add pagenet 310 infer

research/cv/PAGENet/README.md

@@ -88,6 +88,7 @@ PAGE-Net网络由三个部分组成，提取特征的CNN模块，金字塔注意
         │   ├── run_distribute_train_gpu.sh  # 多卡训练脚本文件(gpu)
         │   ├── run_distribute_train.sh      # 多卡训练脚本文件(ascend)
         │   ├── run_eval.sh                  # 评估脚本文件(ascend & gpu)
+        │   ├── run_infer_310.sh             # 评估脚本文件(ascend 310)
         ├── src
         |   ├── model_utils
         |   |   ├── config.py
@@ -99,10 +100,13 @@ PAGE-Net网络由三个部分组成，提取特征的CNN模块，金字塔注意
         │   ├── train_loss.py                # 损失定义
         |   ├── MyTrainOneStep.py            # 定义训练网络封装类
         |   ├── vgg.py                       # 定义vgg
+        ├── ascend310_infer                  # 310推理
         ├── train.py                         # 训练脚本
         ├── eval.py                          # 评估脚本
         ├── export.py                        # 模型导出脚本
         ├── requirements.txt                 # 需求文档
+        ├── preprocess.py                    # 预处理
+        ├── postprocess.py                   # 后处理
 ```
 
 ### 脚本参数
@@ -158,6 +162,19 @@ bash scripts/eval.sh [DEVICE_ID] [CONFIG_PATH] #运行推理
 python export.py --config_path=[CONFIG_PATH]  #导出mindir，模型文件路径为config中的ckpt_file
 ```
 
+```text
+成功导出模型之后，执行以下指令进行310推理
+首先需修改default_config_ascend.yaml文件：
+1. 修改test_img_path为推理数据集原图的路径
+2. 修改test_gt_path为推理数据集MASK的路径
+3. 修改batchsize为1
+执行推理指令如下：
+```
+
+```bash
+bash run_infer_310.sh [MINDIR_PATH] [CONFIG_PATH] [DEVICE_ID]
+```
+
 ## 模型描述
 
 ### 评估性能
@@ -232,4 +249,4 @@ python export.py --config_path=[CONFIG_PATH]  #导出mindir，模型文件路径
 
 ## ModelZoo主页
 
-请浏览官网[主页](https://gitee.com/mindspore/models)。
\ No newline at end of file
+请浏览官网[主页](https://gitee.com/mindspore/models)。

research/cv/PAGENet/ascend310_infer/CMakeLists.txt

+cmake_minimum_required(VERSION 3.14.1)
+project(Ascend310Infer)
+add_compile_definitions(_GLIBCXX_USE_CXX11_ABI=0)
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O2 -g -std=c++17 -Werror -Wall -fPIE -Wl,--allow-shlib-undefined")
+set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR}/)
+option(MINDSPORE_PATH "mindspore install path" "")
+include_directories(${MINDSPORE_PATH})
+include_directories(${MINDSPORE_PATH}/include)
+include_directories(${PROJECT_SRC_ROOT})
+find_library(MS_LIB libmindspore.so ${MINDSPORE_PATH}/lib)
+file(GLOB_RECURSE MD_LIB ${MINDSPORE_PATH}/_c_dataengine*)
+
+add_executable(main src/main.cc src/utils.cc)
+target_link_libraries(main ${MS_LIB} ${MD_LIB} gflags)
+find_package(gflags REQUIRED)
\ No newline at end of file

research/cv/PAGENet/ascend310_infer/build.sh

+#!/bin/bash
+# Copyright 2022 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+if [ -d out ]; then
+    rm -rf out
+fi
+
+mkdir out
+cd out || exit
+
+if [ -f "Makefile" ]; then
+  make clean
+fi
+
+cmake .. \
+    -DMINDSPORE_PATH="`pip show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`"
+make

