From 21b324e8815b680e695776f312ce2049b1bcfa9f Mon Sep 17 00:00:00 2001
From: root <root@s-113-2-1.iluvatar.local>
Date: Wed, 11 Oct 2023 06:51:00 +0000
Subject: [PATCH] add efficientnet_b0

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+# EfficientNet-B0
+
+## Model description
+
+This model is the B0 version of the EfficientNet series, whitch can be used for image classification tasks, such as cat and dog classification, flower classification, and so on.
+
+## Step 1: Installation
+
+```
+git clone -b release/2.5 https://github.com/PaddlePaddle/PaddleClas.git
+
+cd PaddleClas
+pip3 install -r requirements.txt
+pip3 install paddleclas
+pip3 install protobuf==3.20.3
+yum install mesa-libGL 
+pip3 install urllib3==1.26.15
+
+```
+
+
+## Step 2: Preparing datasets
+
+Sign up and login in [ImageNet official website](https://www.image-net.org/index.php), then choose 'Download' to download the whole ImageNet dataset. 
+
+The ImageNet dataset path structure should look like:
+
+```bash
+PaddleClas/dataset/ILSVRC2012/
+├── train
+│   └── n01440764
+│       ├── n01440764_10026.JPEG
+│       └── ...
+├── train_list.txt
+├── val
+│   └── n01440764
+│       ├── ILSVRC2012_val_00000293.JPEG
+│       └── ...
+└── val_list.txt
+```
+
+## Step 3: Training
+
+```
+cd PaddleClas
+
+# 8 GPUs
+export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+
+python3 -m paddle.distributed.launch tools/train.py -c ppcls/configs/ImageNet/EfficientNet/EfficientNetB0.yaml
+
+
+# 1 GPU
+export CUDA_VISIBLE_DEVICES=0
+
+python3 tools/train.py -c ppcls/configs/ImageNet/EfficientNet/EfficientNetB0.yaml
+```
+
+## Results
+
+| Method | ips (BI x 8)  | Top1 | Top5 |
+| ------ | ----------  |--------------|--------------|
+|  EfficientNet-B0 |         |  | |
+
+## Reference
+- [PaddleClas](https://github.com/PaddlePaddle/PaddleClas/tree/release/2.5)
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