Add PaddleSeg doc and infer.cc demo (#114)

* Update README.md

* Update README.md

* Update README.md

* Create README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Add evaluation calculate time and fix some bugs

* Update classification __init__

* Move to ppseg

* Add segmentation doc

* Add PaddleClas infer.py

* Update PaddleClas infer.py

* Delete .infer.py.swp

* Add PaddleClas infer.cc

* Update README.md

* Update README.md

* Update README.md

* Update infer.py

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Add PaddleSeg doc and infer.cc demo

* Update README.md

* Update README.md

* Update README.md

Co-authored-by: Jason <jiangjiajun@baidu.com>
This commit is contained in:
huangjianhui
2022-08-15 15:24:38 +08:00
committed by GitHub
parent 773d6bb938
commit a016ef99ce
10 changed files with 159 additions and 150 deletions

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@@ -8,22 +8,21 @@
本目录下提供`infer.py`快速完成ResNet50_vd在CPU/GPU以及GPU上通过TensorRT加速部署的示例。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/python
# 下载ResNet50_vd模型文件和测试图片
wget https://bj.bcebos.com/paddlehub/fastdeploy/ResNet50_vd_infer.tgz
tar -xvf ResNet50_vd_infer.tgz
wget https://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
#下载部署示例代码
git clone https://github.com/PaddlePaddle/FastDeploy.git
cd examples/vision/classification/paddleclas/python
# CPU推理
python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg --device cpu
python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg --device cpu --topk 1
# GPU推理
python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg --device gpu
python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg --device gpu --topk 1
# GPU上使用TensorRT推理 注意TensorRT推理第一次运行有序列化模型的操作有一定耗时需要耐心等待
python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg --device gpu --use_trt True
python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg --device gpu --use_trt True --topk 1
```
运行完成后返回结果如下所示