research/cv/PAGENet/ascend310_infer/inc/utils.h

+/**
+ * Copyright 2022 Huawei Technologies Co., Ltd
+ * 
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ * 
+ * http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef MINDSPORE_INFERENCE_UTILS_H_
+#define MINDSPORE_INFERENCE_UTILS_H_
+
+#include <sys/stat.h>
+#include <dirent.h>
+#include <vector>
+#include <string>
+#include <memory>
+#include "include/api/types.h"
+
+std::vector<std::string> GetAllFiles(std::string_view dirName);
+DIR *OpenDir(std::string_view dirName);
+std::string RealPath(std::string_view path);
+mindspore::MSTensor ReadFileToTensor(const std::string &file);
+int WriteResult(const std::string& imageFile, const std::vector<mindspore::MSTensor> &outputs);
+#endif

research/cv/PAGENet/ascend310_infer/src/main.cc

+/**
+ * Copyright 2022 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include <dirent.h>
+#include <gflags/gflags.h>
+#include <sys/time.h>
+#include <algorithm>
+#include <fstream>
+#include <iosfwd>
+#include <iostream>
+#include <sstream>
+#include <string>
+#include <vector>
+
+#include "inc/utils.h"
+#include "include/api/context.h"
+#include "include/api/model.h"
+#include "include/api/serialization.h"
+#include "include/api/types.h"
+#include "include/dataset/execute.h"
+#include "include/dataset/vision.h"
+
+using mindspore::Context;
+using mindspore::GraphCell;
+using mindspore::kSuccess;
+using mindspore::Model;
+using mindspore::ModelType;
+using mindspore::MSTensor;
+using mindspore::Serialization;
+using mindspore::Status;
+using mindspore::dataset::Execute;
+
+DEFINE_string(mindir_path, "", "mindir path");
+DEFINE_string(input_path, ".", "input path");
+DEFINE_int32(device_id, 0, "device id");
+
+int main(int argc, char **argv) {
+  gflags::ParseCommandLineFlags(&argc, &argv, true);
+  if (RealPath(FLAGS_mindir_path).empty()) {
+    std::cout << "Invalid mindir" << std::endl;
+    return 1;
+  }
+
+  auto context = std::make_shared<Context>();
+  auto ascend310 = std::make_shared<mindspore::Ascend310DeviceInfo>();
+  ascend310->SetDeviceID(FLAGS_device_id);
+  context->MutableDeviceInfo().push_back(ascend310);
+  mindspore::Graph graph;
+  Serialization::Load(FLAGS_mindir_path, ModelType::kMindIR, &graph);
+
+  Model model;
+  Status ret = model.Build(GraphCell(graph), context);
+  if (ret != kSuccess) {
+    std::cout << "ERROR: Build failed." << std::endl;
+    return 1;
+  }
+  std::vector<MSTensor> model_inputs = model.GetInputs();
+  if (model_inputs.empty()) {
+    std::cout << "Invalid model, inputs is empty." << std::endl;
+    return 1;
+  }
+  auto input_files = GetAllFiles(FLAGS_input_path);
+
+  if (input_files.empty()) {
+    std::cout << "ERROR: input data empty." << std::endl;
+    return 1;
+  }
+  std::map<double, double> costTime_map;
+  size_t size = input_files.size();
+
+  for (size_t i = 0; i < size; ++i) {
+    struct timeval start = {0};
+    struct timeval end = {0};
+    double startTimeMs;
+    double endTimeMs;
+    std::vector<MSTensor> inputs;
+    std::vector<MSTensor> outputs;
+    std::cout << "Start predict input files:" << input_files[i] << std::endl;
+
+    auto input0 = ReadFileToTensor(input_files[i]);
+
+    inputs.emplace_back(model_inputs[0].Name(), model_inputs[0].DataType(),
+                        model_inputs[0].Shape(), input0.Data().get(),
+                        input0.DataSize());
+
+    gettimeofday(&start, nullptr);
+    ret = model.Predict(inputs, &outputs);
+    gettimeofday(&end, nullptr);
+    if (ret != kSuccess) {
+      std::cout << "Predict " << input_files[i] << " failed." << std::endl;
+      return 1;
+    }
+    startTimeMs = (1.0 * start.tv_sec * 1000000 + start.tv_usec) / 1000;
+    endTimeMs = (1.0 * end.tv_sec * 1000000 + end.tv_usec) / 1000;
+    costTime_map.insert(std::pair<double, double>(startTimeMs, endTimeMs));
+    WriteResult(input_files[i], outputs);
+  }
+  double average = 0.0;
+  int inferCount = 0;
+
+  for (auto iter = costTime_map.begin(); iter != costTime_map.end(); iter++) {
+    double diff = iter->second - iter->first;
+    average += diff;
+    inferCount++;
+  }
+  average = average / inferCount;
+  std::stringstream timeCost;
+  timeCost << "NN inference cost average time: " << average
+           << " ms of infer_count " << inferCount << std::endl;
+  std::cout << "NN inference cost average time: " << average
+            << "ms of infer_count " << inferCount << std::endl;
+  std::string fileName =
+      "./time_Result" + std::string("/test_perform_static.txt");
+  std::ofstream fileStream(fileName.c_str(), std::ios::trunc);
+  fileStream << timeCost.str();
+  fileStream.close();
+  costTime_map.clear();
+  return 0;
+}

