TFClassify-Unity and TFClassify-Unity-Barracuda
These are ecosystem siblings representing different inference backend approaches—the first uses TensorFlow directly while the second uses the same models converted to ONNX format and executed through Unity's native Barracuda inference engine for improved performance and compatibility.
About TFClassify-Unity
Syn-McJ/TFClassify-Unity
An example of using Tensorflow with Unity for image classification and object detection.
This project helps Unity developers integrate pre-trained TensorFlow models into their Unity applications. It takes an existing TensorFlow image classification or object detection model and allows it to identify objects or classify images within a Unity environment. This is for Unity developers who want to add AI-powered vision features to their games or simulations.
About TFClassify-Unity-Barracuda
Syn-McJ/TFClassify-Unity-Barracuda
An example of using Tensorflow and ONNX models with Unity Barracuda inference engine for image classification and object detection.
This project helps Unity developers integrate pre-trained machine learning models for visual tasks into their applications. You provide a TensorFlow or ONNX model and this project gives you a Unity application capable of classifying images or detecting objects within them. It's intended for Unity developers building interactive experiences or games that require real-time computer vision.
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