├── images ├── download.png ├── download (1).png ├── download (2).png ├── download (3).png ├── Screenshot from 2023-10-20 14-47-56.png ├── Screenshot from 2023-10-20 14-48-33.png ├── Screenshot from 2023-10-20 14-48-50.png └── Screenshot from 2023-10-20 14-48-56.png └── README.md /images/download.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/inuwamobarak/OWLv2/HEAD/images/download.png -------------------------------------------------------------------------------- /images/download (1).png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/inuwamobarak/OWLv2/HEAD/images/download (1).png -------------------------------------------------------------------------------- /images/download (2).png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/inuwamobarak/OWLv2/HEAD/images/download (2).png -------------------------------------------------------------------------------- /images/download (3).png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/inuwamobarak/OWLv2/HEAD/images/download (3).png -------------------------------------------------------------------------------- /images/Screenshot from 2023-10-20 14-47-56.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/inuwamobarak/OWLv2/HEAD/images/Screenshot from 2023-10-20 14-47-56.png -------------------------------------------------------------------------------- /images/Screenshot from 2023-10-20 14-48-33.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/inuwamobarak/OWLv2/HEAD/images/Screenshot from 2023-10-20 14-48-33.png -------------------------------------------------------------------------------- /images/Screenshot from 2023-10-20 14-48-50.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/inuwamobarak/OWLv2/HEAD/images/Screenshot from 2023-10-20 14-48-50.png -------------------------------------------------------------------------------- /images/Screenshot from 2023-10-20 14-48-56.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/inuwamobarak/OWLv2/HEAD/images/Screenshot from 2023-10-20 14-48-56.png -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # OWLv2 2 | Introducing OWLv2: Google's Breakthrough in Zero-Shot Object Detection 3 | 4 | 5 | # Zero-Shot Object Detection with OWLv2 6 | 7 | Zero-shot object detection is made easy with Google's OWLv2 model. 8 | 9 | ## Introduction 10 | 11 | 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. 12 | 13 | ## Getting Started 14 | 15 | To get started, you need Python and a few libraries installed. You can follow the provided code examples to set up the environment. 16 | 17 | ## Usage 18 | 19 | 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. 20 | 21 | ## Image-Guided Object Detection 22 | 23 | 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. 24 | 25 | Feel free to explore the article and leverage OWLv2 for your object detection needs! 26 | 27 | Links: 28 | 29 | https://github.com/NielsRogge 30 | 31 | https://huggingface.co/docs/transformers/main/en/model_doc/owlv2 32 | 33 | 34 | https://arxiv.org/abs/2306.09683 35 | 36 | 37 | https://huggingface.co/docs/transformers/main/en/model_doc/owlvit 38 | 39 | 40 | https://arxiv.org/abs/2205.06230 41 | 42 | Minderer, M., Gritsenko, A., & Houlsby, N. (2023). Scaling Open-Vocabulary Object Detection. ArXiv. /abs/2306.09683 43 | --------------------------------------------------------------------------------