rtdetr-onnxruntime-deploy | project showcases the deployment of the RT-DETR model

 by   CVHub520 C++ Version: v1.0.0 License: MIT

kandi X-RAY | rtdetr-onnxruntime-deploy Summary

kandi X-RAY | rtdetr-onnxruntime-deploy Summary

rtdetr-onnxruntime-deploy is a C++ library. rtdetr-onnxruntime-deploy has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

This project showcases the deployment of the RT-DETR model using ONNXRUNTIME in C++ and Python.
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              rtdetr-onnxruntime-deploy has a low active ecosystem.
              It has 4 star(s) with 1 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              rtdetr-onnxruntime-deploy has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of rtdetr-onnxruntime-deploy is v1.0.0

            kandi-Quality Quality

              rtdetr-onnxruntime-deploy has no bugs reported.

            kandi-Security Security

              rtdetr-onnxruntime-deploy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              rtdetr-onnxruntime-deploy is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              rtdetr-onnxruntime-deploy releases are available to install and integrate.
              Installation instructions, examples and code snippets are available.

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            rtdetr-onnxruntime-deploy Key Features

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            rtdetr-onnxruntime-deploy Examples and Code Snippets

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            Vulnerabilities

            No vulnerabilities reported

            Install rtdetr-onnxruntime-deploy

            Modify the configuration file [PaddleDetection/configs/rtdetr/base/rtdetr_r50vd.yml]:
            Modify the processing code according to the illustration [PaddleDetection/ppdet/modeling/architectures/detr.py]:

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          • HTTPS

            https://github.com/CVHub520/rtdetr-onnxruntime-deploy.git

          • CLI

            gh repo clone CVHub520/rtdetr-onnxruntime-deploy

          • sshUrl

            git@github.com:CVHub520/rtdetr-onnxruntime-deploy.git

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