React web application for serverless object detection. The inference pipeline is done with ONNX models only and it consists of 4 steps: image preprocessing, object detection, non maximum supression and postprocessing (described in pipeline section). By default digits detection model and 0-9 labels are loaded.
Each pipeline step is done with ONNX models. The complete pipeline during inference is the following:
- Image preprocessing - resize and pad to match model input size (preprocessing)
- Object detection - Detect objects with YOLOv8 model (yolo)
- Non Maximum Supression - Apply NMS to YOLO output (nms)
- Postprocessing - Apply postprocessing to filtered boxes (postprocessing)
- React - Web application used to test object detection models for real world examples
- ONNX - All processing steps used in pipeline
- ONNX Runtime - Pipeline inference
- OpenCV - Image processing for the preprocessing without ONNX