!2609 add new model pcb to model_zoo

Merge pull request !2609 from gdm/master

research/cv/pcb/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} -O0 -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)

research/cv/pcb/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
+  mkdir out
+fi
+cd out || exit
+cmake .. \
+    -DMINDSPORE_PATH="`pip show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`"
+make

research/cv/pcb/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"
+
+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&, const std::vector<mindspore::MSTensor>&, const std::string&);
+std::vector<std::string> GetAllFiles(std::string_view dir_name);
+
+#endif

research/cv/pcb/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 <sys/time.h>
+#include <gflags/gflags.h>
+#include <dirent.h>
+#include <iostream>
+#include <string>
+#include <algorithm>
+#include <iosfwd>
+#include <vector>
+#include <fstream>
+#include <sstream>
+
+#include "include/api/model.h"
+#include "include/api/context.h"
+#include "include/api/types.h"
+#include "include/api/serialization.h"
+#include "include/dataset/vision_ascend.h"
+#include "include/dataset/execute.h"
+#include "include/dataset/transforms.h"
+#include "include/dataset/vision.h"
+#include "inc/utils.h"
+
+using mindspore::dataset::vision::Decode;
+using mindspore::dataset::vision::Resize;
+using mindspore::dataset::vision::CenterCrop;
+using mindspore::dataset::vision::Normalize;
+using mindspore::dataset::vision::HWC2CHW;
+using mindspore::dataset::TensorTransform;
+using mindspore::Context;
+using mindspore::Serialization;
+using mindspore::Model;
+using mindspore::Status;
+using mindspore::ModelType;
+using mindspore::GraphCell;
+using mindspore::kSuccess;
+using mindspore::MSTensor;
+using mindspore::dataset::Execute;
+
+DEFINE_string(mindir_path, "", "mindir path");
+DEFINE_string(query_image_path, "", "query image path");
+DEFINE_string(gallery_image_path, "", "gallery image 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;
+    }
+    auto query_image_files = GetAllFiles(FLAGS_query_image_path);
+    if (query_image_files.empty()) {
+        std::cout << "ERROR: no query data." << std::endl;
+        return 1;
+    }
+    auto gallery_image_files = GetAllFiles(FLAGS_gallery_image_path);
+    if (gallery_image_files.empty()) {
+        std::cout << "ERROR: no gallery data." << std::endl;
+        return 1;
+    }
+    std::vector<MSTensor> modelInputs = model.GetInputs();
+    std::map<double, double> costTime_map;
+    size_t query_size = query_image_files.size();
+    size_t gallery_size = gallery_image_files.size();
+    std::string query_saveDir = "./query_result_files";
+    std::string gallery_saveDir = "./gallery_result_files";
+    for (size_t i = 0; i < query_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 processing query image files:" << query_image_files[i] <<std::endl;
+        MSTensor image = ReadFileToTensor(query_image_files[i]);
+        inputs.emplace_back(modelInputs[0].Name(), modelInputs[0].DataType(), modelInputs[0].Shape(),
+                            image.Data().get(), image.DataSize());
+        gettimeofday(&start, nullptr);
+        ret = model.Predict(inputs, &outputs);
+        gettimeofday(&end, nullptr);
+        if (ret != kSuccess) {
+            std::cout << "Process " << query_image_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(query_image_files[i], outputs, query_saveDir);
+    }
+    for (size_t i = 0; i < gallery_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 processing gallery files:" << gallery_image_files[i] <<std::endl;
+        MSTensor image = ReadFileToTensor(gallery_image_files[i]);
+        inputs.emplace_back(modelInputs[0].Name(), modelInputs[0].DataType(), modelInputs[0].Shape(),
+                            image.Data().get(), image.DataSize());
+        gettimeofday(&start, nullptr);
+        ret = model.Predict(inputs, &outputs);
+        gettimeofday(&end, nullptr);
+        if (ret != kSuccess) {
+            std::cout << "Process " << gallery_image_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(gallery_image_files[i], outputs, gallery_saveDir);
+    }
+    double average = 0.0;
+    int inferCount = 0;
+    for (auto iter = costTime_map.begin(); iter != costTime_map.end(); iter++) {
+        average += iter->second - iter->first;
+        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/pcb/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 <fstream>
+#include <algorithm>
+#include <iostream>
+#include "inc/utils.h"
+
+using mindspore::MSTensor;
+using mindspore::DataType;
+
+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;
+}
+
+
+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;
+}
+
+int WriteResult(const std::string& imageFile, const std::vector<MSTensor> &outputs, const std::string& saveDir) {
+  for (size_t i = 0; i < outputs.size(); ++i) {
+    size_t outputSize;
+    std::shared_ptr<const void> netOutput;
+    netOutput = outputs[i].Data();
+    outputSize = outputs[i].DataSize();
+    int pos = imageFile.rfind('/');
+    std::string fileName(imageFile, pos + 1);
+    fileName.replace(fileName.find('.'), fileName.size() - fileName.find('.'), ".bin");
+    std::string outFileName = saveDir + "/" + fileName;
+    FILE *outputFile = fopen(outFileName.c_str(), "wb");
+    fwrite(netOutput.get(), outputSize, sizeof(char), outputFile);
+    fclose(outputFile);
+    outputFile = nullptr;
+  }
+  return 0;
+}
+
+
+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/pcb/config/base_config.yaml

+# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
+
+enable_modelarts: False
+# Url for modelarts
+data_url: ""
+train_url: ""
+checkpoint_url: ""
+# Path for local
+run_distribute: False
+enable_profiling: False
+dataset_path: "/cache/dataset/"
+output_path: "/cache/output/"
+load_path: "/cache/load_checkpoint/"
+device_target: "Ascend"
+log_save_path: "./log/"
+checkpoint_save_path: "./checkpoint/"
+checkpoint_file_path: "/cache/load_checkpoint/pretrained_resnet50.ckpt"
+# =========================================================================
+
+# dataset setting
+mindrecord_dir: "./MindRecord"
+dataset_name: "cuhk03"
+batch_size: 1
+num_parallel_workers: 4
+device_num: 1
+
+# model setting
+model_name: "PCB"
+
+# optimizer setting
+learning_rate: 0.1
+lr_mult: 0.1
+decay_rate: 0.1
+momentum: 0.9
+weight_decay: 5e-4
+nesterov: True
+
+# training setting
+mode_name: "GRAPH"
+sink_mode: True
+seed: 1
+epoch_size: 10
+decay_epoch_size: 10
+warmup_epoch_size: 0
+
+# checkpoint callbacks setting
+save_checkpoint: True
+save_checkpoint_epochs: 10
+keep_checkpoint_max: 15
+
+# EvalCallBack setting
+run_eval: False
+eval_interval: 15
+eval_start_epoch: 60
+
+use_G_feature: True
+
+# Export setting
+device_id: 0
+image_height: 384
+image_width: 128
+file_name: "export_PCB_test"
+file_format: "MINDIR"
+
+# preprocess setting
+preprocess_result_path: "./preprocess_Result"  
+
+# postprocessing setting
+query_prediction_path: "./query_result_files"
+gallery_prediction_path: "./gallery_result_files"

research/cv/pcb/config/eval_PCB_cuhk03.yaml

+# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
+
+enable_modelarts: False
+# Url for modelarts
+data_url: ""
+train_url: ""
+checkpoint_url: ""
+# Path for local
+run_distribute: False
+enable_profiling: False
+dataset_path: "/cache/dataset/"
+output_path: "/cache/output/"
+load_path: "/cache/load_checkpoint/"
+device_target: "Ascend"
+log_save_path: "./log/PCB/cuhk03/eval/"
+checkpoint_save_path: ""
+checkpoint_file_path: "/cache/load_checkpoint/PCB-45_115.ckpt"
+# =========================================================================
+
+# dataset setting
+mindrecord_dir: "./MindRecord"
+dataset_name: "cuhk03"
+batch_size: 64
+num_parallel_workers: 4
+
+# model setting
+model_name: "PCB"
+use_G_feature: True

research/cv/pcb/config/eval_PCB_duke.yaml

+# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
+
+enable_modelarts: False
+# Url for modelarts
+data_url: ""
+train_url: ""
+checkpoint_url: ""
+# Path for local
+run_distribute: False
+enable_profiling: False
+dataset_path: "/cache/dataset/"
+output_path: "/cache/output/"
+load_path: "/cache/load_checkpoint/"
+device_target: "Ascend"
+log_save_path: "./log/PCB/duke/eval/"
+checkpoint_save_path: ""
+checkpoint_file_path: "/cache/load_checkpoint/PCB-60_258.ckpt"
+# =========================================================================
+
+# dataset setting
+mindrecord_dir: "./MindRecord"
+dataset_name: "duke"
+batch_size: 64
+num_parallel_workers: 4
+
+# model setting
+model_name: "PCB"
+use_G_feature: True

