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huolongshe 9ea6b81f93 | 1 month ago | |
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app | 2 months ago | |
demo_data | 2 months ago | |
docs | 2 months ago | |
.gitignore | 2 months ago | |
Dockerfile | 2 months ago | |
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README.md | 2 months ago | |
application.yml | 1 month ago | |
build-docker.sh | 2 months ago | |
pack_model.py | 2 months ago | |
pip-install-reqs.sh | 2 months ago | |
requirements.txt | 2 months ago | |
run_model_server.py | 2 months ago |
Deformable DEtection TRansformer (DETR), with box refinement trained end-to-end on COCO 2017 object detection (118k annotated images).
It was introduced in the paper Deformable DETR: Deformable Transformers for End-to-End Object Detection by Zhu et al. and first released in this repository.
模型来源: https://hf-mirror.com/SenseTime/deformable-detr-with-box-refine
本模型基于 ServiceBoot微服务引擎 进行服务化封装,参见: 《CubeAI模型开发指南》
$ sh pip-install-reqs.sh
$ serviceboot start
或
$ python3 run_model_server.py
一键式本地容器化部署和运行,参见: 《CubeAI模型独立部署指南》 或 CubeAI Docker Builder
本模型服务可一键发布至 CubeAI智立方平台 进行共享和部署,参见: 《CubeAI模型发布指南》
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Python Shell Dockerfile Text
Dear OpenI User
Thank you for your continuous support to the Openl Qizhi Community AI Collaboration Platform. In order to protect your usage rights and ensure network security, we updated the Openl Qizhi Community AI Collaboration Platform Usage Agreement in January 2024. The updated agreement specifies that users are prohibited from using intranet penetration tools. After you click "Agree and continue", you can continue to use our services. Thank you for your cooperation and understanding.
For more agreement content, please refer to the《Openl Qizhi Community AI Collaboration Platform Usage Agreement》