Code for a Parrot Bebop 2 drone to track animals (will be verified using dogs) steered autonomously from a computer using computer vision.
Aim: Using Machine Learning and Computer Vision to create and autonomous surveillance drone (will be verified using people)
The tutorial folder contains all the instructions for running the PyStalk project
5 tutorials are available:
- The “short python intro” can be used to get the basics of Python programming language.
- The “intro_to_neural_nets” provides a general introduction to neural networks. The theory is applied to a letter recognition example.
- The “Using Convolutional Neural Networks to classify dogs and cats” provides a general way to use convolutional neural networks to classify images.
- The “TF_model_tutorial” can be used as an instruction guide to install all the packages needed to run the TensorFlow model ssd_inception_v2.
- The “Getting ready with pyparrot_modified” provides an installation guide for all the libraries needed for the drone connectivity and the drone motion.
This folder contains the modified pre-trained TensorFlow model and all necessary utils which are needed for object detection
This folder contains all the script necessary for establishing the connection between the drone and the computer