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authorManu Mathew2020-07-18 05:04:46 -0500
committerManu Mathew2020-07-18 05:04:46 -0500
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4This repository is an extension of the popular [mmdetection](https://github.com/open-mmlab/mmdetection) open source repository for object detection training. While mmdetection focuses on a wide variety of models, typically at high complexity, we focus on models that are optimized for speed and accuracy so that they run efficiently on embedded devices. 4This repository is an extension of the popular [mmdetection](https://github.com/open-mmlab/mmdetection) open source repository for object detection training. While mmdetection focuses on a wide variety of models, typically at high complexity, we focus on models that are optimized for speed and accuracy so that they run efficiently on embedded devices.
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6When we say MMDetection or mmdetection, we refer to the original repository. However, when we say Jacinto-AI-Detection or "this repository", we refer to this extension of mmdetection with speed/accuracy optimized models. 6Kindly take time to read through the original documentation of the original [mmdetection](https://github.com/open-mmlab/mmdetection) before attempting to use this repository.
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8Kindly take time to read through the original documentation of the original [mmdetection](https://github.com/open-mmlab/mmdetection) before attempting to use this repository. This repository requires mmdetection to be installed.
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10 8
11## License 9## License
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13This repository is released under the following [LICENSE](./LICENSE). 11Please see [LICENSE](./LICENSE) and [LICENSE.SPDX](./LICENSE.SPDX)
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15 13
16## Installation 14## Installation
17 15
18Please refer to [mmdetection install.md](https://github.com/open-mmlab/mmdetection/docs/install.md) for installation and dataset preparation. 16This repository requires mmdetection (mmdet Python package) to be installed. Please refer to [installation instructions for mmdetection](https://github.com/open-mmlab/mmdetection/blob/master/docs/install.md) for installation and dataset preparation. If you get any issues with the master branch of mmdetection, please try after checking out the latest release tag. Note mmdetection also requreis mmcv and several other dependencies to be installed as described in the above URL.
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20If you get any issues with the master branch of mmdetection, please try after checking out the tag **v2.1.0**
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22After installing mmdetection, please install [PyTorch-Jacinto-AI-DevKit](https://bitbucket.itg.ti.com/projects/JACINTO-AI/repos/pytorch-jacinto-ai-devkit/browse/) as our repository uses several components from there - especially to define low complexity models and to Quantization Aware Training (QAT). 18After installing mmdetection, please install [PyTorch-Jacinto-AI-DevKit](https://bitbucket.itg.ti.com/projects/JACINTO-AI/repos/pytorch-jacinto-ai-devkit/browse/) as this repository uses several components from there - especially to define low complexity models and to do Quantization Aware Training (QAT) and Calibration.
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24 20
25## Get Started 21## Get Started
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27Please see [getting_started.md](https://github.com/open-mmlab/mmdetection/docs/getting_started.md) for the basic usage of MMDetection. However, some of these may not apply to these repository. 23Please see [Getting Started with MMDetection](https://github.com/open-mmlab/mmdetection/blob/master/docs/getting_started.md) for the basic usage of mmdetection. Note: Some of these may not apply to this repository.
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29Please see [usage/instructions](https://github.com/open-mmlab/mmdetection/docs/jacinto_ai_detection_usage.md) for training and testing with this repository. 25Please see [Usage](./docs/usage.md) for training and testing with this repository.
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31 27
32## Benchmark and Model Zoo 28## Benchmark and Model Zoo
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34Several trained models with accuracy report is available at [Jacinto-AI-Detection Model Zoo](docs/jacinto_ai_detection_model_zoo.md) 30Several trained models with accuracy report is available at [Jacinto-AI-Detection Model Zoo](./docs/model_zoo.md)
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36 32
37## Quantization 33## Quantization
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39Tutorial on how to do [Quantization Aware Training in Jacinto-AI-Detection](docs/jacinto_ai_quantization_aware_training.md) in Jacinto-AI-MMDetection. 35Tutorial on how to do [Quantization Aware Training](./docs/quantization.md) in Jacinto-AI-MMDetection.
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41 37
42## Acknowledgement 38## Acknowledgement
@@ -47,7 +43,7 @@ We wish that the toolbox and benchmark could serve the growing research communit
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48## Citation 44## Citation
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50This package/toolbox is an extension of mmdetection (https://github.com/open-mmlab/mmdetection). If you use this package/toolbox or benchmark in your research, please cite that project as well. 46This package/toolbox is an extension of mmdetection (https://github.com/open-mmlab/mmdetection). If you use this repository or benchmark in your research or work, please cite the following:
51 47
52``` 48```
53@article{PyTorch-Jacinto-AI-Detection, 49@article{PyTorch-Jacinto-AI-Detection,
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74 70
75## Contact 71## Contact
76This extension of MMDetection is part of Jacinto-AI-DevKit and is maintained by the Jacinto AI team: jacinto-ai-devkit@list.ti.com 72This extension of MMDetection is part of Jacinto-AI-DevKit and is maintained by the Jacinto AI team (jacinto-ai-devkit@list.ti.com). For more details, please visit: https://github.com/TexasInstruments/jacinto-ai-devkit