This is crucial for anyone wanting to use FalconEditor for their own projects. We will also be hosting a free photogrammetry course that uses a free workflow, independent of OS specifications, to create robust digital twins. These 2 lessons complement each other incredibly well. Sign up for the course here! https://docs.google.com/forms/d/e/1FAIpQLSd2WsKaa1CjRM89uv3LNkZXj1TUNWrNxDrtyWny2w1OQDHn8g/viewform
We’ve uploaded our Cheerios Detector model- a YOLOv8 model trained using synthetic data to recognize cereal boxes in indoor environments. But we know you can make it even more robust! 💡
See the model in action in our “Cheerios detector” space, and then take it a step further by using FalconEditor to create custom synthetic data.
With FalconEditor, you can generate complex, targeted data that will enhance your model's performance and make it even more accurate, adaptable, and robust! 🧠✨
Don’t just use the data — improve it! Create unique scenarios, train for rare edge cases, and employ tailored conditions that push the boundaries of AI training.
Training YOLO with Synthetic Data from Duality AI's Falcon Simulation Software 🎮📊 Hello again! 👋 Duality.ai has released a second Google Colab and tutorial for training a YOLOv8 model using synthetic data from our Falcon simulation software!
Train using synthetic images of a soup can twin this time, and see it work on real-world images. 🥫🍜 The tutorial also walks you through how to add your own twin from our FalconCloud library, and our goal is to equip people like you to be able to create your own data for your own projects.
You'll have to create a free account to access the files, but once you do, you'll have access to not only this colab file, but also all of our lessons and our digital twin library. 🎓
This method is a game-changer for cost-effective, scalable, and customizable datasets in computer vision.
Why Synthetic Data?🤔 - Precise Annotations: Get bounding boxes, segmentation masks, and more without manual effort. - Customizable Scenarios: Get comprehensive data and cover all corner cases by simulating diverse conditions like lighting, weather, visual occlusions, and more.
What’s in the Notebook?📓 - Training & Evaluation: Train YOLOv8 with synthetic data and test its performance on real-world samples.
Let’s Discuss!💬 Check out our discord to see how people are using the Falcon simulation software to develop strong datasets and train robust models. https://discord.com/invite/dualityfalconcommunity
Training YOLO with Synthetic Data from Duality AI's Falcon🎮📊 Hi Huggingface community! 👋 Duality.ai is excited to share a Google Colab notebook that demonstrates how easy it is to train YOLOv8 using synthetic data generated in our Falcon simulation software—and see it work in the real world!
This method is a game-changer for cost-effective, scalable, and customizable datasets in computer vision. Why Synthetic Data?🤔 - Precise Annotations: Get bounding boxes, segmentation masks, and more without manual effort. - Customizable Scenarios: Simulate diverse conditions like lighting and weather. What’s in the Notebook?📓 - Training & Evaluation: Train YOLOv8 with synthetic data and test its performance on real-world samples. Try it Out! 🚀 Access the notebook here: https://storage.googleapis.com/duality-public-share/syntheticDataWorks.ipynb It’s fully documented and ready for you to explore and adapt.