research/cv/PAGENet/ascend310_infer/src/utils.cc

+/**
+ * Copyright 2022 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "inc/utils.h"
+#include <algorithm>
+#include <fstream>
+#include <iostream>
+
+using mindspore::DataType;
+using mindspore::MSTensor;
+
+std::vector<std::string> GetAllFiles(std::string_view dirName) {
+  struct dirent *filename;
+  DIR *dir = OpenDir(dirName);
+  if (dir == nullptr) {
+    return {};
+  }
+  std::vector<std::string> res;
+  while ((filename = readdir(dir)) != nullptr) {
+    std::string dName = std::string(filename->d_name);
+    if (dName == "." || dName == ".." || filename->d_type != DT_REG) {
+      continue;
+    }
+    res.emplace_back(std::string(dirName) + "/" + filename->d_name);
+  }
+  std::sort(res.begin(), res.end());
+  for (auto &f : res) {
+    std::cout << "image file: " << f << std::endl;
+  }
+  return res;
+}
+
+int WriteResult(const std::string &imageFile,
+                const std::vector<MSTensor> &outputs) {
+  std::string homePath = "./result_Files";
+  size_t outputSize;
+  std::shared_ptr<const void> netOutput;
+  netOutput = outputs[9].Data();
+  outputSize = outputs[9].DataSize();
+  int pos = imageFile.rfind('/');
+  std::string fileName(imageFile, pos + 1);
+  fileName.replace(fileName.find('.'), fileName.size() - fileName.find('.'), ".bin");
+  std::string outFileName = homePath + "/" + fileName;
+  FILE *outputFile = fopen(outFileName.c_str(), "wb");
+  fwrite(netOutput.get(), outputSize, sizeof(char), outputFile);
+  fclose(outputFile);
+  outputFile = nullptr;
+  return 0;
+}
+
+mindspore::MSTensor ReadFileToTensor(const std::string &file) {
+  if (file.empty()) {
+    std::cout << "Pointer file is nullptr" << std::endl;
+    return mindspore::MSTensor();
+  }
+
+  std::ifstream ifs(file);
+  if (!ifs.good()) {
+    std::cout << "File: " << file << " is not exist" << std::endl;
+    return mindspore::MSTensor();
+  }
+
+  if (!ifs.is_open()) {
+    std::cout << "File: " << file << "open failed" << std::endl;
+    return mindspore::MSTensor();
+  }
+
+  ifs.seekg(0, std::ios::end);
+  size_t size = ifs.tellg();
+  mindspore::MSTensor buffer(file, mindspore::DataType::kNumberTypeUInt8,
+                             {static_cast<int64_t>(size)}, nullptr, size);
+
+  ifs.seekg(0, std::ios::beg);
+  ifs.read(reinterpret_cast<char *>(buffer.MutableData()), size);
+  ifs.close();
+
+  return buffer;
+}
+
+DIR *OpenDir(std::string_view dirName) {
+  if (dirName.empty()) {
+    std::cout << " dirName is null ! " << std::endl;
+    return nullptr;
+  }
+  std::string realPath = RealPath(dirName);
+  struct stat s;
+  lstat(realPath.c_str(), &s);
+  if (!S_ISDIR(s.st_mode)) {
+    std::cout << "dirName is not a valid directory !" << std::endl;
+    return nullptr;
+  }
+  DIR *dir;
+  dir = opendir(realPath.c_str());
+  if (dir == nullptr) {
+    std::cout << "Can not open dir " << dirName << std::endl;
+    return nullptr;
+  }
+  std::cout << "Successfully opened the dir " << dirName << std::endl;
+  return dir;
+}
+
+std::string RealPath(std::string_view path) {
+  char realPathMem[PATH_MAX] = {0};
+  char *realPathRet = nullptr;
+  realPathRet = realpath(path.data(), realPathMem);
+
+  if (realPathRet == nullptr) {
+    std::cout << "File: " << path << " is not exist.";
+    return "";
+  }
+
+  std::string realPath(realPathMem);
+  std::cout << path << " realpath is: " << realPath << std::endl;
+  return realPath;
+}

