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1.4 KiB
1.4 KiB
English | 简体中文
PaddleClas Python部署示例
在部署前，需确认以下两个步骤
-
- 软硬件环境满足要求，参考FastDeploy环境要求
本目录下提供infer.py快速完成 ResNet50_vd 在RKNPU上部署的示例。执行如下脚本即可完成
# 下载部署示例代码
git clone https://github.com/PaddlePaddle/FastDeploy.git
cd FastDeploy/examples/vision/classification/paddleclas/rknpu2/python
# 下载图片
wget https://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
# 推理
python3 infer.py --model_file ./ResNet50_vd_infer/ResNet50_vd_infer_rk3588.rknn --config_file ResNet50_vd_infer/inference_cls.yaml --image ILSVRC2012_val_00000010.jpeg
# 运行完成后返回结果如下所示
ClassifyResult(
label_ids: 153,
scores: 0.684570,
)
注意事项
RKNPU上对模型的输入要求是使用NHWC格式，且图片归一化操作会在转RKNN模型时，内嵌到模型中，因此我们在使用FastDeploy部署时，需要先调用DisablePermute(C++)或`disable_permute(Python)，在预处理阶段禁用数据格式的转换。