From 3a5a469f2f7acc64df605cf61e68e381a4fdf71b Mon Sep 17 00:00:00 2001 From: ZeyangGao Date: Tue, 15 Jun 2021 18:15:24 +0800 Subject: [PATCH] ssd_mobilenetv2 310 infer & resnet152 issue fix --- model_zoo/official/cv/resnet152/export.py | 42 +++-- .../research/cv/ssd_mobilenetV2/README.md | 49 ++++++ .../ascend310_infer/CMakeLists.txt | 14 ++ .../ssd_mobilenetV2/ascend310_infer/build.sh | 29 +++ .../ascend310_infer/inc/utils.h | 32 ++++ .../ascend310_infer/src/main.cc | 165 ++++++++++++++++++ .../ascend310_infer/src/utils.cc | 129 ++++++++++++++ .../cv/ssd_mobilenetV2/postprocess.py | 89 ++++++++++ .../ssd_mobilenetV2/scripts/run_infer_310.sh | 99 +++++++++++ .../cv/ssd_mobilenetV2_FPNlite/README.md | 49 ++++++ .../ascend310_infer/CMakeLists.txt | 14 ++ .../ascend310_infer/build.sh | 29 +++ .../ascend310_infer/inc/utils.h | 32 ++++ .../ascend310_infer/src/main.cc | 165 ++++++++++++++++++ .../ascend310_infer/src/utils.cc | 129 ++++++++++++++ .../cv/ssd_mobilenetV2_FPNlite/postprocess.py | 89 ++++++++++ .../scripts/run_infer_310.sh | 99 +++++++++++ 17 files changed, 1236 insertions(+), 18 deletions(-) create mode 100644 model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/CMakeLists.txt create mode 100644 model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/build.sh create mode 100644 model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/inc/utils.h create mode 100644 model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/src/main.cc create mode 100644 model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/src/utils.cc create mode 100644 model_zoo/research/cv/ssd_mobilenetV2/postprocess.py create mode 100644 model_zoo/research/cv/ssd_mobilenetV2/scripts/run_infer_310.sh create mode 100644 model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/CMakeLists.txt create mode 100644 model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/build.sh create mode 100644 model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/inc/utils.h create mode 100644 model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/src/main.cc create mode 100644 model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/src/utils.cc create mode 100644 model_zoo/research/cv/ssd_mobilenetV2_FPNlite/postprocess.py create mode 100644 model_zoo/research/cv/ssd_mobilenetV2_FPNlite/scripts/run_infer_310.sh diff --git a/model_zoo/official/cv/resnet152/export.py b/model_zoo/official/cv/resnet152/export.py index e065eb6ba77..6e5f165ee8f 100644 --- a/model_zoo/official/cv/resnet152/export.py +++ b/model_zoo/official/cv/resnet152/export.py @@ -15,27 +15,33 @@ """Export DPN suggest run as python export.py --file_name [filename] --file_format [file format] --checkpoint_path [ckpt path] """ - +import argparse import numpy as np -from mindspore import Tensor, context, load_checkpoint, load_param_into_net, export -from src.dpn import dpns -from src.model_utils.config import config +from mindspore import Tensor, context +from mindspore.train.serialization import export, load_checkpoint +from src.resnet import resnet152 as resnet +from src.config import config5 as config +parser = argparse.ArgumentParser(description="resnet152 export ") +parser.add_argument("--device_id", type=int, default=0, help="Device id") +parser.add_argument("--ckpt_file", type=str, required=True, help="checkpoint file path") +parser.add_argument("--dataset", type=str, default="imagenet2012", help="Dataset, either cifar10 or imagenet2012") +parser.add_argument("--width", type=int, default=224, help="input width") +parser.add_argument("--height", type=int, default=224, help="input height") +parser.add_argument("--file_name", type=str, default='resnet152', help="output file name") +parser.add_argument("--file_format", type=str, choices=['AIR', 'ONNX', 'MINDIR'], default='AIR', help="Device id") +parser.add_argument("--device_target", type=str, choices=['Ascend', 'GPU', 'CPU'], default='Ascend', help="target") +args = parser.parse_args() -context.set_context(mode=context.GRAPH_MODE, device_target=config.device_target) -if config.device_target == "Ascend": - context.set_context(device_id=config.device_id) +context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target) if __name__ == "__main__": + target = args.device_target + if target != "GPU": + context.set_context(device_id=args.device_id) # define net - backbone = config.backbone - num_classes = config.num_classes - net = dpns[backbone](num_classes=num_classes) - - # load checkpoint - param_dict = load_checkpoint(config.checkpoint_path) - load_param_into_net(net, param_dict) - net.set_train(False) - - image = Tensor(np.zeros([1, 3, config.height, config.width], np.float32)) - export(net, image, file_name=config.file_name, file_format=config.file_format) + network = resnet(class_num=config.class_num) + param_dict = load_checkpoint(args.ckpt_file, net=network) + network.set_train(False) + input_data = Tensor(np.zeros([1, 3, args.height, args.width]).astype(np.float32)) + export(network, input_data, file_name=args.file_name, file_format=args.file_format) diff --git a/model_zoo/research/cv/ssd_mobilenetV2/README.md b/model_zoo/research/cv/ssd_mobilenetV2/README.md index c4480be3dd6..5f67fd80381 100644 --- a/model_zoo/research/cv/ssd_mobilenetV2/README.md +++ b/model_zoo/research/cv/ssd_mobilenetV2/README.md @@ -15,6 +15,10 @@ - [Training on Ascend](#training-on-ascend) - [Evaluation Process](#evaluation-process) - [Evaluation on Ascend](#evaluation-on-ascend) + - [Inference Process](#inference-process) + - [Export MindIR](#export-mindir) + - [Infer on Ascend](#infer-on-ascend) + - [Result](#result) - [Model Description](#model-description) - [Performance](#performance) - [Evaluation Performance](#evaluation-performance) @@ -282,6 +286,51 @@ Inference result will be stored in the example path, whose folder name begins wi mAP: 0.2527925497483538 ``` +### Inference Process + +#### [Export MindIR](#contents) + +```shell +python export.py --ckpt_file [CKPT_PATH] --file_name [FILE_NAME] --file_format [FILE_FORMAT] +``` + +The ckpt_file parameter is required, +`EXPORT_FORMAT` should be in ["AIR", "MINDIR"] + +#### [Infer on Ascend310](#contents) + +Before performing inference, the mindir file must be exported by `export.py` script. We only provide an example of inference using MINDIR model. +Current batch_Size can only be set to 1. The precision calculation process needs about 70G+ memory space, otherwise the process will be killed for execeeding memory limits. + +```shell +# Ascend310 inference +bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANNO_PATH] [DEVICE_ID] +``` + +- `DVPP` is mandatory, and must choose from ["DVPP", "CPU"], it's case-insensitive. Note that the image shape of ssd_vgg16 inference is [300, 300], The DVPP hardware restricts width 16-alignment and height even-alignment. Therefore, the network needs to use the CPU operator to process images. +- `ANNO_PATH` is mandatory, and must specify annotation file path including file name. +- `DEVICE_ID` is optional, default value is 0. + +#### [Result](#contents) + +Inference result is saved in current path, you can find result like this in acc.log file. + +```bash +Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.256 +Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.422 +Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 +Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.042 +Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.230 +Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.453 +Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.263 +Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.410 +Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.442 +Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.133 +Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.466 +Average Recall (AR) @[ IoU=0.50:0.95 | area=large | maxDets=100 ] = 0.714 +mAP: 0.2561487588412723 +``` + ## [Model Description](#contents) ### [Performance](#contents) diff --git a/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/CMakeLists.txt b/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/CMakeLists.txt new file mode 100644 index 00000000000..ee3c8544734 --- /dev/null +++ b/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/CMakeLists.txt @@ -0,0 +1,14 @@ +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) diff --git a/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/build.sh b/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/build.sh new file mode 100644 index 00000000000..285514e19f2 --- /dev/null +++ b/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/build.sh @@ -0,0 +1,29 @@ +#!