Object Detection with YOLO

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Object Detection with YOLO#

In this workshop, we’ll go through the steps of acquiring images, annotating them, training an object detection model, and testing it in real time on our USB microscopes.

        flowchart LR
    A(🔬 Acquisition) --> B(🖌️ Annotation)
    B --> C(🎓 Training)
    C --> D(⚖️ Validation)
    D --> E(🔋 Inference)

Introduction

We will implement a system based on the YOLO algorithm, which is a state-of-the-art method for real-time object detection. YOLO models usually offer good performance and require few images for training, making them particularly useful for applications in computer vision and scientific image analysis.

We will train a model to automatically recognize different kinds of seeds and spices from your kitchen:

seeds_overview

Microscope Setup#

To complete this workshop, you will need:

  • A USB microscope

  • Some seeds to capture images of (e.g., quinoa, chia)

  • Python installed on your system

Camera Setup

You should also be able to start the camera and capture images.

Open the Camera app from the Start menu.

Open the Photo Booth app from the Applications folder.

  1. Install Cheese using sudo apt install cheese.

  2. Launch it from the terminal with the cheese command.

Now that you’re set up, let’s dive in - starting with acquiring some training images.

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