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## Prepare pretrained model
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If you use origin ResNet, you do not need to do anything. But if you want to use ResNet_ibn, you need to download pretrain model in [here](https://drive.google.com/open?id=1thS2B8UOSBi_cJX6zRy6YYRwz_nVFI_S). And then you can put it in `~/.cache/torch/checkpoints` or anywhere you like.
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If you use origin ResNet, you do not need to do anything. But if you want to use ResNet-ibn or ResNeSt, you need to download pretrain model in [here](https://drive.google.com/open?id=1thS2B8UOSBi_cJX6zRy6YYRwz_nVFI_S).
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And then you need to put it in `~/.cache/torch/checkpoints` or anywhere you like.
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Then you should set the pretrain model path in `configs/Base-bagtricks.yml`.
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# Installation
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## Requirements
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- Linux or macOS with python ≥ 3.6
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- PyTorch ≥ 1.0
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- torchvision that matches the Pytorch installation. You can install them together at [pytorch.org]() to make sure of this.
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- [yacs](https://github.com/rbgirshick/yacs)
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- Cython (optional to compile evaluation)
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README.md
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# FastReID
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FastReID is a research platform that implements state-of-the-art re-identification algorithms.
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FastReID is a research platform that implements state-of-the-art re-identification algorithms. It is a groud-up rewrite of the previous verson, [reid strong baseline](https://github.com/michuanhaohao/reid-strong-baseline).
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## What's New
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- Remove [ignite](https://github.com/pytorch/ignite)(a high-level library) dependency and powered by [PyTorch](https://pytorch.org/).
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- Includes more features such as circle loss, visualizing ranklist and label, SoTA results on intra-domain, cross-domain and partial reid, testing on multi-datasets at the same time, etc.
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- Can be used as a library to support [different projects](https://github.com/JDAI-CV/fast-reid/tree/master/projects) on top of it. We'll open source more research projects in this way.
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- It trains much faster.
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See our [zhihu blog]() to learn more about fastreid.
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## Installation
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See [INSTALL.md](https://github.com/JDAI-CV/fast-reid/blob/master/INSTALL.md).
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## Quick Start
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The designed architecture follows this guide [PyTorch-Project-Template](https://github.com/L1aoXingyu/PyTorch-Project-Template), you can check each folder's purpose by yourself.
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See GETTING_STARTED.md.
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See [GETTING_STARTED.md](https://github.com/JDAI-CV/fast-reid/blob/master/GETTING_STARTED.md).
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Learn more at out documentation. And see projects/ for some projects that are build on top of fastreid.
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Install dependencies:
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- [pytorch 1.0.0+](https://pytorch.org/)
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- torchvision
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- [yacs](https://github.com/rbgirshick/yacs)
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Learn more at out [documentation](). And see [projects/](https://github.com/JDAI-CV/fast-reid/tree/master/projects) for some projects that are build on top of fastreid.
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## Model Zoo and Baselines
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