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@ -112,7 +112,7 @@ The processed dataset is now open source in [AIStudio](https://aistudio.baidu.co
**Attention**: **Attention**:
1. This experiment is based on GPU:Tesla V100* 4; CPU:Inter Xeon* 32; RAM:DDR4 128GB for training and testing; 1. This experiment is based on GPU:Tesla V100* 4; CPU:Inter Xeon* 32; RAM:DDR4 128GB for training and testing;
2. The experiments are based on the above data set [Retail Product Characteristics Study Data Set] (https://aistudio.baidu.com/aistudio/datasetdetail/113685) for training and testing; 2. The experiments are based on the above data set [Retail Product Characteristics Study Data Set](https://aistudio.baidu.com/aistudio/datasetdetail/113685) for training and testing;
3. Evaluation of RP2K and other large open source data sets of retail products will be carried out soon. 3. Evaluation of RP2K and other large open source data sets of retail products will be carried out soon.
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python client.py python client.py
``` ```
- For details of the image recognition part deployment, you can see [PP-ShiTu部署](https://github.com/PaddlePaddle/PaddleClas/blob/release/2.3/docs/zh_CN/inference_deployment/python_deploy.md#%E4%B8%BB%E4%BD%93%E6%A3%80%E6%B5%8B%E3%80%81%E7%89%B9%E5%BE%81%E6%8F%90%E5%8F%96%E5%92%8C%E5%90%91%E9%87%8F%E6%A3%80%E7%B4%A2%E4%B8%B2%E8%81%94) - For details of the image recognition part deployment, you can see [PP-ShiTu Development](https://github.com/PaddlePaddle/PaddleClas/blob/release/2.3/docs/zh_CN/inference_deployment/python_deploy.md#%E4%B8%BB%E4%BD%93%E6%A3%80%E6%B5%8B%E3%80%81%E7%89%B9%E5%BE%81%E6%8F%90%E5%8F%96%E5%92%8C%E5%90%91%E9%87%8F%E6%A3%80%E7%B4%A2%E4%B8%B2%E8%81%94)
- Wechat applet - Wechat applet
Open the wechat developer tool, import the AIContainer folder under the system folder and run it Open the wechat developer tool, import the AIContainer folder under the system folder and run it