Jacob Solawetz

10 Jul 2020 • 5 min read

In this post, we walk through how to download data from Supervise.ly and convert Supervise.ly annotations to YOLO Darknet format specifically, and more generally convert Supervisely JSON to any other object detection annotation format for use in any of your custom computer vision models. This guide is imperative

1 Jul 2020 • 6 min read

Learn how to train a YOLOv4-tiny model on a custom dataset.

18 Jun 2020 • 4 min read

We are excited to announce integration with the Open Images Dataset and the release of two new public datasets encapsulating subdomains of the Open Images Dataset: Vehicles Object Detection [https://public.roboflow.ai/object-detection/vehicles-openimages] and Shellfish Object Detection [https://public.roboflow.ai/object-detection/shellfish-openimages]. In this post, we will

12 Jun 2020 • 16 min read

We appreciate the machine learning community's feedback, and we're publishing additional details on our methodology. (Note: On June 14, we've incorporated updates from YOLOv4 author Alexey Bochkovskiy, YOLOv5 author Glenn Jocher, and others in the community.) Don't care about the controversy? Skip

10 Jun 2020 • 4 min read

Less than 50 days after the release YOLOv4, YOLOv5 improves accessibility for realtime object detection. June 29, YOLOv5 has released the first official version of the repository. We wrote a new deep dive on YOLOv5. June 12, 8:08 AM CDT Update: In response to to community feedback, we have

2 Jun 2020 • 7 min read

Data augmentation in computer vision is not new, but recently data augmentation has emerged on the forefront of state of the art modeling. YOLOv4, a new state of the art image detection model, uses a variety of data augmentation techniques to boost the models performance on COCO, a popular image

4 May 2020 • 5 min read

In May 2016, Joshua Brown died in the Tesla's first autopilot crash [https://news.sky.com/story/tesla-driver-in-first-self-drive-fatal-crash-10330121] . The crash was attributed to the self-driving cars system not recognizing the difference between a truck and the bright sky above it. The system did not recognize the difference between

1 May 2020 • 6 min read

YOLOv3 [https://models.roboflow.ai/object-detection/yolo-v3-pytorch] is known to be an incredibly performant, state-of-the-art model architecture: fast, accurate, and reliable. So how does the "new kid on the block," EfficientDet [https://blog.roboflow.com/breaking-down-efficientdet/], compare? Without spoilers, we were surprised by these results. NOTE: YOLO v5

22 Apr 2020 • 7 min read

In this post, we do a deep dive into the neural magic of EfficientDet [https://models.roboflow.ai/object-detection/efficientdet] for object detection [https://models.roboflow.ai/object-detection], focusing on the model's motivation, design, and architecture. Recently, the Google Brain team published [https://arxiv.org/abs/1911.09070]

13 Apr 2020 • 5 min read

Learn how to train an EfficientDet object detection model with a custom dataset.