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«Non-local»复现了论文Non-local Neural Networks提出的视频分类模型
受到传统图像处理算法non-local means影响，Non-local Neural Networks提出了注意力模块Non-local Block
通过requirements.txt安装运行所需依赖
$ pip install -r requirements.txt
处理数据时需要额外安装denseflow，可以在innerlee/setup中找到安装脚本
首先设置GPU和当前位置
$ export CUDA_VISIBLE_DEVICES=1
$ export PYTHONPATH=.
- 训练
# 训练UCF101
# 单GPU
$ python tools/train.py --config_file=configs/i3d-3x3-nl_r3d50_ucf101_rgb_224x32_dense.yaml
# 多GPU
$ python tools/train.py \
--config_file=configs/i3d-3x3-nl_r3d50_ucf101_rgb_224x32_dense.yaml \
--eval_step=1000 \
--save_step=1000 \
-g=<N>
- 测试
$ python tools/test.py <config_file> <pth_file>
$ python tools/test.py configs/i3d-3x3-nl_r3d50_ucf101_rgb_224x32_dense.yaml outputs/i3d-3x3-nl_r3d50_ucf101_rgb_224x32_dense.pth
- zhujian - Initial work - zjykzj
@misc{fan2020pyslowfast,
author = {Haoqi Fan and Yanghao Li and Bo Xiong and Wan-Yen Lo and
Christoph Feichtenhofer},
title = {PySlowFast},
howpublished = {\url{https://github.com/facebookresearch/slowfast}},
year = {2020}
}
@misc{wang2018nonlocal,
title={Non-local Neural Networks},
author={Xiaolong Wang and Ross Girshick and Abhinav Gupta and Kaiming He},
year={2018},
eprint={1711.07971},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
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注意:
GIT提交，请遵守Conventional Commits规范- 语义版本化，请遵守Semantic Versioning 2.0.0规范
README编写，请遵守standard-readme规范
Apache License 2.0 © 2020 zjykzj