Models

What is EfficientDet?

EfficientDet achieves the best performance in the fewest training epochs among object detection model architectures, making it a highly scalable architecture especially when operating with limited compute.

About the model

Here is an overview of the

EfficientDet

model:

Date of Release Nov 20, 2019
Model Type Object Detection
Architecture
Framework Used PyTorch
Annotation Format COCO JSON
Stars on GitHub 1300+

What is EfficientDet?

EfficientDet is a state-of-the-art object detection model for real-time object detection originally written in Tensorflow and Keras but now having implementations in PyTorch--this notebook uses the PyTorch implementation of EfficientDet. It has an EfficientNet backbone and a custom detection and classification network. Because of this backbone, EffcientDet is designed to efficiently scale from the smallest model size. The smallest EfficientDet, EfficientDet-D0 has 4 million weight parameters - it is truly tiny. EfficientDet infers in 30ms in this distribution and is considered and can be stored with only 17 megabytes of storage--making it both a small and fast model.

EfficientDet Results

EfficientDet performed state-of-the-art on COCO when it was released and performs slightly better than YOLOv3.

EfficientDet Performance

Further Reading over EfficientDet

Training EfficientDet with Custom Data: https://blog.roboflow.com/training-efficientdet-object-detection-model-with-a-custom-dataset/

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Model Performance

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EfficientDet Annotation Format

EfficientDet

uses the

COCO JSON

annotation format. If your annotation is in a different format, you can use Roboflow's annotation conversion tools to get your data into the right format.

Convert data between formats

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