mmgeneration
mmdeploy
mmgeneration | mmdeploy | |
---|---|---|
2 | 4 | |
1,806 | 2,524 | |
1.5% | 2.5% | |
2.4 | 7.9 | |
8 months ago | about 1 month ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
mmgeneration
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMGeneration: OpenMMLab image and video generative models toolbox.
- Defect Detection using RPI
mmdeploy
- [D] Object detection models that can be easily converted to CoreML
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Orange Pi 5 Plus Koboldcpp Demo (MPT, Falcon, Mini-Orca, Openllama)
The RK3588 also has a NPU for accelerating neural networks. The bad news is the API is not supported by any of the inference engines (afaik), but the NPU can run models directly that have been converted to the RKNN format. It is a long shot, but you can find details here.
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MMDeploy: Deploy All the Algorithms of OpenMMLab
BibTeX @misc{=mmdeploy, title={OpenMMLab's Model Deployment Toolbox.}, author={MMDeploy Contributors}, howpublished = {\url{https://github.com/open-mmlab/mmdeploy}}, year={2021} }
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Removing the bounding box generated by OnnxRuntime segmentation
I have a semantic segmentation model trained using the mmdetection repo. Then it is converted to the ONNX format using the mmdeploy repo.
What are some alternatives?
anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
FastDeploy - ⚡️An Easy-to-use and Fast Deep Learning Model Deployment Toolkit for ☁️Cloud 📱Mobile and 📹Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models with end-to-end optimization, multi-platform and multi-framework support.
mmrotate - OpenMMLab Rotated Object Detection Toolbox and Benchmark
mmflow - OpenMMLab optical flow toolbox and benchmark
mim - MIM Installs OpenMMLab Packages
mmfewshot - OpenMMLab FewShot Learning Toolbox and Benchmark
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
mmdetection - OpenMMLab Detection Toolbox and Benchmark
rich-text-to-image - Rich-Text-to-Image Generation
mmpretrain - OpenMMLab Pre-training Toolbox and Benchmark
mmtracking - OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.