research/cv/PAGENet/postprocess.py

+# Copyright 2022 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+"""post process for 310 inference"""
+import os
+import argparse
+import numpy as np
+from PIL import Image
+import mindspore.nn as nn
+
+def parse(arg=None):
+    """Define configuration of postprocess"""
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--bin_path', type=str, default='./result_Files/')
+    parser.add_argument('--mask_path', type=str, default='./preprocess_Mask_Result/')
+    parser.add_argument('--output_dir', type=str, default='./postprocess_Result/')
+    return parser.parse_args(arg)
+
+def load_bin_file(bin_file, shape=None, dtype="float32"):
+    """Load data from bin file"""
+    data = np.fromfile(bin_file, dtype=dtype)
+    if shape:
+        data = np.reshape(data, shape)
+    return data
+
+def save_bin_to_image(data, out_name):
+    """Save bin file to image arrays"""
+    pic = Image.fromarray(data)
+    pic = pic.convert('RGB')
+    pic.save(out_name)
+    print("Successfully save image in " + out_name)
+
+def scan_dir(bin_path):
+    """Scan directory"""
+    out = os.listdir(bin_path)
+    return out
+
+def sigmoid(z):
+    """sigmoid"""
+    return 1/(1 + np.exp(-z))
+
+def postprocess(args):
+    """Post process bin file"""
+    file_list = scan_dir(args.bin_path)
+    loss = nn.Loss()
+    F_score = nn.F1()
+    loss.clear()
+    total_test_step = 0
+    test_data_size = len(file_list)
+    for file_path in file_list:
+        data = load_bin_file(args.bin_path + file_path, shape=(224, 224), dtype="float32")
+        targets1 = load_bin_file(args.mask_path + file_path, shape=(224, 224), dtype="float32")
+        pre_mask = data
+        targets1 = targets1.astype(int)
+        pre_mask = pre_mask.flatten()
+        targets1 = targets1.flatten()
+        pre_mask1 = pre_mask.tolist()
+        F_pre = np.array([[1 - i, i] for i in pre_mask1])
+        F_score.update(F_pre, targets1)
+        total_test_step = total_test_step + 1
+        if total_test_step % 100 == 0:
+            print("evaling:{}/{}".format(total_test_step, test_data_size))
+    F_score_result = F_score.eval()
+    print("F-score: ", (F_score_result[0] + F_score_result[1]) / 2)
+    print("---------------eval finish------------")
+if __name__ == "__main__":
+    argms = parse()
+    postprocess(argms)

research/cv/PAGENet/preprocess.py

+# Copyright 2022 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+"""pre process for 310 inference"""
+
+import os
+from src.mind_dataloader_final import get_test_loader
+from src.model_utils.config import config
+
+def preprocess():
+    test_loader = get_test_loader(config.test_img_path, config.test_gt_path, batchsize=1, testsize=config.train_size)
+    data_iterator = test_loader.create_tuple_iterator()
+    total_test_step = 0
+    test_data_size = test_loader.get_dataset_size()
+    image_root = config.test_img_path
+    Names = []
+    for data in os.listdir(image_root):
+        name = data.split(".")[0]
+        Names.append(name)
+    Names = sorted(Names)
+    for imgs, targets in data_iterator:
+        targets1 = targets.asnumpy()
+        targets1 = targets1.astype(int)
+        file_name = Names[total_test_step]
+        data_name = os.path.join("./preprocess_Result/", file_name + ".bin")
+        mask_name = os.path.join("./preprocess_Mask_Result/", file_name + ".bin")
+        imgs.asnumpy().tofile(data_name)
+        targets.asnumpy().tofile(mask_name)
+        total_test_step = total_test_step + 1
+        if total_test_step % 100 == 0:
+            print("preprocess:{}/{}".format(total_test_step, test_data_size))
+
+if __name__ == "__main__":
+    preprocess()