/bin/bash +# Copyright 2021 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="`pip3.7 show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`" +make diff --git a/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/inc/utils.h b/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/inc/utils.h new file mode 100644 index 00000000000..efebe03a8c1 --- /dev/null +++ b/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/inc/utils.h @@ -0,0 +1,32 @@ +/** + * Copyright 2021 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 +#include +#include +#include +#include +#include "include/api/types.h" + +std::vector 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 &outputs); +#endif diff --git a/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/src/main.cc b/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/src/main.cc new file mode 100644 index 00000000000..4b92f1a0719 --- /dev/null +++ b/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/src/main.cc @@ -0,0 +1,165 @@ +/** + * Copyright 2021 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 +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#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/vision.h" +#include "inc/utils.h" + +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; +using mindspore::dataset::TensorTransform; +using mindspore::dataset::vision::DvppDecodeResizeJpeg; +using mindspore::dataset::vision::Resize; +using mindspore::dataset::vision::HWC2CHW; +using mindspore::dataset::vision::Normalize; +using mindspore::dataset::vision::Decode; + +DEFINE_string(mindir_path, "", "mindir path"); +DEFINE_string(dataset_path, ".", "dataset path"); +DEFINE_int32(device_id, 0, "device id"); +DEFINE_string(aipp_path, "./aipp.cfg", "aipp path"); +DEFINE_string(cpu_dvpp, "DVPP", "cpu or dvpp process"); +DEFINE_int32(image_height, 640, "image height"); +DEFINE_int32(image_width, 640, "image width"); + +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(); + auto ascend310 = std::make_shared(); + ascend310->SetDeviceID(FLAGS_device_id); + ascend310->SetBufferOptimizeMode("off_optimize"); + context->MutableDeviceInfo().push_back(ascend310); + mindspore::Graph graph; + Serialization::Load(FLAGS_mindir_path, ModelType::kMindIR, &graph); + if (FLAGS_cpu_dvpp == "DVPP") { + if (RealPath(FLAGS_aipp_path).empty()) { + std::cout << "Invalid aipp path" << std::endl; + return 1; + } else { + ascend310->SetInsertOpConfigPath(FLAGS_aipp_path); + } + } + + Model model; + Status ret = model.Build(GraphCell(graph), context); + if (ret != kSuccess) { + std::cout << "ERROR: Build failed." << std::endl; + return 1; + } + + auto all_files = GetAllFiles(FLAGS_dataset_path); + if (all_files.empty()) { + std::cout << "ERROR: no input data." << std::endl; + return 1; + } + + std::map costTime_map; + size_t size = all_files.size(); + + for (size_t i = 0; i < size; ++i) { + struct timeval start = {0}; + struct timeval end = {0}; + double startTimeMs; + double endTimeMs; + std::vector inputs; + std::vector outputs; + std::cout << "Start predict input files:" << all_files[i] << std::endl; + if (FLAGS_cpu_dvpp == "DVPP") { + auto resizeShape = {static_cast (FLAGS_image_height), static_cast (FLAGS_image_width)}; + Execute resize_op(std::shared_ptr(new DvppDecodeResizeJpeg(resizeShape))); + auto imgDvpp = std::make_shared(); + resize_op(ReadFileToTensor(all_files[i]), imgDvpp.get()); + inputs.emplace_back(imgDvpp->Name(), imgDvpp->DataType(), imgDvpp->Shape(), + imgDvpp->Data().get(), imgDvpp->DataSize()); + } else { + std::shared_ptr decode(new Decode()); + std::shared_ptr hwc2chw(new HWC2CHW()); + std::shared_ptr normalize( + new Normalize({123.675, 116.28, 103.53}, {58.395, 57.120, 57.375})); + auto resizeShape = {FLAGS_image_height, FLAGS_image_width}; + std::shared_ptr resize(new Resize(resizeShape)); + Execute composeDecode({decode, resize, normalize, hwc2chw}); + auto img = MSTensor(); + auto image = ReadFileToTensor(all_files[i]); + composeDecode(image, &img); + std::vector model_inputs = model.GetInputs(); + if (model_inputs.empty()) { + std::cout << "Invalid model, inputs is empty." << std::endl; + return 