreML format using CreateML or coreml tools. Then, open your machine learning model by drag & drop on Finder or Dock.
When an external video input device is connected to your Mac, it will be used in priority. If no external device is available, the FaceTime camera on your MacBook will be used. You can also use your iPhone nearby Mac.
Push 'Play' button or hit space bar to start/stop processing video input.

The supported types of machine learning models include:
- Image classification
- Object detection
- Style transfer
Models lacking a non-maximum suppression layer, or those that use MultiArray for input/output data, are not supported.

In the iClouds documents folder (/Libraries/Containers/VisionDetector/Data/Documents/), you'll find an empty tab-separated values (TSV) file named 'customMessage.tsv'. This file is for defining custom messages to be displayed while running object detection model. The data should be organized into a table with two columns as follows:
(Label output by YOLO, etc.) (tab) (Message) (return)
(Label output by YOLO, etc.) (tab) (Message) (return)
(Label output by YOLO, etc.) (tab) (Message) (return)
This is experimental.

Note: This application does not include a machine learning model.