research/cv/PAGENet/scripts/run_infer_310.sh

+#!/bin/bash
+# Copyright 2022 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+if [[ $# -lt 2 || $# -gt 3 ]]; then
+    echo "Usage: bash run_infer_310.sh [MINDIR_PATH] [CONFIG_FILE] [DEVICE_ID]
+    DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero"
+exit 1
+fi
+get_real_path(){
+
+  if [ "${1:0:1}" == "/" ]; then
+        echo "$1"
+    else
+        echo "$(realpath -m $PWD/$1)"
+    fi
+}
+model=$(get_real_path $1)
+config_path=$(get_real_path $2)
+device_id=0
+if [ $# == 3 ]; then
+    device_id=$3
+fi
+echo "mindir name: "$model
+echo "device id: "$device_id
+echo "config_path: "$config_path
+
+export ASCEND_HOME=/usr/local/Ascend/
+if [ -d ${ASCEND_HOME}/ascend-toolkit ]; then
+    export PATH=$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/ascend-toolkit/latest/atc/bin:$PATH
+    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/ascend-toolkit/latest/atc/lib64:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH
+    export TBE_IMPL_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe
+    export ASCEND_OPP_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp
+else
+    export ASCEND_HOME=/usr/local/Ascend/latest/
+    export PATH=$ASCEND_HOME/atc/ccec_compiler/bin:$ASCEND_HOME/atc/bin:$PATH
+    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/atc/lib64:$ASCEND_HOME/acllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH
+    export PYTHONPATH=$ASCEND_HOME/atc/python/site-packages:$PYTHONPATH
+    export ASCEND_OPP_PATH=$ASCEND_HOME/opp
+fi
+
+function preprocess_data()
+{
+    if [ -d preprocess_Result ]; then
+       rm -rf ./preprocess_Result
+    fi
+
+    if [ -d preprocess_Mask_Result ]; then
+       rm -rf ./preprocess_Mask_Result
+    fi
+    mkdir preprocess_Result
+    mkdir preprocess_Mask_Result
+    python ../preprocess.py --config_path=$config_path &> preprocess.log
+}
+function compile_app()
+{
+    cd ../ascend310_infer/ || exit
+    bash build.sh &> build.log
+}
+
+function infer()
+{
+    cd - || exit
+    if [ -d result_Files ]; then
+        rm -rf ./result_Files
+    fi
+    if [ -d time_Result ]; then
+        rm -rf ./time_Result
+    fi
+    mkdir result_Files
+    mkdir time_Result
+
+    ../ascend310_infer/out/main --mindir_path=$model --input_path=./preprocess_Result --device_id=$device_id &> infer.log
+}
+
+function post_process()
+{
+   if [ -d postprocess_Result ]; then
+       rm -rf ./postprocess_Result
+    fi
+    mkdir postprocess_Result
+    python ../postprocess.py --bin_path='./result_Files/' --mask_path='./preprocess_Mask_Result/' --output_dir='./postprocess_Result/' &> postprocess.log
+}
+
+preprocess_data
+if [ $? -ne 0 ]; then
+    echo "preprocess dataset failed"
+    exit 1
+fi
+
+compile_app
+if [ $? -ne 0 ]; then
+    echo "compile app code failed"
+    exit 1
+fi
+
+infer
+if [ $? -ne 0 ]; then
+    echo " execute inference failed"
+    exit 1
+fi
+
+post_process
+if [ $? -ne 0 ]; then
+    echo " execute post_process failed"
+    exit 1
+fi