8000 GitHub - dev-chip/fever-monitor: A Python fever monitor using AI thermal face detection.
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Fever Monitor using YOLOv4 thermal face detection.

A project submitted in partial fulfilment of the award of the degree of BSc (Hons) Computer Science at Staffordshire University.

A Python fever monitor using AI thermal face detection.

How it works

Uses a FLIR Lepton™ 3.5 thermal imaging camera to input a thermal video feed using a Darknet YOLOv4 model (https://github.com/pjreddie/darknet). The user is alerted of any faces that exceed a temperature threshold.

Running the application

  1. Request the weights files from James Cook (contact@cookjames.uk).
  2. Download and install the latest Python 3 version.
  3. Download and unzip the Python application.
  4. After successfully receiving the two weights files: a. Copy the ‘tiny_yolo_3l_best.weights’ file into the following project subdirectory: ‘fever_monitor/yolo/Lightweight’ b. Copy the ‘yolo-obj_best.weights’ file into the following project subdirectory: ‘fever_monitor/yolo/Standard’
  5. Install Python prerequisites by running the ‘pip_installs’ script (cross-platform compatible).
  6. Install a Python cv2 module compatible with your system.
  7. Connect the PureThermal 2 FLIR Lepton Smart I/O Module board – with FLIR Lepton 3.5 thermal camera attached – by USB.
  8. Start the application GUI by running the ‘start_gui.py’ file.

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