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update version and readme (#370)
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README.md

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@@ -33,7 +33,7 @@ In NanoDet-Plus, we propose a novel label assignment strategy with a simple **as
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[NanoDet-Plus 知乎中文介绍](https://zhuanlan.zhihu.com/p/449912627)
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[NanoDet 知乎中文介绍](https://zhuanlan.zhihu.com/p/306530300)
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[NanoDet 知乎中文介绍](https://zhuanlan.zhihu.com/p/306530300)
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QQ交流群:908606542 (答案:炼丹)
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FBNetV5 | 320*640 | 30.4 | - | - | 1.8G | - | -
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MobileDet | 320*320 | 25.6 | - | - | 0.9G | - | -
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***Download pre-trained models and find more models in [Model Zoo](#model-zoo)***
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***Download pre-trained models and find more models in [Model Zoo](#model-zoo) or in [Release Files](https://github.com/RangiLyu/nanodet/releases)***
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<details>
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<summary>Notes (click to expand)</summary>
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First, install requirements and setup NanoDet following installation guide. Then download COCO pretrain weight from here
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👉[COCO pretrain weight (Google Drive)](https://drive.google.com/file/d/1ZkYucuLusJrCb_i63Lid0kYyyLvEiGN3/view?usp=sharing)
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👉[COCO pretrain weight (Google Drive)](https://github.com/RangiLyu/nanodet/releases/download/v1.0.0-alpha/nanodet-plus-m_416_checkpoint.ckpt)
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The pre-trained weight was trained by the config `config/nanodet-plus-m_416.yml`.
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* Inference images
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* Linux or MacOS
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* CUDA >= 10.0
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* Python >= 3.6
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* Pytorch >= 1.6
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* Pytorch >= 1.7
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* experimental support Windows (Notice: Windows not support distributed training before pytorch1.7)
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### Step

nanodet/__about__.py

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import time
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_this_year = time.strftime("%Y")
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__version__ = "0.4.2"
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__version__ = "1.0.0-alpha"
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__author__ = "RangiLyu"
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__author_email__ = "[email protected]"
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__license__ = "Apache-2.0"

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