Try the Model

Use the widget below to experiment with EfficientDet. You can detect COCO classes such as people, vehicles, animals, household items.

Overview

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 License

EfficientDet

is licensed under a

Apache-2.0

license.

Performance

Deploy a EfficientDet API

You can use Roboflow Inference to deploy a

EfficientDet

API on your hardware. You can deploy the model on CPU (i.e. Raspberry Pi, AI PCs) and GPU devices (i.e. NVIDIA Jetson, NVIDIA T4).

Below are instructions on how to deploy your own model API.

Label Data Automatically with EfficientDet

You can automatically label a dataset using EfficientDet with help from Autodistill, an open source package for training computer vision models. You can label a folder of images automatically with only a few lines of code. Below, see our tutorials that demonstrate how to use EfficientDet to train a computer vision model.

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