Top Tensorflow Object Detection Models

Explore object detection models that use the TensorFlow framework.
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Deploy select models (i.e. YOLOv8, CLIP) using the Roboflow Hosted API, or your own hardware using Roboflow Inference.

Object Detection

Object Detection

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Object Detection

Object Detection

MobileNet SSD v2

Model Size:

MB

Parameters:

Architecture:

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

Jupyter notebook

Object Detection

Object Detection

Deploy on Device with Roboflow✅

Object Detection

Object Detection

Model Size:

MB

Parameters:

Architecture:

One of the most accurate object detection algorithms but requires a lot of power at inference time. A good choice if you can do processing asynchronously on a server. Learn more »

Jupyter notebook

Object Detection

Object Detection

Deploy on Device with Roboflow✅

Object Detection

Object Detection

EfficientDet (D7) Tensorflow 2

Model Size:

MB

Parameters:

77 million

Architecture:

A scalable, state of the art object detection model, implemented here within the TensorFlow 2 Object Detection API. Learn more »

Jupyter notebook

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