Tracking chocolates on conveyor belt using custom trained Yolov8

video_to_image.ipynb - Convert video into images to get training data
autodistill.ipynb - Auto annotate images using Grounding DINO
run.py - script to make augmentations/albumentations of both images and annotations using variables in constant.yaml (special thanks to author of this article: https://medium.com/red-buffer/apply-data-augmentation-on-yolov5-yolov8-dataset-958e89d4bc5d)
yolov8_training.ipynb - train yolov8(small) on custom data
byte_track.ipynb - track and count items using trained model alongwith bytetrack and supervision.

Name		Name	Last commit message	Last commit date
Latest commit History 6 Commits
controller		controller
dataset		dataset
images		images
raw_video		raw_video
runs/detect		runs/detect
videos		videos
.gitignore		.gitignore
Readme.md		Readme.md
autodistill.ipynb		autodistill.ipynb
box_size.py		box_size.py
byte_track.ipynb		byte_track.ipynb
contants.yaml		contants.yaml
output_vis.png		output_vis.png
run.py		run.py
video_to_image.ipynb		video_to_image.ipynb
yolov8_training.ipynb		yolov8_training.ipynb

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