research/cv/pcb/config/eval_PCB_market.yaml

+# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
+
+enable_modelarts: False
+# Url for modelarts
+data_url: ""
+train_url: ""
+checkpoint_url: ""
+# Path for local
+run_distribute: False
+enable_profiling: False
+dataset_path: "/cache/dataset/"
+output_path: "/cache/output/"
+load_path: "/cache/load_checkpoint/"
+device_target: "Ascend"
+log_save_path: "./log/PCB/market/eval/"
+checkpoint_save_path: ""
+checkpoint_file_path: "/cache/load_checkpoint/PCB-60_202.ckpt"
+# =========================================================================
+
+# dataset setting
+mindrecord_dir: "./MindRecord"
+dataset_name: "market"
+batch_size: 64
+num_parallel_workers: 4
+
+# model setting
+model_name: "PCB"
+use_G_feature: True

research/cv/pcb/config/eval_RPP_cuhk03.yaml

+# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
+
+enable_modelarts: False
+# Url for modelarts
+data_url: ""
+train_url: ""
+checkpoint_url: ""
+# Path for local
+run_distribute: False
+enable_profiling: False
+dataset_path: "/cache/dataset/"
+output_path: "/cache/output/"
+load_path: "/cache/load_checkpoint/"
+device_target: "Ascend"
+log_save_path: "./log/RPP/cuhk03/eval/"
+checkpoint_save_path: ""
+checkpoint_file_path: "/cache/load_checkpoint/RPP-10_115.ckpt"
+# =========================================================================
+
+# dataset setting
+mindrecord_dir: "./MindRecord"
+dataset_name: "cuhk03"
+batch_size: 64
+num_parallel_workers: 4
+
+# model setting
+model_name: "RPP"
+use_G_feature: True

research/cv/pcb/config/eval_RPP_duke.yaml

+# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
+
+enable_modelarts: False
+# Url for modelarts
+data_url: ""
+train_url: ""
+checkpoint_url: ""
+# Path for local
+run_distribute: False
+enable_profiling: False
+dataset_path: "/cache/dataset/"
+output_path: "/cache/output/"
+load_path: "/cache/load_checkpoint/"
+device_target: "Ascend"
+log_save_path: "./log/RPP/duke/eval/"
+checkpoint_save_path: ""
+checkpoint_file_path: "/cache/load_checkpoint/RPP-40_258.ckpt"
+# =========================================================================
+
+# dataset setting
+mindrecord_dir: "./MindRecord"
+dataset_name: "duke"
+batch_size: 64
+num_parallel_workers: 4
+
+# model setting
+model_name: "RPP"
+use_G_feature: True

research/cv/pcb/config/eval_RPP_market.yaml

+# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
+
+enable_modelarts: False
+# Url for modelarts
+data_url: ""
+train_url: ""
+checkpoint_url: ""
+# Path for local
+run_distribute: False
+enable_profiling: False
+dataset_path: "/cache/dataset/"
+output_path: "/cache/output/"
+load_path: "/cache/load_checkpoint/"
+device_target: "Ascend"
+log_save_path: "./log/RPP/market/eval/"
+checkpoint_save_path: ""
+checkpoint_file_path: "/cache/load_checkpoint/RPP-10_202.ckpt"
+# =========================================================================
+
+# dataset setting
+mindrecord_dir: "./MindRecord"
+dataset_name: "market"
+batch_size: 64
+num_parallel_workers: 4
+
+# model setting
+model_name: "RPP"
+use_G_feature: True

research/cv/pcb/config/infer_310_config.yaml

+# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
+
+enable_modelarts: False
+# Url for modelarts
+data_url: ""
+train_url: ""
+checkpoint_url: ""
+# Path for local
+run_distribute: False
+enable_profiling: False
+dataset_path: "/cache/dataset/"
+output_path: "/cache/output/"
+load_path: "/cache/load_checkpoint/"
+device_target: "Ascend"
+log_save_path: "./log/"
+checkpoint_save_path: "./checkpoint/"
+checkpoint_file_path: "/cache/load_checkpoint/RPP-10_115.ckpt"
+# =========================================================================
+
+# dataset setting
+mindrecord_dir: "./MindRecord"
+dataset_name: "cuhk03"
+batch_size: 1
+num_parallel_workers: 4
+
+# model setting
+model_name: "RPP"
+use_G_feature: True
+
+# Export setting
+image_height: 384
+image_width: 128
+file_name: "export_RPP_cuhk03_G"
+file_format: "MINDIR"
+
+# preprocess setting
+preprocess_result_path: "./preprocess_Result"
+
+# postprocessing setting
+query_prediction_path: "./query_result_files"
+gallery_prediction_path: "./gallery_result_files"

