From d8809ba7e7a49c04531c436d044a9af3aff5d681 Mon Sep 17 00:00:00 2001 From: Raphael Maenle Date: Mon, 21 Mar 2022 14:15:34 +0000 Subject: [PATCH] Update README.md --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 34413f2..f5e3650 100644 --- a/README.md +++ b/README.md @@ -58,6 +58,7 @@ Here you'll train, quantize, compile (on a gpu if possible) and infer (on the ha explains well on how to create that. - There's a minimal example dataset in this repository under `/dataset` - To mount this, use eg.: `docker run -it --gpus all -ipc=host -v /path/to/dataset/:/dataset yolov5:v0` + - `python train.py --img 640 --batch 16 --epochs 3 --data /dataset/dataset/dataset.yaml --weights yolov5m.pt --cfg models/yolov5m.yaml` - For training, make sure you target the correct `--model` and use the correct `--weights` (which are now conveniently already in the hailo docker) - once you've saved the best.pb onnx file, you can exit this docker container - once you are done with the steps 'training and exporting to ONNX', move on to the next step.