OWLv2

Introducing OWLv2: Google's Breakthrough in Zero-Shot Object Detection

Zero-Shot Object Detection with OWLv2

Zero-shot object detection is made easy with Google's OWLv2 model.

Introduction

We provide a step-by-step guide on using Google's OWLv2 model for zero-shot and image-guided object detection. OWLv2 is a powerful model capable of detecting objects in images without the need for manually annotated bounding boxes.

Getting Started

To get started, you need Python and a few libraries installed. You can follow the provided code examples to set up the environment.

Usage

Learn how to use OWLv2 for zero-shot object detection, process images, and visualize the results. The article provides code examples and explanations for each step.

Image-Guided Object Detection

Discover how to perform image-guided object detection with OWLv2. Use a single query image to detect objects in new images. The article includes code and instructions.

Feel free to explore the article and leverage OWLv2 for your object detection needs!

Links:

https://github.com/NielsRogge

https://huggingface.co/docs/transformers/main/en/model_doc/owlv2

https://arxiv.org/abs/2306.09683

https://huggingface.co/docs/transformers/main/en/model_doc/owlvit

https://arxiv.org/abs/2205.06230

Minderer, M., Gritsenko, A., & Houlsby, N. (2023). Scaling Open-Vocabulary Object Detection. ArXiv. /abs/2306.09683