Streamline Custom Vision AI Ops

Dedicated to making computer vision accessible, we are thrilled to announce our partnership with Roboflow as the official dataset management and annotation tool for YOLOv5.

Roboflow’s goal is to enable developers to build better computer vision models by streamlining the process of collecting and labeling your data, training your model, and using active learning to improve models even faster. This way, developers can spend more time on domain-specific problems instead of machine learning minutia and computer vision infrastructure.

Roboflow has continuously demonstrated their support to open source projects that share our vision. Make sure you check their guide on How to Train YOLOv5 on Custom Dataset, released in June 2020.

Ultralytics’ mission is to make AI easy by creating accessible Vision AI tools for every developer. YOLOv5 allows developers to start training and deploying state-of-the-art vision models in their own projects.

Via a shared vision of easy AI, Roboflow and Ultralytics are leveraging their unique strengths to bring greater capability to our users.
Now there’s new help on the horizon thanks to this new partnership that makes training custom models easier than ever before!

Introducing A New Partnership That Makes Training Custom Models Easier

YOLOv5 has now become one of the world's most popular AIs due to its simplicity and accuracy in real-world use cases. Our new Roboflow integration provides for an even more seamless YOLOv5 training and deployment experience.  

Now you can label and automatically export your custom datasets directly to YOLOv5 for training with Roboflow using their pip package, with a focus on enabling active learning. This way, you get to streamline your MLOps process by avoiding the time spent on computer vision minutia.
Eliminate all the needless work with machine learning to make computer vision as easy as, say, YOLO.

Where to Start?

We've made it easy to train your models on custom datasets with our new YOLOv5 Colab notebook. To get started, follow the steps below:

1. Open the YOLOv5 custom training Colab notebook
2. pip install roboflow to begin using your Roboflow datasets
3. Export your project from Roboflow in your desired format
4. A code snippet will be generated for custom training
5. Copy/paste the snippet from your account into the designated spot in the notebook

Voilà!

‍

You can find more useful information on the following Roboflow video tutorial.

An Exciting Time to be in the Field of Computer Vision  

The combination of Roboflow's newest features with the strengths of YOLOv5 makes for an incredibly powerful MLOps solution. We’re excited for the possibilities that Ultralytics and Roboflow are opening up through our shared vision of easy AI, and can't wait to see what our users create using our new integration.

We're looking forward to hearing about the breakthroughs that our developer community will achieve!

‍