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Building a Real-Time Object Detection Web App with TensorFlow.js and p5.js

Tutorial February 12, 2025
javascript

  • Setup: The setup function initializes the canvas and video capture. The video is hidden by p5.js’s default element so that we can draw it onto the canvas manually.
  • Model Loading: We load the COCO-SSD model asynchronously. Once the model is ready, we start continuous object detection by calling detectObjects().
  • Detection Loop: The detectObjects function uses the loaded model to analyze the current video frame and stores the detection results. It recursively calls itself so that new frames are analyzed continuously.
  • Drawing: In the draw loop, the video feed is displayed and for each detected object, a rectangle and label are drawn. The bounding box coordinates and object class are provided by the model.

Now that you have a basic real-time object detection app, consider extending its functionality:

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