How doguilmak/drone-detection-yolov8x works
This repository is a Colab-style YOLOv8x drone-detection research project. Its main workflow configures a labeled dataset, trains a detector, and records results; the notebook also describes video tracking. The available source excerpt omits parts of the training and tracking cells, so the graph shows only documented or directly supported connections.
Main entry points: drone_detection_yolov8x.py Training Notebook · coco.yaml Dataset Config · train_batch Training Batch · test_batch Test Batch
Components 8
Training Workflow
- Training Notebook
drone_detection_yolov8x.py - Dataset Config
coco.yaml - Training Batch
train_batch - Test Batch
test_batch - Drone Video
test/pexels-joseph-redfield-8459631 (1080p).mp4
Detection Model
- Ultralytics YOLO
Results
- Training Results
results
Other components
- Researcher
Connections 7
- Researcher → Training Notebook: runs
- Training Notebook → Dataset Config: writes config
- Training Notebook → Ultralytics YOLO: trains model
- Training Notebook → Training Batch: uses data
- Training Notebook → Test Batch: uses data
- Training Notebook → Training Results: records results
- Training Notebook → Drone Video: tracks video