resnet50-python-torchscript

TorchScript ResNet-50 inference with Python

This directory includes scripts used to run simple ResNet-50 inference via the MAX Engine Python API to classify an input image. In this case, we use an image of a leatherback turtle as an example.

Quickstart

Magic instructions

If you have magic, you can run the following command:

magic run bash run.sh

Conda instructions

Create a Conda environment, activate that environment, and install the requirements:

# Create a Conda environment if you don't have one
conda create -n max-repo
# Update the environment with the environment.yml file
conda env update -n max-repo -f environment.yml --prune
# Run the example
conda run -n max-repo --live-stream bash run.sh

Scripts included

• download-model.py: Downloads the model from HuggingFace, converts it to TorchScript, and saves it to an output directory of your choosing, or defaults to ../../models/resnet50.torchscript.

  For more information about the model, please refer to the model card.

• simple-inference.py: Classifies example input image using MAX Engine. The script prepares an example input, executes the model, and generates the resultant classification output.

  You can use the --input CLI flag to specify an input example. For example:

  python3 simple-inference.py --input=<path_to_input_jpg>