If your labeling tool exported annotations in theCOCO
format, but you’re trying to use a
model that needsYOLO Darknet
annotations, we’ve got you covered. You can convert those in 3 clicks with Roboflow.
Roboflow is the universal conversion tool for computer vision annotation formats. The Public plan is the best way for those exploring personal projects, class assignments, and other experiments to try Roboflow. To convert your dataset, start by creating a workspace on the Public plan.
Once your account has been created, click Create Dataset.
To learn how to create COCO JSON yourself from scratch, see our CVAT (object detection annotation tool) tutorial.
Next, you can choose Preprocessing and Augmentation options for your dataset version and then click Generate.
After generating, you will be prompted to Export your dataset. You can choose to receive your dataset as a .zip file or a curl download link. You can also choose which format you would like to export. Choose
YOLO Darknet TXT
Congratulations, you have successfully converted your dataset from
YOLO Darknet TXT
Ready to use your new
You might be looking to use YOLOv4 on your own dataset.
Here are some compatible models:
Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. PyTorch version.
YOLOv4 has emerged as the best real time object detection model. YOLOv4 carries forward many of the research contributions of the YOLO family of models along with new modeling and data augmentation techniques. This implementation is in Darknet.