Drone - Based Traffic Data Processing Code for Road Traffic Planning in Lusaka, Zambia.

This repository contains the Python source code and documentation used for processing drone-based traffic video data in an undergraduate research study on the application of drone technology to road traffic planning in Lusaka, Zambia. The processing workflow includes YOLO-based vehicle detection, virtual line-crossing counts, basic vehicle tracking, queue-region processing, and extraction of traffic-processing outputs. The repository provides the reconstructed processing script and documentation describing its inputs, processing workflow, dependencies, and outputs. The trained YOLO model weights used during the original processing are not included because they are not currently available. Consequently, the repository does not by itself provide complete reproducibility of the original model inference. The code is provided to support transparency and reproducibility of the documented computational workflow associated with the research. No raw drone video, interview recordings, or personally identifiable information are included in this repository.