research/cv/pcb/config/train_PCB_cuhk03/finetune_PCB.yaml

+# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
+
+enable_modelarts: False
+# Url for modelarts
+data_url: ""
+train_url: ""
+checkpoint_url: ""
+# Path for local
+run_distribute: False
+enable_profiling: False
+dataset_path: "/cache/dataset/"
+output_path: "/cache/output/"
+load_path: "/cache/load_checkpoint/"
+device_target: "Ascend"
+log_save_path: "./log/PCB/cuhk03/train"
+checkpoint_save_path: "./checkpoint/PCB/cuhk03/train"
+checkpoint_file_path: "/cache/load_checkpoint/PCB-40_115.ckpt"
+# =========================================================================
+
+# dataset setting
+mindrecord_dir: "./MindRecord"
+dataset_name: "cuhk03"
+batch_size: 64
+num_parallel_workers: 4
+device_num: 1
+
+# model setting
+model_name: "PCB"
+
+# optimizer setting
+learning_rate: 0.05
+lr_mult: 0.1
+decay_rate: 0.5
+momentum: 0.9
+weight_decay: 5e-4
+nesterov: True
+loss_scale: 1.0
+
+# training setting
+mode_name: "GRAPH"
+sink_mode: True
+seed: 1
+epoch_size: 45
+decay_epoch_size: 15
+warmup_epoch_size: 0
+
+# checkpoint callbacks setting
+save_checkpoint: True
+save_checkpoint_epochs: 45
+keep_checkpoint_max: 15
+
+# EvalCallBack setting
+run_eval: False
+eval_interval: 15
+eval_start_epoch: 60
+
+use_G_feature: True

research/cv/pcb/config/train_PCB_cuhk03/train_PCB.yaml

+# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
+
+enable_modelarts: False
+# Url for modelarts
+data_url: ""
+train_url: ""
+checkpoint_url: ""
+# Path for local
+run_distribute: False
+enable_profiling: False
+dataset_path: "/cache/dataset/"
+output_path: "/cache/output/"
+load_path: "/cache/load_checkpoint/"
+device_target: "Ascend"
+log_save_path: "./log/PCB/cuhk03/train"
+checkpoint_save_path: "./checkpoint/PCB/cuhk03/train"
+checkpoint_file_path: "/cache/load_checkpoint/pretrained_resnet50.ckpt"
+# =========================================================================
+
+# dataset setting
+mindrecord_dir: "./MindRecord"
+dataset_name: "cuhk03"
+batch_size: 64
+num_parallel_workers: 4
+device_num: 1
+
+# model setting
+model_name: "PCB"
+
+# optimizer setting
+learning_rate: 0.1
+lr_mult: 0.1
+decay_rate: 0.1
+momentum: 0.9
+weight_decay: 5e-4
+nesterov: True
+loss_scale: 1.0
+
+# training setting
+mode_name: "GRAPH"
+sink_mode: True
+seed: 1
+epoch_size: 40
+decay_epoch_size: 40
+warmup_epoch_size: 0
+
+# checkpoint callbacks setting
+save_checkpoint: True
+save_checkpoint_epochs: 40
+keep_checkpoint_max: 15
+
+# EvalCallBack setting
+run_eval: False
+eval_interval: 15
+eval_start_epoch: 60
+
+use_G_feature: True

