Convert Yolov5 to CoreML. Also add a decode layer.
How to use Yolov5 on iOS
Yolov5 is an object detection machine learning model.
Convert to CoreML format for use on iPhone and iPad.
The converted model cannot be used as it is
The converted model is a large number of boxes for each class, so it cannot be used as it is.
We need to add a layer for decoding and a layer for Non Max Suppression to narrow down the coordinates of the reliable box.
By doing these things, wewill be able to handle it with the iOS Vision framework, and we will be able to use a simple file preview function like the image at the beginning.
Here is a script that can be used on iOS
Click here for the converted model (COCO data set)
GitHub - john-rocky/CoreML-Models: Converted CoreML Model Zoo.
Converted CoreML Model Zoo. CoreML is a machine learning framework by Apple. If you are iOS developer, you can easly…
Yolov5 models trained with your own dataset can also be converted to CoreML format with this conversion script.
Conversion code explanation
Use the export code in the Yolov5 repository to convert the Pytorch model to a CoreML model.
Defines the decode layer.
Defines Non Max Suppression.
Add a decode layer and Non Max Suppression to your CoreML model.
This will save the CoreML model that you can use with Vision.
How to use on iOS
GitHub - john-rocky/CoreML-YOLOv5: A sample project how to use YOLOv5 in iOS
A sample project how to use YOLOv5 in iOS. You can run model on your image from photo library. 1, Clone or download…
Decoding and NMS refer to the following repositories and books.
GitHub - dbsystel/yolov5-coreml-tools: Scripts for exporting YOLOv5 models to CoreML and…
The scripts in this repo can be used to export a YOLOv5 model to coreml and benchmark it. Other dependencies are…
Core ML Survival Guide
Core ML is pretty easy to use - except when it doesn't do what you want. The Core ML Survival Guide is packed with tips…
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