PekingU/rtdetr_r101vd_coco_o365 is an object detection model hosted on Hugging Face. It belongs to the RT-DETR family of real-time detection transformers and carries the apache-2.0 license.
The model was produced by Peking University and is tagged for the coco dataset in English. It implements the vision task of object detection and draws from the paper identified by arxiv:2304.08069. Users load it through the Transformers library by importing a pipeline for object-detection or by instantiating AutoImageProcessor and AutoModelForObjectDetection classes with the repository identifier. The provided code examples demonstrate both the high-level pipeline approach and direct model loading with automatic device mapping.
Files for the model are available in safetensors format. It appears among collections of transformers for object detection and can be deployed to inference providers or copied to storage buckets on the platform.
The model is offered at no monetary cost under its open license for researchers and developers who integrate it into computer-vision pipelines or adapt it for custom use.
Rtdetr R101vd Coco O365 is an Other AI project. It focuses on running high-accuracy real-time object detection on images without training a model from scratch. Rtdetr R101vd Coco O365 is an open-source project aimed at computer vision researchers and developers. The project is open source (Apache-2.0). It runs on the web and API.
Peking University builds and maintains Rtdetr R101vd Coco O365, and it first shipped in 2023. Development happens publicly on GitHub with 5.4k stars and 3 commits in the last 90 days. Key capabilities include Object Detection, transformers, and safetensors. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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