Drone tracking algorithm implementation in python based on older algorithm implemented in Matlab (see matlab_drone_tracker_project_report.docx)
This project's goal was to design a real time algorithm that enables a drone with a camera to track another drone.
Full project description can be found in the project report file: python_drone_tracker_project_report.pdf

Software Installation for windows 64 bit: (Detailed installation instructions can be found in setup_instructions.pdf)

• Anaconda for Python 3.5 -> https://repo.continuum.io/archive/ -> Anaconda3-4.2.0-Windows-x86_64.exe
  • Add Anaconda3 to Environment Variables
• JetBrains PyCharm 2019.1.1 -> https://www.jetbrains.com/pycharm/download/#section=windows
  • Configure Anaconda as your project's python interpreter
• Python packages
  • opencv-python (3.4.5.20)
  • joblib (0.13.2)
  • numpy (1.11.3)
  • scipy (1.2.1)
  • scikit-image (0.13.1)
  • sklearn (0.0)
  • scikit-learn (0.20.3)
  • matplotlib (1.5.1)
  • Pillow (2.9.0)
• Caffe -> https://github.com/BVLC/caffe/tree/windows
  • edit scripts\build_win.cmd:
    • WITH_NINJA = 0
    • PYTHON_VERSION = 3
    • CONDA_ROOT = <your conda root, e.g C:\Program Files\Anaconda3>
• Visual Studio 2015 -> https://visualstudio.microsoft.com/vs/older-downloads/
  • Note that the compiler is not installed by default, choose C++ in Languages during installation
• CMake -> https://cmake.org/download/ -> cmake-3.14.5-win64-x64.msi
• Git -> https://git-scm.com/download/win
• Additional files
  • bvlc_alexnet - a folder with the neural network configuration and Caffe model. Too large for GitHub, available on server.
    • make sure the files bvlc_alexnet.caffemodel and deploy_fc7.prototxt are present
    • deploy_fc7.prototxt can also be found in bvlc_alexnet folder in this github (the Caffe model is too large to upload)
  • Drone movies (GOPR0010.MP4, GOPR0014.mp4). Too large for GitHub, available on server.
• Edit paths in Python code
  • Main_Drine_Tracking.py - net Caffe model path (lines 21-22)
  • video_info.py - input videos path