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docs: update

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gaotingquan 2022-06-07 11:49:27 +00:00
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docs/en/inference_deployment/whl_deploy_en.md
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@ -212,14 +212,14 @@ You can save the prediction result(s) as pre-label, only need to use `pre_label_
```python ```python
from paddleclas import PaddleClas from paddleclas import PaddleClas
clas = PaddleClas(model_name='ResNet50', save_dir='./output_pre_label/') clas = PaddleClas(model_name='ResNet50', save_dir='./output_pre_label/')
infer_imgs = 'docs/images/inference_deployment/whl_' # it can be infer_imgs folder path which contains all of images you want to predict. infer_imgs = 'docs/images/' # it can be infer_imgs folder path which contains all of images you want to predict.
result=clas.predict(infer_imgs) result=clas.predict(infer_imgs)
print(next(result)) print(next(result))
``` ```
* CLI * CLI
```bash ```bash
paddleclas --model_name='ResNet50' --infer_imgs='docs/images/inference_deployment/whl_' --save_dir='./output_pre_label/' paddleclas --model_name='ResNet50' --infer_imgs='docs/images/' --save_dir='./output_pre_label/'
``` ```
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docs/zh_CN/inference_deployment/whl_deploy.md
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@ -212,14 +212,14 @@ print(next(result))
```python ```python
from paddleclas import PaddleClas from paddleclas import PaddleClas
clas = PaddleClas(model_name='ResNet50', save_dir='./output_pre_label/') clas = PaddleClas(model_name='ResNet50', save_dir='./output_pre_label/')
infer_imgs = 'docs/images/whl/' # it can be infer_imgs folder path which contains all of images you want to predict. infer_imgs = 'docs/images/' # it can be infer_imgs folder path which contains all of images you want to predict.
result=clas.predict(infer_imgs) result=clas.predict(infer_imgs)
print(next(result)) print(next(result))
``` ```
* CLI * CLI
```bash ```bash
paddleclas --model_name='ResNet50' --infer_imgs='docs/images/whl/' --save_dir='./output_pre_label/' paddleclas --model_name='ResNet50' --infer_imgs='docs/images/' --save_dir='./output_pre_label/'
``` ```
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