Ultralytics HUB datasets align with the format used by YOLOv5 and YOLOv8. They adhere to the same structural and labeling conventions, ensuring a seamless experience.
Ensure that the YAML file describing your dataset is placed in the root directory of your dataset, as illustrated below. Once in place, zip the directory for uploading to Ultralytics HUB. The dataset YAML, its directory, and the zip file should all bear the identical name.
For instance, with a dataset named 'coco8', as shown in ultralytics/hub/example_datasets/coco8.zip, include a coco8.yaml
within the coco8/
directory. Zip this to form coco8.zip
for upload with the command:
# Zipping the dataset directory for upload
zip -r coco8.zip coco8
Explore the provided example_datasets/coco8.zip for insights on structuring your custom dataset.
The dataset YAML follows the established YOLOv5 and YOLOv8 format. For exhaustive instructions, refer to the Train Custom Data tutorial.
# YAML configuration example for custom datasets
path: # dataset root dir (leave empty for HUB integration)
train: images/train # train images (relative to 'path') 8 images
val: images/val # val images (relative to 'path') 8 images
test: # test images (optional)
# Class labels
names:
0: person
1: bicycle
2: car
3: motorcycle
# Add more classes as needed
Upload your zipped dataset to Ultralytics HUB by logging in, navigating to the 'Datasets' tab, and selecting 'Upload Dataset'. This lets you scan and view your dataset prior to training YOLOv5 or YOLOv8 models.
Connect to the Ultralytics HUB notebook and employ your model API key to embark on model training!
Transition your model to 13 different formats including TensorFlow, ONNX, OpenVINO, CoreML, Paddle, and more. Operate your models directly on your iOS or Android mobile device by downloading the Ultralytics App!
For those just embarking on their Ultralytics HUB journey, the Issues tab is your go-to resource for support. Click the 'New Issue' button and share your thoughts or questions. Our aim is to enhance your experience with invaluable solutions and improvements! 😃