1; + } + inputs.emplace_back(model_inputs[0].Name(), model_inputs[0].DataType(), model_inputs[0].Shape(), + img.Data().get(), img.DataSize()); + } + + gettimeofday(&start, nullptr); + ret = model.Predict(inputs, &outputs); + gettimeofday(&end, nullptr); + if (ret != kSuccess) { + std::cout << "Predict " << all_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(startTimeMs, endTimeMs)); + WriteResult(all_files[i], outputs); + } + double average = 0.0; + int inferCount = 0; + + for (auto iter = costTime_map.begin(); iter != costTime_map.end(); iter++) { + double diff = 0.0; + 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; +} diff --git a/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/src/utils.cc b/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/src/utils.cc new file mode 100644 index 00000000000..c947e4d5f45 --- /dev/null +++ b/model_zoo/research/cv/ssd_mobilenetV2/ascend310_infer/src/utils.cc @@ -0,0 +1,129 @@ +/** + * Copyright 2021 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 +#include +#include +#include "inc/utils.h" + +using mindspore::MSTensor; +using mindspore::DataType; + +std::vector GetAllFiles(std::string_view dirName) { + struct dirent *filename; + DIR *dir = OpenDir(dirName); + if (dir == nullptr) { + return {}; + } + std::vector 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 &outputs) { + std::string homePath = "./result_Files"; + for (size_t i = 0; i < outputs.size(); ++i) { + size_t outputSize; + std::shared_ptr 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('.'), '_' + std::to_string(i) + ".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(size)}, nullptr, size); + + ifs.seekg(0, std::ios::beg); + ifs.read(reinterpret_cast(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; +} diff --git a/model_zoo/research/cv/ssd_mobilenetV2/postprocess.py b/model_zoo/research/cv/ssd_mobilenetV2/postprocess.py new file mode 100644 index 00000000000..5c456952156 --- /dev/null +++ b/model_zoo/research/cv/ssd_mobilenetV2/postprocess.py @@ -0,0 +1,89 @@ +# Copyright 2021 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 + +from src.config import config +from src.eval_utils import metrics + +parser = argparse.ArgumentParser(description="ssd_mobilenetv2 acc calculation") +parser.add_argument("--result_path", type=str, required=True, help="result files path.") +parser.add_argument("--img_path", type=str, required=True, help="image file path.") +parser.add_argument("--anno_path", type=str, required=True, help="annotation json file path.") +parser.add_argument("--drop", action="store_true", help="drop iscrowd images or not.") +args = parser.parse_args() + +def get_imgSize(file_name): + img = Image.open(file_name) + return img.size + +def get_result(result_path, img_id_file_path): + '''calculate map result for this net''' + anno_json = args.anno_path + if args.drop: + from pycocotools.coco import COCO + train_cls = config.classes + train_cls_dict = {} + for i, cls in enumerate(train_cls): + train_cls_dict[cls] = i + coco = COCO(anno_json) + classs_dict = {} + cat_ids = coco.loadCats(coco.getCatIds()) + for cat in cat_ids: + classs_dict[cat["id"]] = cat["name"] + + files = os.listdir(img_id_file_path) + pred_data = [] + + for file in files: + img_ids_name = file.split('.')[0] + img_id = int(np.squeeze(img_ids_name)) + if args.drop: + anno_ids = coco.getAnnIds(imgIds=img_id, iscrowd=None) + anno = coco.loadAnns(anno_ids) + annos = [] + iscrowd = False + for label in anno: + bbox = label["bbox"] + class_name = classs_dict[label["category_id"]] + iscrowd = iscrowd or label["iscrowd"] + if class_name in train_cls: + x_min, x_max = bbox[0], bbox[0] + bbox[2] + y_min, y_max = bbox[1], bbox[1] + bbox[3] + annos.append(list(map(round, [y_min, x_min, y_max, x_max])) + [train_cls_dict[class_name]]) + if iscrowd or (not annos): + continue + + img_size = get_imgSize(os.path.join(img_id_file_path, file)) + image_shape = np.array([img_size[1], img_size[0]]) + result_path_0 = os.path.join(result_path, img_ids_name + "_0.bin") + result_path_1 = os.path.join(result_path, img_ids_name + "_1.bin") + boxes = np.fromfile(result_path_0, dtype=np.float32).reshape(config.num_ssd_boxes, 4) + box_scores = np.fromfile(result_path_1, dtype=np.float32).reshape(config.num_ssd_boxes, config.num_classes) + + pred_data.append({ + "boxes": boxes, + "box_scores": box_scores, + "img_id": img_id, + "image_shape": image_shape + }) + mAP = metrics(pred_data, anno_json) + print(f" mAP:{mAP}") + +if __name__ == '__main__': + get_result(args.result_path, args.img_path) diff --git a/model_zoo/research/cv/ssd_mobilenetV2/scripts/run_infer_310.sh b/model_zoo/research/cv/ssd_mobilenetV2/scripts/run_infer_310.sh new file mode 100644 index 00000000000..fe082077f01 --- /dev/null +++ b/model_zoo/research/cv/ssd_mobilenetV2/scripts/run_infer_310.sh @@ -0,0 +1,99 @@ +#!