Models

What is MobileNet SSD v2?

This architecture provides good realtime results on limited compute. It's designed to run in realtime (30 frames per second) even on mobile devices.

About the model

Here is an overview of the

MobileNet SSD v2

model:

Date of Release Jan 13, 2018
Model Type Object Detection
Architecture
Framework Used TensorFlow 1.5
Annotation Format Tensorflow TFRecord
Stars on GitHub 1900+

What is MobileNetSSDv2?

MobileNetSSDv2 (MobileNet Single Shot Detector) is an object detection model with 267 layers and 15 million parameters. It provides real-time inference under compute constraints in devices like smartphones. Once trained, MobileNetSSDv2 can be stored with 63 MB, making it an ideal model to use on smaller devices.

MobileNetSSDv2 Architecture

The MobileNetSSDv2 Model essentially is a 2-part model. The first part consists of the base MobileNetV2 network with a SSD layer that classifies the detected image. In essence, the MobileNet base network acts as a feature extractor for the SSD layer which will then classify the object of interest.

MobileNetSSDv2 Architecture


Image in Courtesy of Matthijs Hollemans

MobileNetV2 Results

MobileNet V2 outperforms MobileNet V1 with higher accuracies and lower latencies.

MobileNetSSDv2 Performance

Image courtesy of Google AI

Further Reading

Training a TensorFlow MobileNet Object Detection Model with a Custom Dataset: https://blog.roboflow.ai/training-a-tensorflow-object-detection-model-with-a-custom-dataset/

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Model Performance

Explore this model on Roboflow

Deploy MobileNet SSD v2 to production

Roboflow offers a range of SDKs with which you can deploy your model to production.

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MobileNet SSD v2 Annotation Format

MobileNet SSD v2

uses the

uses the

Tensorflow TFRecord

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

Label data automatically with MobileNet SSD v2

You can automatically label a dataset using

MobileNet SSD v2

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

MobileNet SSD v2

to train a computer vision model.

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