目录
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Add examples in /vision/examples/ Changes to be committed: new file: examples/classification/InceptionV3/datautils/datasets.py new file: examples/classification/InceptionV3/evalinceltionv3.py new file: examples/classification/InceptionV3/models/Inceptionv3.py new file: examples/classification/InceptionV3/rank_0/om/analyze_fail.dat new file: examples/classification/InceptionV3/traininceptionv3.py new file: examples/classification/InceptionV3/utils/loss.py new file: examples/classification/InceptionV3/utils/var_init.py new file: examples/classification/MNASNet/datautils/datasets.py new file: examples/classification/MNASNet/evalmnasnet.py new file: examples/classification/MNASNet/models/Mnasnet.py new file: examples/classification/MNASNet/rank_0/om/analyze_fail.dat new file: examples/classification/MNASNet/trainmnasnet.py new file: examples/classification/MNASNet/utils/loss.py new file: examples/classification/MNASNet/utils/var_init.py new file: examples/classification/ResNext/datautils/datasets.py new file: examples/classification/ResNext/evalresnext.py new file: examples/classification/ResNext/models/Resnext.py new file: examples/classification/ResNext/rank_0/om/analyze_fail.dat new file: examples/classification/ResNext/trainresnext.py new file: examples/classification/ResNext/utils/loss.py new file: examples/classification/ResNext/utils/var_init.py new file: examples/classification/SEResNet/datautils/datasets.py new file: examples/classification/SEResNet/evalseresnet.py new file: examples/classification/SEResNet/models/SEResNet.py new file: examples/classification/SEResNet/rank_0/om/analyze_fail.dat new file: examples/classification/SEResNet/trainseresnet.py new file: examples/classification/SEResNet/utils/loss.py new file: examples/classification/SEResNet/utils/var_init.py new file: examples/classification/ShuffleNetV1/datautils/datasets.py new file: examples/classification/ShuffleNetV1/evalshufflenetv1.py new file: examples/classification/ShuffleNetV1/models/Shufflenetv1.py new file: examples/classification/ShuffleNetV1/rank_0/om/analyze_fail.dat new file: examples/classification/ShuffleNetV1/trainshufflenetv1.py new file: examples/classification/ShuffleNetV1/utils/loss.py new file: examples/classification/ShuffleNetV1/utils/var_init.py new file: examples/classification/ShuffleNetV2/Train_shuffleNetV2.py new file: examples/classification/ShuffleNetV2/datautils/dataset2.py new file: examples/classification/ShuffleNetV2/eval.py new file: examples/classification/ShuffleNetV2/models/ShuffleNetV2.py new file: examples/classification/ShuffleNetV2/rank_0/om/analyze_fail.dat new file: examples/classification/ShuffleNetV2/src/config.py new file: examples/classification/ShuffleNetV2/src/lr_generator.py new file: examples/classification/ShuffleNetV2/utils/loss.py new file: examples/classification/ShuffleNetV2/utils/var_init.py new file: examples/classification/VggNet/datautils/datasets.py new file: examples/classification/VggNet/evalvgg.py new file: examples/classification/VggNet/models/Vggnet.py new file: examples/classification/VggNet/rank_0/om/analyze_fail.dat new file: examples/classification/VggNet/trainvgg.py new file: examples/classification/VggNet/utils/loss.py new file: examples/classification/VggNet/utils/var_init.py new file: examples/classification/alexnet/checkpoint_alexnet-graph.meta new file: examples/classification/alexnet/datautils/datasets.py new file: examples/classification/alexnet/evalalexnet.py new file: examples/classification/alexnet/models/AlexNet.py new file: examples/classification/alexnet/rank_0/om/analyze_fail.dat new file: examples/classification/alexnet/trainalexnet.py new file: examples/classification/alexnet/utils/loss.py new file: examples/classification/alexnet/utils/var_init.py new file: examples/segmentation/IOU/iou.py

2年前1077次提交
目录README.md

MindSpore Vision

LOGO.png

MindSpore Vision is an open source computer vision research toolbox based on MindSpore.

Projects in MindSpore Vision

The master branch works with MindSpore 1.5+.

Base Structure

MindSpore Vision a MindSpore base Python package that provides high-level features:

  • Base backbone of models like resnet and mobilenet series.
  • Deep neural networks work flows built on a engin system.
  • Domain oriented rich dataset interface.
  • Rich visualization and IO(Input/Output) interfaces.

BaseArchitecture.png

Installation

Please refer to get_started.md for installation.

License

This project is released under the Apache 2.0 license.

Feedbacks and Contact

The dynamic version is still under development, if you find any issue or have an idea on new features, please don’t hesitate to contact us via Gitee Issues.

Acknowledgement

MindSpore is an open source project that welcome any contribution and feedback. We wish that the toolbox and benchmark could serve the growing research community by providing a flexible as well as standardized toolkit to reimplement existing methods and develop their own new computer vision methods.

Contributing

We appreciate all contributions to improve MindSpore Vision. Please refer to CONTRIBUTING.md for the contributing guideline.

Citation

If you find this project useful in your research, please consider citing:

__special_katext_id_1__

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