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Mobile Neural Networks on iOS with Core ML - Part 2

  1. 0

    Converting an ONNX Object Detection Model to iOS Core ML

    In this series, we’ll use a pretrained model to create an iOS application that will detect multiple persons and objects in a live camera feed rather than in a static picture.
    Added 23 Nov 2020
  2. 1

    Decoding a Core ML YOLO Object Detector

    In this article, we will decode the Core ML YOLO Model by transforming an array of abstract numbers to a human-readable form.
    Added 23 Nov 2020
  3. 2

    Decoding a YOLO Core ML Object Detector Using Array Operations

    In the next article, we’ll do the same but with array operations. This will allow us to include the decoding logic directly in the model.
    Added 24 Nov 2020
  4. 3

    Creating a YOLO Core ML Object Detector with Decoding Logic

    In this article we are ready to include detection decoding directly in the Core ML model.
    Added 25 Nov 2020
  5. 4

    Building a Core ML Pipeline for the iOS Vision Framework

    In this article we’ll create a Core ML pipeline to be our end-to-end model.
    Added 26 Nov 2020
  6. 5

    iOS Object Detection with Live Camera Preview

    In the next article, we’ll start working on the iOS application that will use that model.
    Added 27 Nov 2020
  7. 6

    Building an Object Detection iOS App with YOLO Core ML Model

    In this last article in this series, we’ll extend the application to use our YOLO v2 model for object detection.
    Added 30 Nov 2020