chengchunlei
45 lines
1.5 KiB
Markdown
45 lines
1.5 KiB
Markdown
## 1.Install requirements：
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```
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pip3.7.5 install python-opencv
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cd backend_C++/dnmetis_backend
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pip3.7.5 setup.py install
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```
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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。
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## 2.Download model(.om)
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1.download efficientnet-b8 model(.om) URL:
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```
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链接：https://pan.baidu.com/s/1N-kpQoDe3NRxvjFKjAT9AA
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提取码：tvg0
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```
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Original efficientnet-b8 pb model URL:
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```
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链接：https://pan.baidu.com/s/1CajdSlNTh6k35RoyOn-3Ug
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提取码：slqm
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```
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2.Imagenet-val dataset and labels in val_map.txt:
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## 3.Start execute the inference:
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sh run_efficientnet-b8.sh
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or
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python3.7 main.py --model=./model/efficientnet-b8.om --image_size='672,672,3' --inputs='images:0' --outputs='Softmax:0' --precision=fp16
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## 4.ATC offline model generate (optional):
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1.download efficientnet-b8 model(.pb) URL: obs://hwwheel23/efficientnet-b8.pb
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2.atc --model=$MODEL_DIR/efficientnet-b8.pb --framework=3 --input_shape='images:1,672,672,3' --output=$MODEL_DIR/efficientnet-b8 --mode=0 --out_nodes='Softmax:0' --soc_version=Ascend310 --input_fp16_nodes=images --output_type=FP16
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## 5.Imagenet2012-val Top1 Accuracy:
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