/bin/bash +# Copyright 2021 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 3 || $# -gt 4 ]]; then + echo "Usage: bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANNO_PATH] [DEVICE_ID] + DVPP is mandatory, and must choose from [DVPP|CPU], it's case-insensitive + ANNO_PATH is mandatory, and should specify annotation file path of your data including file name. + DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero" +exit 1 +fi + +get_real_path(){ + if [ "${1:0:1}" == "/" ]; then + echo "$1" + else + echo "$(realpath -m $PWD/$1)" + fi +} +model=$(get_real_path $1) +data_path=$(get_real_path $2) +anno=$(get_real_path $3) + +device_id=0 +if [ $# == 4 ]; then + device_id=$4 +fi + +echo "mindir name: "$model +echo "dataset path: "$data_path +echo "image process mode: "$DVPP +echo "device id: "$device_id + +export ASCEND_HOME=/usr/local/Ascend/ +if [ -d ${ASCEND_HOME}/ascend-toolkit ]; then + export PATH=$ASCEND_HOME/fwkacllib/bin:$ASCEND_HOME/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/ascend-toolkit/latest/atc/bin:$PATH + export LD_LIBRARY_PATH=$ASCEND_HOME/fwkacllib/lib64:/usr/local/lib:$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=$ASCEND_HOME/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe + export PYTHONPATH=$ASCEND_HOME/fwkacllib/python/site-packages:${TBE_IMPL_PATH}:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/python/site-packages:$PYTHONPATH + export ASCEND_OPP_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp +else + export PATH=$ASCEND_HOME/fwkacllib/bin:$ASCEND_HOME/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/atc/ccec_compiler/bin:$ASCEND_HOME/atc/bin:$PATH + export LD_LIBRARY_PATH=$ASCEND_HOME/fwkacllib/lib64:/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/fwkacllib/python/site-packages:$ASCEND_HOME/atc/python/site-packages:$PYTHONPATH + export ASCEND_OPP_PATH=$ASCEND_HOME/opp +fi + +function compile_app() +{ + cd ../ascend310_infer || exit + bash build.sh &> build.log +} + +function infer() +{ + cd - || exit + if [ -d result_Files ]; then + rm -rf ./result_Files + fi + if [ -d time_Result ]; then + rm -rf ./time_Result + fi + mkdir result_Files + mkdir time_Result + ../ascend310_infer/out/main --mindir_path=$model --dataset_path=$data_path --cpu_dvpp='CPU' --device_id=$device_id --image_height=320 --image_width=320 &> infer.log +} + +function cal_acc() +{ + python3.7 ../postprocess.py --result_path=./result_Files --img_path=$data_path --anno_path=$anno --drop &> acc.log & +} + +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 +cal_acc +if [ $? -ne 0 ]; then + echo "calculate accuracy failed" + exit 1 +fi \ No newline at end of file diff --git a/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/README.md b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/README.md index 4f5d3cc312c..2c3bfa82050 100644 --- a/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/README.md +++ b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/README.md @@ -15,6 +15,10 @@ - [Training on Ascend](#training-on-ascend) - [Evaluation Process](#evaluation-process) - [Evaluation on Ascend](#evaluation-on-ascend) + - [Inference Process](#inference-process) + - [Export MindIR](#export-mindir) + - [Infer on Ascend](#infer-on-ascend) + - [Result](#result) - [Model Description](#model-description) - [Performance](#performance) - [Evaluation Performance](#evaluation-performance) @@ -286,6 +290,51 @@ Inference result will be stored in the example path, whose folder name begins wi mAP: 0.23368420287379554 ``` +### Inference Process + +#### [Export MindIR](#contents) + +```shell +python export.py --ckpt_file [CKPT_PATH] --file_name [FILE_NAME] --file_format [FILE_FORMAT] +``` + +The ckpt_file parameter is required, +`EXPORT_FORMAT` should be in ["AIR", "MINDIR"] + +#### [Infer on