Core ML supports a variety of machine learning models, including neural networks, tree ensembles, support vector machines, and generalized linear models. Core ML requires the Core ML model format (models with a .mlmodel file extension). learn more
For this Demo I used the SqueezeNet model dowloaded from here
Please find the orignal source code of model here
the app was fully made in swift
| Architecture | Master | Package | |
|---|---|---|---|
| macOS | x86_64 | ||
| Ubuntu 14.04 | x86_64 | ||
| Ubuntu 16.04 | x86_64 | ||
| Ubuntu 18.04 | x86_64 |
Swift Community-Hosted CI Platforms
| OS | Architecture | Build |
|---|---|---|
| Debian 9.1 (Raspberry Pi) | ARMv7 | |
| Fedora 27 | x86_64 | |
| Ubuntu 16.04 | x86_64 | |
| Ubuntu 16.04 | PPC64LE | |
| Ubuntu 16.04 | AArch64 | |
| Android | ARMv7 | |
| Android | AArch64 | |
| Ubuntu 16.04 (TensorFlow) | x86_64 | |
| macOS 10.13 (TensorFlow) | x86_64 | |
| Ubuntu 16.04 (TensorFlow with GPU) | x86_64 | |
| Debian 9.5 | x86_64 | |
| Windows 2019 | x86_64 |
