RetinaNet Keras uses its own annotation format where all the annotations are in a single file. Each line represents one bounding box.
Writing a script to convert your data to try one specific model can be time consuming and error-prone. Why waste the time when you can just use Roboflow to convert your data for you?
Below, learn the structure of RetinaNet Keras CSV.
0001.jpg,2694,1211,353,353,helmet
0001.jpg,1754,1449,68,68,person
0002.jpg,113,95,226,226,helmet
0003.jpg,352,114,151,151,helmet
0003.jpg,799,217,139,139,person
0004.jpg,162,126,124,124,helmetWith Roboflow supervision, an open source Python package with utilities for completing computer vision tasks, you can merge and split detections in RetinaNet Keras CSV. Read our dedicated guides to learn how to merge and split RetinaNet Keras CSV detections.
Below, see model architectures that require data in the RetinaNet Keras CSV format when training a new model.
On each page below, you can find links to our guides that show how to plot predictions from the model, and complete other common tasks like detecting small objects with the model.