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CoreML Semantic Segmentation with DETR ResNet50

This project is a practice implementation using Apple's DETR ResNet50 Semantic Segmentation model. It performs segmentation on live camera input in an iOS app, and displays the results along with a pie chart showing the area fraction of each detected class.

Features

  • Real-time segmentation using DETR ResNet50 Semantic Segmentation model
  • Visualization of segmentation results overlaid on the camera feed
  • Pie chart display of class area fractions

App Screenshot

Setup Instructions

  1. Clone the Repository

    git clone https://github.com/DaisukeNakajima001/Test_CoreML_Segmentation_and_Drow_AreaFraction_Graph.git

  2. Download the Model

  3. Add the Model to the Project

    • Place the downloaded .mlmodel file in the AI_Models directory of the project.
    • In Xcode, drag and drop the .mlmodel file into the project navigator.
    • Ensure the model is added to the target.

  4. Build and Run the Project

    • Open the project in Xcode.
    • Connect an iOS device and select it as the build target.
    • Press Cmd+R to build and run the app on your device.

Notes

  • The .mlmodel file is ignored in version control (.gitignore).
  • You must download the model separately and link it in Xcode.
  • Ensure proper permissions for camera access in your app's Info.plist.
<key>NSCameraUsageDescription</key>
<string>Camera access is required for segmentation.</string>