DJW c16313bb6a 第一次提交 10 месяцев назад
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README.md c16313bb6a 第一次提交 10 месяцев назад
cspnext-l_8xb256-rsb-a1-600e_in1k.py c16313bb6a 第一次提交 10 месяцев назад
cspnext-m_8xb256-rsb-a1-600e_in1k.py c16313bb6a 第一次提交 10 месяцев назад
cspnext-s_8xb256-rsb-a1-600e_in1k.py c16313bb6a 第一次提交 10 месяцев назад
cspnext-tiny_8xb256-rsb-a1-600e_in1k.py c16313bb6a 第一次提交 10 месяцев назад
cspnext-x_8xb256-rsb-a1-600e_in1k.py c16313bb6a 第一次提交 10 месяцев назад

README.md

CSPNeXt ImageNet Pre-training

In this folder, we provide the imagenet pre-training config of RTMDet's backbone CSPNeXt.

Requirements

To train with these configs, please install MMClassification 1.x first.

Install by MIM:

mim install mmcls>=1.0.0rc0

or install by pip:

pip install mmcls>=1.0.0rc0

Prepare Dataset

To pre-train on ImageNet, you need to prepare the dataset first. Please refer to the guide.

How to Train

You can use the classification config in the same way as the detection config.

For single-GPU training, run:

python tools/train.py \
    ${CONFIG_FILE} \
    [optional arguments]

For multi-GPU training, run:

bash ./tools/dist_train.sh \
    ${CONFIG_FILE} \
    ${GPU_NUM} \
    [optional arguments]

More details can be found in user guides.

Results and Models

Model resolution Params(M) Flops(G) Top-1 (%) Top-5 (%) Download
CSPNeXt-tiny 224x224 2.73 0.34 69.44 89.45 model
CSPNeXt-s 224x224 4.89 0.66 74.41 92.23 model
CSPNeXt-m 224x224 13.05 1.93 79.27 94.79 model
CSPNeXt-l 224x224 27.16 4.19 81.30 95.62 model
CSPNeXt-x 224x224 48.85 7.76 82.10 95.69 model