Top Image Classification Models

Classify images with two lines of code. These models are ready to go, often with pre-trained weights and exports available for mobile or server-side inference.
Deploy select models (i.e. YOLOv8, CLIP) using the Roboflow Hosted API, or your own hardware using Roboflow Inference.

Frequently Asked Questions

What models are used for image classification?

There are a wide variety of models used for image classification. Popular choices of models for image classification tasks include YOLOv5, the Vision Transformer, and Resnet34.

What are the use cases for image classification?

Image classification is useful in any computer vision task where you need to assign content into one of a limited number of categories. Here are a few examples of real-world use cases for image classification:

  • Deciding whether an image contains explicit material
  • Classifying plant species
  • Identifying wildlife species
  • Tracking what types of vehicles enter a parking lot (i.e. cars, motorbikes)

What is image classification?

Image classification is a computer vision task where images are assigned a label based on their contents. Only one label is assigned per image. For example, consider a dataset that classifies tree species. One photo may be given the class “birch” and another “fir”.

Where Can I Learn More About Object Detection?

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