You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
37 lines
2.2 KiB
37 lines
2.2 KiB
# Roboflow Datasets |
|
|
|
You can now use Roboflow to organize, label, prepare, version, and host your datasets for training YOLOv5 🚀 models. Roboflow is free to use with YOLOv5 if you make your workspace public. |
|
UPDATED 30 September 2021. |
|
|
|
## Upload |
|
You can upload your data to Roboflow via [web UI](https://docs.roboflow.com/adding-data), [rest API](https://docs.roboflow.com/adding-data/upload-api), or [python](https://docs.roboflow.com/python). |
|
|
|
## Labeling |
|
After uploading data to Roboflow, you can label your data and review previous labels. |
|
|
|
[](https://roboflow.com/annotate) |
|
|
|
## Versioning |
|
You can make versions of your dataset with different preprocessing and offline augmentation options. YOLOv5 does online augmentations natively, so be intentional when layering Roboflow's offline augs on top. |
|
|
|
 |
|
|
|
## Exporting Data |
|
You can download your data in YOLOv5 format to quickly begin training. |
|
|
|
``` |
|
from roboflow import Roboflow |
|
rf = Roboflow(api_key="YOUR API KEY HERE") |
|
project = rf.workspace().project("YOUR PROJECT") |
|
dataset = project.version("YOUR VERSION").download("yolov5") |
|
``` |
|
|
|
## Custom Training |
|
We have released a custom training tutorial demonstrating all of the above capabilities. You can access the code here: |
|
|
|
[](https://colab.research.google.com/github/roboflow-ai/yolov5-custom-training-tutorial/blob/main/yolov5-custom-training.ipynb) |
|
|
|
## Active Learning |
|
The real world is messy and your model will invariably encounter situations your dataset didn't anticipate. Using [active learning](https://blog.roboflow.com/what-is-active-learning/) is an important strategy to iteratively improve your dataset and model. With the Roboflow and YOLOv5 integration, you can quickly make improvements on your model deployments by using a battle tested machine learning pipeline. |
|
|
|
<p align=""><a href="https://roboflow.com/?ref=ultralytics"><img width="1000" src="https://uploads-ssl.webflow.com/5f6bc60e665f54545a1e52a5/615627e5824c9c6195abfda9_computer-vision-cycle.png"/></a></p>
|
|
|