diff --git a/examples/vision/classification/paddleclas/sophgo/python/README.md b/examples/vision/classification/paddleclas/sophgo/python/README.md index ba64406c2..87d33162d 100644 --- a/examples/vision/classification/paddleclas/sophgo/python/README.md +++ b/examples/vision/classification/paddleclas/sophgo/python/README.md @@ -15,8 +15,11 @@ cd FastDeploy/examples/vision/classification/paddleclas/sophgo/python # Download images. wget https://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg -# Inference. -python3 infer.py --model_file ./bmodel/resnet50_1684x_f32.bmodel --config_file ResNet50_vd_infer/inference_cls.yaml --image ILSVRC2012_val_00000010.jpeg +# Inference. Need to manually set the model, configuration file and image path used for inference. +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 + +# Automatic completion of downloading data - model compilation - inference, no need to set up model, configuration file and image paths. +python3 infer.py --auto True --model '' --config_file '' --image '' # The returned result. ClassifyResult( diff --git a/examples/vision/classification/paddleclas/sophgo/python/README_CN.md b/examples/vision/classification/paddleclas/sophgo/python/README_CN.md index 2cc9e4596..d0699d638 100644 --- a/examples/vision/classification/paddleclas/sophgo/python/README_CN.md +++ b/examples/vision/classification/paddleclas/sophgo/python/README_CN.md @@ -15,8 +15,12 @@ cd FastDeploy/examples/vision/classification/paddleclas/sophgo/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 ./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( diff --git a/examples/vision/classification/paddleclas/sophgo/python/infer.py b/examples/vision/classification/paddleclas/sophgo/python/infer.py old mode 100644 new mode 100755 index 5bc84789e..7625c3ce2 --- a/examples/vision/classification/paddleclas/sophgo/python/infer.py +++ b/examples/vision/classification/paddleclas/sophgo/python/infer.py @@ -1,15 +1,15 @@ 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.") + parser.add_argument("--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( @@ -17,17 +17,86 @@ 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 +104,7 @@ 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)