research/cv/pcb/config/train_PCB_duke.yaml

+# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
+
+enable_modelarts: False
+# Url for modelarts
+data_url: ""
+train_url: ""
+checkpoint_url: ""
+# Path for local
+run_distribute: False
+enable_profiling: False
+dataset_path: "/cache/dataset/"
+output_path: "/cache/output/"
+load_path: "/cache/load_checkpoint/"
+device_target: "Ascend"
+
+log_save_path: "./log/PCB/duke/train"
+checkpoint_save_path: "./checkpoint/PCB/duke/train"
+checkpoint_file_path: "/cache/load_checkpoint/pretrained_resnet50.ckpt"
+# =========================================================================
+
+# dataset setting
+mindrecord_dir: "./MindRecord"
+dataset_name: "duke"
+batch_size: 64
+num_parallel_workers: 4
+device_num: 1
+
+# model setting
+model_name: "PCB"
+
+# optimizer setting
+learning_rate: 0.1
+lr_mult: 0.1
+decay_rate: 0.1
+momentum: 0.9
+weight_decay: 5e-4
+nesterov: True
+loss_scale: 1.0
+
+# training setting
+mode_name: "GRAPH"
+sink_mode: True
+seed: 1
+epoch_size: 60
+decay_epoch_size: 40
+warmup_epoch_size: 0
+
+# checkpoint callbacks setting
+save_checkpoint: True
+save_checkpoint_epochs: 60
+keep_checkpoint_max: 15
+
+# EvalCallBack setting
+run_eval: False
+eval_interval: 15
+eval_start_epoch: 60
+
+use_G_feature: True

research/cv/pcb/config/train_PCB_market.yaml

+# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
+
+enable_modelarts: False
+# Url for modelarts
+data_url: ""
+train_url: ""
+checkpoint_url: ""
+# Path for local
+run_distribute: False
+enable_profiling: False
+dataset_path: "/cache/dataset/"
+output_path: "/cache/output/"
+load_path: "/cache/load_checkpoint/"
+device_target: "Ascend"
+
+log_save_path: "./log/PCB/market/train"
+checkpoint_save_path: "./checkpoint/PCB/market/train"
+checkpoint_file_path: "/cache/load_checkpoint/pretrained_resnet50.ckpt"
+# =========================================================================
+
+# dataset setting
+mindrecord_dir: "./MindRecord"
+dataset_name: "market"
+batch_size: 64
+num_parallel_workers: 4
+device_num: 1
+
+# model setting
+model_name: "PCB"
+
+# optimizer setting
+learning_rate: 0.1
+lr_mult: 0.1
+decay_rate: 0.1
+momentum: 0.9
+weight_decay: 5e-4
+nesterov: True
+loss_scale: 1.0
+
+# training setting
+mode_name: "GRAPH"
+sink_mode: True
+seed: 37
+epoch_size: 60
+decay_epoch_size: 40
+warmup_epoch_size: 1
+
+# checkpoint callbacks setting
+save_checkpoint: True
+save_checkpoint_epochs: 60
+keep_checkpoint_max: 15
+
+# EvalCallBack setting
+run_eval: False
+eval_interval: 15
+eval_start_epoch: 60
+
+use_G_feature: True

research/cv/pcb/config/train_RPP_cuhk03/finetune_RPP.yaml

+# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
+
+enable_modelarts: False
+# Url for modelarts
+data_url: ""
+train_url: ""
+checkpoint_url: ""
+# Path for local
+run_distribute: False
+enable_profiling: False
+dataset_path: "/cache/dataset/"
+output_path: "/cache/output/"
+load_path: "/cache/load_checkpoint/"
+device_target: "Ascend"
+log_save_path: "./log/RPP/cuhk03/train"
+checkpoint_save_path: "./checkpoint/RPP/cuhk03/train"
+checkpoint_file_path: "/cache/load_checkpoint/RPP-45_115.ckpt"
+# =========================================================================
+
+# dataset setting
+mindrecord_dir: "./MindRecord"
+dataset_name: "cuhk03"
+batch_size: 64
+num_parallel_workers: 4
+device_num: 1
+
+# model setting
+model_name: "RPP"
+
+# optimizer setting
+learning_rate: 0.005
+lr_mult: 0.5
+decay_rate: 0.5
+momentum: 0.9
+weight_decay: 5e-4
+nesterov: True
+loss_scale: 1.0
+
+# training setting
+mode_name: "GRAPH"
+sink_mode: True
+seed: 37
+epoch_size: 10
+decay_epoch_size: 10
+warmup_epoch_size: 0
+
+# checkpoint callbacks setting
+save_checkpoint: True
+save_checkpoint_epochs: 10
+keep_checkpoint_max: 15
+
+# EvalCallBack setting
+run_eval: False
+eval_interval: 15
+eval_start_epoch: 60
+
+use_G_feature: True