From 354c36d4c090337cadaa2a2fc362ef45ab345256 Mon Sep 17 00:00:00 2001 From: yunyaoXYY Date: Tue, 21 Mar 2023 03:33:07 +0000 Subject: [PATCH] update sophgo --- deploy/fastdeploy/sophgo/python/infer.py | 100 ++++++++++++++++-- docs/zh_CN/fastdeploy/sophgo/python/README.md | 6 +- 2 files changed, 96 insertions(+), 10 deletions(-) diff --git a/deploy/fastdeploy/sophgo/python/infer.py b/deploy/fastdeploy/sophgo/python/infer.py index 5bc84789..d1e7974f 100644 --- a/deploy/fastdeploy/sophgo/python/infer.py +++ b/deploy/fastdeploy/sophgo/python/infer.py @@ -1,15 +1,20 @@ import fastdeploy as fd import cv2 import os +from subprocess import run def parse_arguments(): import argparse import ast parser = argparse.ArgumentParser() - parser.add_argument("--model", required=True, help="Path of model.") parser.add_argument( - "--config_file", required=True, help="Path of config file.") + "--auto", + required=True, + help="Auto download, convert, compile and infer if True") + parser.add_argument("--model", required=True, help="Path of bmodel") + parser.add_argument( + "--config_file", required=True, help="Path of config file") parser.add_argument( "--image", type=str, required=True, help="Path of test image file.") parser.add_argument( @@ -18,16 +23,95 @@ def parse_arguments(): return parser.parse_args() +def download(): + cmd_str = 'wget https://bj.bcebos.com/paddlehub/fastdeploy/ResNet50_vd_infer.tgz' + jpg_str = 'wget https://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg' + tar_str = 'tar xvf ResNet50_vd_infer.tgz' + if not os.path.exists('ResNet50_vd_infer.tgz'): + run(cmd_str, shell=True) + if not os.path.exists('ILSVRC2012_val_00000010.jpeg'): + run(jpg_str, shell=True) + run(tar_str, shell=True) + + +def paddle2onnx(): + cmd_str = 'paddle2onnx --model_dir ResNet50_vd_infer \ + --model_filename inference.pdmodel \ + --params_filename inference.pdiparams \ + --save_file ResNet50_vd_infer.onnx \ + --enable_dev_version True' + + print(cmd_str) + run(cmd_str, shell=True) + + +def mlir_prepare(): + mlir_path = os.getenv("MODEL_ZOO_PATH") + mlir_path = mlir_path[:-13] + cmd_list = [ + 'mkdir ResNet50', 'cp -rf ' + os.path.join( + mlir_path, 'regression/dataset/COCO2017/') + ' ./ResNet50', + 'cp -rf ' + os.path.join(mlir_path, + 'regression/image/') + ' ./ResNet50', + 'cp ResNet50_vd_infer.onnx ./ResNet50/', 'mkdir ./ResNet50/workspace' + ] + for str in cmd_list: + print(str) + run(str, shell=True) + + +def onnx2mlir(): + cmd_str = 'model_transform.py \ + --model_name ResNet50_vd_infer \ + --model_def ../ResNet50_vd_infer.onnx \ + --input_shapes [[1,3,224,224]] \ + --mean 0.0,0.0,0.0 \ + --scale 0.0039216,0.0039216,0.0039216 \ + --keep_aspect_ratio \ + --pixel_format rgb \ + --output_names save_infer_model/scale_0.tmp_1 \ + --test_input ../image/dog.jpg \ + --test_result ./ResNet50_vd_infer_top_outputs.npz \ + --mlir ./ResNet50_vd_infer.mlir' + + print(cmd_str) + os.chdir('./ResNet50/workspace/') + run(cmd_str, shell=True) + os.chdir('../../') + + +def mlir2bmodel(): + cmd_str = 'model_deploy.py \ + --mlir ./ResNet50_vd_infer.mlir \ + --quantize F32 \ + --chip bm1684x \ + --test_input ./ResNet50_vd_infer_in_f32.npz \ + --test_reference ./ResNet50_vd_infer_top_outputs.npz \ + --model ./ResNet50_vd_infer_1684x_f32.bmodel' + + print(cmd_str) + os.chdir('./ResNet50/workspace') + run(cmd_str, shell=True) + os.chdir('../../') + + args = parse_arguments() -# 配置runtime，加载模型 +if (args.auto): + download() + paddle2onnx() + mlir_prepare() + onnx2mlir() + mlir2bmodel() + +# config runtime and load the model runtime_option = fd.RuntimeOption() runtime_option.use_sophgo() -model_file = args.model +model_file = './ResNet50/workspace/ResNet50_vd_infer_1684x_f32.bmodel' if args.auto else args.model params_file = "" -config_file = args.config_file - +config_file = './ResNet50_vd_infer/inference_cls.yaml' if args.auto else args.config_file +image_file = './ILSVRC2012_val_00000010.jpeg' if args.auto else args.image model = fd.vision.classification.PaddleClasModel( model_file, params_file, @@ -35,7 +119,7 @@ model = fd.vision.classification.PaddleClasModel( runtime_option=runtime_option, model_format=fd.ModelFormat.SOPHGO) -# 预测图片分类结果 -im = cv2.imread(args.image) +# predict the results of image classification +im = cv2.imread(image_file) result = model.predict(im, args.topk) print(result) diff --git a/docs/zh_CN/fastdeploy/sophgo/python/README.md b/docs/zh_CN/fastdeploy/sophgo/python/README.md index 922c11d3..258e169d 100644 --- a/docs/zh_CN/fastdeploy/sophgo/python/README.md +++ b/docs/zh_CN/fastdeploy/sophgo/python/README.md @@ -9,7 +9,6 @@ ## 2.运行部署示例 ```bash # 下载部署示例代码 -# 下载部署示例代码 git clone https://github.com/PaddlePaddle/FastDeploy.git cd FastDeploy/examples/vision/classification/paddleclas/sophgo/python @@ -23,7 +22,10 @@ cd PaddleClas/deploy/fastdeploy/sophgo/python wget https://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg # 推理转换好的模型 -python3 infer.py --model_file ./bmodel/resnet50_1684x_f32.bmodel --config_file ResNet50_vd_infer/inference_cls.yaml --image ILSVRC2012_val_00000010.jpeg +# 手动设置推理使用的模型、配置文件和图片路径 +python3 infer.py --auto False --model_file ./bmodel/resnet50_1684x_f32.bmodel --config_file ResNet50_vd_infer/inference_cls.yaml --image ILSVRC2012_val_00000010.jpeg +# 自动完成下载数据-模型编译-推理，不需要设置模型、配置文件和图片路径 +python3 infer.py --auto True --model '' --config_file '' --image '' # 运行完成后返回结果如下所示 ClassifyResult( -- GitLab