Using PyTorch for Image Classification and Object Detection/

Using a PyTorch Model in JavaScript with ONNX

In this project, we’ll convert a PyTorch model and use it in JavaScript with ONNX.

The Open Neural Network Exchange (ONNX) is an open-source artificial intelligence ecosystem that promotes innovation and collaboration in the AI sector. ResNet-18 is an 18 layer deep, convolutional neural network used for image classification.

We’ll start by importing a pre-trained ResNet-18 model. Then we’ll export the model from Python to ONNX. At the end of this project, we’ll import this model in JavaScript and use it to make predictions.

Before We Start

Basics of Convolutional Neural Networks

Cats vs Dogs Classification with Convolutional Neural Networks

Popular Neural Network Architectures for Image Classification

Using PyTorch for Image Classification

Model Deployment

Using a PyTorch Model in JavaScript with ONNX

Basics of Object Detection

Two-Stage Object Detection Architectures

One-Stage Object Detection Architectures

YOLOv7 Model Train and Inference on Edge

Conclusion

Appendix

Building a System for Safety Helmet Detection Based on YOLOv5

Using a PyTorch Model in JavaScript with ONNX