models directory contains scripts for the following models, which download the pretrained models, compile and deploy them using HALO on X86-CPU or NVGPU. Please refer to Instruction.md for more details about how to run the examples.
| Model Class | Model Source | HALO Examples |
|---|---|---|
| AlexNet | PyTorch | models/vision/classification/alexnet |
| CaffeNet | BVLC/Caffe | models/vision/classification/caffenet |
| DenseNet-121 | PyTorch | models/vision/classification/densenet |
| GoogleNet | PyTorch | models/vision/classification/googlenet |
| Inception_V1 | ONNX | models/vision/classification/inception |
| Inception_V3 | PyTorch | models/vision/classification/inception |
| MNIST | TensorFlow Tutorial | models/vision/classification/mnist_simple |
| MobileNet_V2 | PyTorch | models/vision/classification/mobilenet |
| Resnet V1-18 | ONNX | models/vision/classification/resnet |
| ResNet V2-50 | ONNX | models/vision/classification/resnet |
| ResNet V2-101 | ONNX | models/vision/classification/resnet |
| ShuffleNet | ONNX | models/vision/classification/shufflenet |
| ShuffleNet_V2 | ONNX | |
| SqueezeNet_10 | PyTorch | models/vision/classification/squeezenet |
| SqueezeNet_11 | PyTorch | models/vision/classification/squeezenet |
| VGG-16 | PyTorch | models/vision/classification/vgg |
| VGG-19 | PyTorch | models/vision/classification/vgg |
| Model Class | Model Source | HALO Examples |
|---|---|---|
| YOLO v3 | ONNX | models/vision/detection/yolo |
| UNet | PyTorch | models/vision/segmentation/unet |