From aa417b15332c548de9e3d1bc06b5c67bb52c9e1b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E8=8C=83=E7=A8=8B?= <568994792@qq.com> Date: Thu, 10 Nov 2022 07:50:32 +0000 Subject: [PATCH] add ACL_PyTorch/contrib/cv/segmentation/Swin-Transformer-Semantic-Segmentation. MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Signed-off-by: 范程 <568994792@qq.com> --- .../Swin-Transformer-Semantic-Segmentation | 13 +++++++++++++ 1 file changed, 13 insertions(+) create mode 100644 ACL_PyTorch/contrib/cv/segmentation/Swin-Transformer-Semantic-Segmentation diff --git a/ACL_PyTorch/contrib/cv/segmentation/Swin-Transformer-Semantic-Segmentation b/ACL_PyTorch/contrib/cv/segmentation/Swin-Transformer-Semantic-Segmentation new file mode 100644 index 0000000000..096f12667a --- /dev/null +++ b/ACL_PyTorch/contrib/cv/segmentation/Swin-Transformer-Semantic-Segmentation @@ -0,0 +1,13 @@ +1.性能对比 +在 310P 设备上,当 batchsize 为 1 时模型性能为 19.33 fps. +| batchsize | T4性能 | 310P性能 | 310P/T4 | +|-----------|---------- |----------- |-----------| +| 1 | 1.72 fps | 19.33 fps | 11.23倍 | + +注:当 batchsize 为 4 或更高时,因内存不足导致推理失败,无法获取性能数据。 + +2.精度对比 +自测了 batchsize 为 1 精度,比开源仓精度的高。 +| Model | batchsize | mIoU(NPU) | mIoU(开源)| +|----------------------------------------|-----------|-----------|----------| +| Swin-Transformer-Semantic-Segmentation | 1 | 48.06% | 47.64% | \ No newline at end of file -- Gitee