From 59a97a9a2e1735530d15faab3610237c535cda61 Mon Sep 17 00:00:00 2001 From: "yongle.wu" Date: Wed, 15 Nov 2023 10:59:10 +0800 Subject: [PATCH] Signed-off-by: yongle.wu add Res2Net50_14w_8s for paddlepaddle link #I85WCD add Res2Net50_14w_8s for paddlepaddle --- .../Res2Net50_14w_8s/paddlepaddle/README.md | 47 +++++++++++++++++++ 1 file changed, 47 insertions(+) create mode 100644 cv/classification/Res2Net50_14w_8s/paddlepaddle/README.md diff --git a/cv/classification/Res2Net50_14w_8s/paddlepaddle/README.md b/cv/classification/Res2Net50_14w_8s/paddlepaddle/README.md new file mode 100644 index 000000000..997d4d8aa --- /dev/null +++ b/cv/classification/Res2Net50_14w_8s/paddlepaddle/README.md @@ -0,0 +1,47 @@ +# Res2Net50_14w_8s +## Model description +Res2Net is modified from the source code of ResNet. The main function of Res2Net is to add hierarchical connections within the block and indirectly increase the receptive field while reusing the feature map. +## Step 1: Installing + +```bash +git clone -b release/2.5 https://github.com/PaddlePaddle/PaddleClas.git +cd PaddleClas +pip3 install -r requirements.txt +``` + +## Step 2: Download data + +Sign up and login in [ImageNet official website](https://www.image-net.org/index.php), then choose 'Download' to download the whole ImageNet dataset. Specify `/path/to/imagenet` to your ImageNet path in later training process. + +The ImageNet dataset path structure should look like: + +```bash +imagenet +├── train +│ └── n01440764 +│ ├── n01440764_10026.JPEG +│ └── ... +├── train_list.txt +├── val +│ └── n01440764 +│ ├── ILSVRC2012_val_00000293.JPEG +│ └── ... +└── val_list.txt +``` + +## Step 3: Run ResNeSt50 + +```bash +cd PaddleClas +# Link your dataset to default location +ln -s /path/to/imagenet ./dataset/ILSVRC2012 +export FLAGS_cudnn_exhaustive_search=True +export FLAGS_cudnn_batchnorm_spatial_persistent=True +export CUDA_VISIBLE_DEVICES=0,1,2,3 +python3 -m paddle.distributed.launch --gpus=0,1,2,3 tools/train.py -c ./ppcls/configs/ImageNet/Res2Net/Res2Net50_14w_8s.yaml -o Arch.pretrained=False -o Global.device=gpu +``` + +| GPU | FP32 | +| ----------- | ------------------------------------ | +| 4 cards | Acc@1= | + -- Gitee