Ascend310](#contents) + +Before performing inference, the mindir file must be exported by `export.py` script. We only provide an example of inference using MINDIR model. +Current batch_Size can only be set to 1. The precision calculation process needs about 70G+ memory space, otherwise the process will be killed for execeeding memory limits. + +```shell +# Ascend310 inference +bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANNO_PATH] [DEVICE_ID] +``` + +- `DVPP` is mandatory, and must choose from ["DVPP", "CPU"], it's case-insensitive. Note that the image shape of ssd_vgg16 inference is [300, 300], The DVPP hardware restricts width 16-alignment and height even-alignment. Therefore, the network needs to use the CPU operator to process images. +- `ANNO_PATH` is mandatory, and must specify annotation file path including file name. +- `DEVICE_ID` is optional, default value is 0. + +#### [Result](#contents) + +Inference result is saved in current path, you can find result like this in acc.log file. + +```bash +Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.264 +Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.430 +Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.279 +Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 +Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.274 +Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.428 +Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.263 +Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.417 +Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.466 +Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.164 +Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.528 +Average Recall (AR) @[ IoU=0.50:0.95 | area=large | maxDets=100 ] = 0.675 +mAP: 0.2645785822173796 +``` + ## [Model Description](#contents) ### [Performance](#contents) diff --git a/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/CMakeLists.txt b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/CMakeLists.txt new file mode 100644 index 00000000000..ee3c8544734 --- /dev/null +++ b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/CMakeLists.txt @@ -0,0 +1,14 @@ +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) diff --git a/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/build.sh b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/build.sh new file mode 100644 index 00000000000..285514e19f2 --- /dev/null +++ b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/build.sh @@ -0,0 +1,29 @@ +#!/bin/bash +# Copyright 2021 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="`pip3.7 show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`" +make diff --git a/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/inc/utils.h b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/inc/utils.h new file mode 100644 index 00000000000..efebe03a8c1 --- /dev/null +++ b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/inc/utils.h @@ -0,0 +1,32 @@ +/** + * Copyright 2021 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 +#include +#include +#include +#include +#include "include/api/types.h" + +std::vector 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 &outputs); +#endif diff --git a/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/src/main.cc b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/src/main.cc new file mode 100644 index 00000000000..4b92f1a0719 --- /dev/null +++ b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/src/main.cc @@ -0,0 +1,165 @@ +/** + * Copyright 2021 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 +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#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/vision.h" +#include "inc/utils.h" + +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; +using mindspore::dataset::TensorTransform; +using mindspore::dataset::vision::DvppDecodeResizeJpeg; +using mindspore::dataset::vision::Resize; +using mindspore::dataset::vision::HWC2CHW; +using mindspore::dataset::vision::Normalize; +using mindspore::dataset::vision::Decode; + +DEFINE_string(mindir_path, "", "mindir path"); +DEFINE_string(dataset_path, ".", "dataset path"); +DEFINE_int32(device_id, 0, "device id"); +DEFINE_string(aipp_path, "./aipp.cfg", "aipp path"); +DEFINE_string(cpu_dvpp, "DVPP", "cpu or dvpp