Top Tensorflow Object Detection Models

Explore object detection models that use the TensorFlow framework.

Deploy select models (i.e. YOLOv8, CLIP) using the Roboflow Hosted API, or your own hardware using Roboflow Inference.

Object Detection
Object Detection
Deploy on Device with Roboflow✅
Object Detection
Object Detection

Model Size:

MB

Parameters:

Top FPS:

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 »
Object Detection
Object Detection
Deploy on Device with Roboflow✅
Object Detection
Object Detection

Model Size:

MB

Parameters:

Top FPS:

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 »
Object Detection
Object Detection
Deploy on Device with Roboflow✅
Object Detection
Object Detection

Model Size:

MB

Parameters:

77 million

Top FPS:

8

Architecture:

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

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