Thermal Camera Setup and Testing Guide

This repository provides step-by-step instructions to set up and use a thermal camera (e.g., FLIR Lepton) with the PureThermal 2 interface board. It also includes preliminary exercises to validate that the hardware and software are correctly configured before running the final project.

---

Features

• Real-time thermal video visualization.
• Highlights the hottest and coldest points in the frame, displaying their temperatures.
• A side color bar shows the temperature range (red = hottest, blue = coldest).

---

Requirements

Hardware

• PureThermal 2 interface board.
• FLIR Lepton camera module.
• A computer running Linux (tested on Ubuntu).

Software

• Python 3.x.
• Required libraries:
  • libuvc.
  • OpenCV.
  • numpy.

---

Step-by-Step Setup

Step 1: Clone This Repository

Clone this repository to your local machine:

git clone https://github.com/Clarrainl/thermal-camera.git
cd thermal-camera

---

Step 2: Install System Dependencies

Install the required libraries and dependencies:

sudo apt update
sudo apt install -y build-essential cmake libusb-1.0-0-dev libjpeg-dev python3-pip libgtk2.0-dev libgtk-3-dev python3-opencv

---

Step 3: Clone and Build libuvc

Clone the libuvc repository and build it on your machine:

git clone https://github.com/groupgets/libuvc.git
cd libuvc
mkdir build && cd build
cmake ..
make
sudo make install
sudo ldconfig

Expected result: The make command should complete without errors, showing output like:

[100%] Built target uvc

---

Step 4: Activate the Virtual Environment

A virtual environment has already been created in the file directory of this repository. To activate it, run:

cd file
source thermcam/bin/activate

This ensures all dependencies are properly installed and isolated for this project.

---

Running the Final Project

Step 5: Run the Final Script

The main script for the project is uvc-radiometry-celsius.py. Navigate to the directory and activate the environment before running:

cd file
source thermcam/bin/activate
sudo python3 uvc-radiometry-celsius.py

Expected result:

• The thermal image will be displayed in real-time.
• The hottest and coldest points will be highlighted in red and blue, respectively.
• Their temperatures will be displayed in white.
• A color bar on the right will indicate the temperature range.

Press q to exit the program.

---

Troubleshooting

**Issue: **

1. Ensure the camera is properly connected.
2. Verify detection with:

   ls /dev/video*

If no device appears, check the USB connection.

---

Issue: OpenCV Errors

If you encounter errors like:

• The function is not implemented.
• Cannot query video position.

Ensure OpenCV is installed via:

sudo apt update
sudo apt install python3-opencv

---

Repository Structure

thermal-camera-project/
├── README.md                   # Documentation
├── LICENSE                     # License information
├── file/                       # Main directory for scripts and virtual environment
│   ├── thermcam/               # Virtual environment for the project
│   ├── uvc-deviceinfo.py       # Camera info script
│   ├── uvc-radiometry.py       # Basic thermal data stream
│   └── uvc-radiometry-celsius.py # Final project script

---

Example Output

The final thermal video includes:

• Real-time thermal visualization.
• Hottest (red) and coldest (blue) points highlighted.
• A color bar on the right showing the temperature range:

---

Credits

• libuvc
• OpenCV

Authors

• Clarrainl
• j-albo
• Mauweberla

Acknowledgements

• Creation of GitHub template: Marita Georganta - Robotic Sensing Expert
• Creation of MRAC-IAAC GitHub Structure: Huanyu Li - Robotic Researcher