process"); +DEFINE_int32(image_height, 640, "image height"); +DEFINE_int32(image_width, 640, "image width"); + +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(); + auto ascend310 = std::make_shared(); + ascend310->SetDeviceID(FLAGS_device_id); + ascend310->SetBufferOptimizeMode("off_optimize"); + context->MutableDeviceInfo().push_back(ascend310); + mindspore::Graph graph; + Serialization::Load(FLAGS_mindir_path, ModelType::kMindIR, &graph); + if (FLAGS_cpu_dvpp == "DVPP") { + if (RealPath(FLAGS_aipp_path).empty()) { + std::cout << "Invalid aipp path" << std::endl; + return 1; + } else { + ascend310->SetInsertOpConfigPath(FLAGS_aipp_path); + } + } + + Model model; + Status ret = model.Build(GraphCell(graph), context); + if (ret != kSuccess) { + std::cout << "ERROR: Build failed." << std::endl; + return 1; + } + + auto all_files = GetAllFiles(FLAGS_dataset_path); + if (all_files.empty()) { + std::cout << "ERROR: no input data." << std::endl; + return 1; + } + + std::map costTime_map; + size_t size = all_files.size(); + + for (size_t i = 0; i < size; ++i) { + struct timeval start = {0}; + struct timeval end = {0}; + double startTimeMs; + double endTimeMs; + std::vector inputs; + std::vector outputs; + std::cout << "Start predict input files:" << all_files[i] << std::endl; + if (FLAGS_cpu_dvpp == "DVPP") { + auto resizeShape = {static_cast (FLAGS_image_height), static_cast (FLAGS_image_width)}; + Execute resize_op(std::shared_ptr(new DvppDecodeResizeJpeg(resizeShape))); + auto imgDvpp = std::make_shared(); + resize_op(ReadFileToTensor(all_files[i]), imgDvpp.get()); + inputs.emplace_back(imgDvpp->Name(), imgDvpp->DataType(), imgDvpp->Shape(), + imgDvpp->Data().get(), imgDvpp->DataSize()); + } else { + std::shared_ptr decode(new Decode()); + std::shared_ptr hwc2chw(new HWC2CHW()); + std::shared_ptr normalize( + new Normalize({123.675, 116.28, 103.53}, {58.395, 57.120, 57.375})); + auto resizeShape = {FLAGS_image_height, FLAGS_image_width}; + std::shared_ptr resize(new Resize(resizeShape)); + Execute composeDecode({decode, resize, normalize, hwc2chw}); + auto img = MSTensor(); + auto image = ReadFileToTensor(all_files[i]); + composeDecode(image, &img); + std::vector model_inputs = model.GetInputs(); + if (model_inputs.empty()) { + std::cout << "Invalid model, inputs is empty." << std::endl; + return 1; + } + inputs.emplace_back(model_inputs[0].Name(), model_inputs[0].DataType(), model_inputs[0].Shape(), + img.Data().get(), img.DataSize()); + } + + gettimeofday(&start, nullptr); + ret = model.Predict(inputs, &outputs); + gettimeofday(&end, nullptr); + if (ret != kSuccess) { + std::cout << "Predict " << all_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(startTimeMs, endTimeMs)); + WriteResult(all_files[i], outputs); + } + double average = 0.0; + int inferCount = 0; + + for (auto iter = costTime_map.begin(); iter != costTime_map.end(); iter++) { + double diff = 0.0; + 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; +} diff --git a/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/src/utils.cc b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/src/utils.cc new file mode 100644 index 00000000000..c947e4d5f45 --- /dev/null +++ b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/ascend310_infer/src/utils.cc @@ -0,0 +1,129 @@ +/** + * Copyright 2021 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 +#include +#include +#include "inc/utils.h" + +using mindspore::MSTensor; +using mindspore::DataType; + +std::vector GetAllFiles(std::string_view dirName) { + struct dirent *filename; + DIR *dir = OpenDir(dirName); + if (dir == nullptr) { + return {}; + } + std::vector 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 &outputs) { + std::string homePath = "./result_Files"; + for (size_t i = 0; i < outputs.size(); ++i) { + size_t outputSize; + std::shared_ptr 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('.'), '_' + std::to_string(i) + ".