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update dnmetis/README.md.

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chengchunlei
2020-10-24 18:02:32 +08:00
committed by Gitee
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@@ -6,13 +6,19 @@ pip3.7.5 setup.py install
``` ```
Details of dnmetis_backend installation can be found in backend_C++/dnmetis_backend/README.md. Notice that, you just need to install requirements once for a brand new Ai1-Inference environment。 Details of dnmetis_backend installation can be found in backend_C++/dnmetis_backend/README.md. Notice that, you just need to install requirements once for a brand new Ai1-Inference environment。
## 2.Download dataset and model(.om) ## 2.Download model(.om)
1.download Imagenet-val dataset URL: http://www.image-net.org/download-imageurls 1.download efficientnet-b8 model(.om) URL:
```
2.download efficientnet-b8 model(.om) URL: obs://hwwheel23/efficientnet-b8.om 链接：https://pan.baidu.com/s/1N-kpQoDe3NRxvjFKjAT9AA
提取码：tvg0
3.process the original Imagenet-val dataset as list: ```
Original efficientnet-b8 pb model URL:
```
链接：https://pan.baidu.com/s/1CajdSlNTh6k35RoyOn-3Ug
提取码：slqm
```
2.Imagenet-val dataset and labels in val_map.txt:
![输入图片说明](https://images.gitee.com/uploads/images/2020/0918/234302_a572d632_5418572.jpeg "无标题.jpg") ![输入图片说明](https://images.gitee.com/uploads/images/2020/0918/234302_a572d632_5418572.jpeg "无标题.jpg")
@@ -24,7 +30,7 @@ sh run_efficientnet-b8.sh
or or
python3.7 main.py --model=/data/hwwheel123/model/efficientnet-b8.om --image_size='672,672,3' --inputs='images:0' --outputs='Softmax:0' --precision=fp16 python3.7 main.py --model=./model/efficientnet-b8.om --image_size='672,672,3' --inputs='images:0' --outputs='Softmax:0' --precision=fp16
## 4.ATC offline model generate (optional): ## 4.ATC offline model generate (optional):