YOLOv8 Web UI

This Gradio application is designed to facilitate the end-to-end creation of a YOLOv8 object detection model.

Capabilities

Label Images: this tab lets you upload images, either in bulk or one at a time, to be labeled. The bounding boxes are automatically detected, and the labels are assigned through a textbox. Entries are separated by semi-colons
Image Gallery: this tab allows us to view our labeled images, seperated by the assigned training split
Train: train any of the YOLOv8 models on the labeled images. Outputs the validation metrics and the best trained model from the run, best.pt
Inference: predict object labels on images and videos. Works for direct upload and URL submission

This application wouldn't have been feasible without the groundwork completed by the researchers for the (GLIGEN)[https://github.com/gligen/GLIGEN] project. Their bounding box detector code was instrumental to making this work.
(Ultralytics)[https://github.com/ultralytics/ultralytics] for their incredible work on YOLOv8

Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
assets		assets
dataset		dataset
datasets		datasets
gligen		gligen
images		images
runs/detect		runs/detect
README.md		README.md
YOLO.ipynb		YOLO.ipynb
app-final.py		app-final.py
app.py		app.py
requirements.txt		requirements.txt