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(size)}, nullptr, size); + + ifs.seekg(0, std::ios::beg); + ifs.read(reinterpret_cast(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; +} diff --git a/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/postprocess.py b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/postprocess.py new file mode 100644 index 00000000000..5c456952156 --- /dev/null +++ b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/postprocess.py @@ -0,0 +1,89 @@ +# Copyright 2021 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 + +from src.config import config +from src.eval_utils import metrics + +parser = argparse.ArgumentParser(description="ssd_mobilenetv2 acc calculation") +parser.add_argument("--result_path", type=str, required=True, help="result files path.") +parser.add_argument("--img_path", type=str, required=True, help="image file path.") +parser.add_argument("--anno_path", type=str, required=True, help="annotation json file path.") +parser.add_argument("--drop", action="store_true", help="drop iscrowd images or not.") +args = parser.parse_args() + +def get_imgSize(file_name): + img = Image.open(file_name) + return img.size + +def get_result(result_path, img_id_file_path): + '''calculate map result for this net''' + anno_json = args.anno_path + if args.drop: + from pycocotools.coco import COCO + train_cls = config.classes + train_cls_dict = {} + for i, cls in enumerate(train_cls): + train_cls_dict[cls] = i + coco = COCO(anno_json) + classs_dict = {} + cat_ids = coco.loadCats(coco.getCatIds()) + for cat in cat_ids: + classs_dict[cat["id"]] = cat["name"] + + files = os.listdir(img_id_file_path) + pred_data = [] + + for file in files: + img_ids_name = file.split('.')[0] + img_id = int(np.squeeze(img_ids_name)) + if args.drop: + anno_ids = coco.getAnnIds(imgIds=img_id, iscrowd=None) + anno = coco.loadAnns(anno_ids) + annos = [] + iscrowd = False + for label in anno: + bbox = label["bbox"] + class_name = classs_dict[label["category_id"]] + iscrowd = iscrowd or label["iscrowd"] + if class_name in train_cls: + x_min, x_max = bbox[0], bbox[0] + bbox[2] + y_min, y_max = bbox[1], bbox[1] + bbox[3] + annos.append(list(map(round, [y_min, x_min, y_max, x_max])) + [train_cls_dict[class_name]]) + if iscrowd or (not annos): + continue + + img_size = get_imgSize(os.path.join(img_id_file_path, file)) + image_shape = np.array([img_size[1], img_size[0]]) + result_path_0 = os.path.join(result_path, img_ids_name + "_0.bin") + result_path_1 = os.path.join(result_path, img_ids_name + "_1.bin") + boxes = np.fromfile(result_path_0, dtype=np.float32).reshape(config.num_ssd_boxes, 4) + box_scores = np.fromfile(result_path_1, dtype=np.float32).reshape(config.num_ssd_boxes, config.num_classes) + + pred_data.append({ + "boxes": boxes, + "box_scores": box_scores, + "img_id": img_id, + "image_shape": image_shape + }) + mAP = metrics(pred_data, anno_json) + print(f" mAP:{mAP}") + +if __name__ == '__main__': + get_result(args.result_path, args.img_path) diff --git a/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/scripts/run_infer_310.sh b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/scripts/run_infer_310.sh new file mode 100644 index 00000000000..fe082077f01 --- /dev/null +++ b/model_zoo/research/cv/ssd_mobilenetV2_FPNlite/scripts/run_infer_310.sh @@ -0,0 +1,99 @@ +#!/bin/bash +# Copyright 2021 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 3 || $# -gt 4 ]]; then + echo "Usage: bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANNO_PATH] [DEVICE_ID] + DVPP is mandatory, and must choose from [DVPP|CPU], it's case-insensitive + ANNO_PATH is mandatory, and should specify annotation file path of your data including file name. + DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero" +exit 1 +fi + +get_real_path(){ + if [ "${1:0:1}" == "/" ]; then + echo "$1" + else + echo "$(realpath -m $PWD/$1)" + fi +} +model=$(get_real_path $1) +data_path=$(get_real_path $2) +anno=$(get_real_path $3) + +device_id=0 +if [ $# == 4 ]; then + device_id=$4 +fi + +echo "mindir name: "$model +echo "dataset path: "$data_path +echo "image process mode: "$DVPP +echo "device id: "$device_id + +export ASCEND_HOME=/usr/local/Ascend/ +if [ -d ${ASCEND_HOME}/ascend-toolkit ]; then + export PATH=$ASCEND_HOME/fwkacllib/bin:$ASCEND_HOME/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/ascend-toolkit/latest/atc/bin:$PATH + export LD_LIBRARY_PATH=$ASCEND_HOME/fwkacllib/lib64:/usr/local/lib:$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=$ASCEND_HOME/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe + export PYTHONPATH=$ASCEND_HOME/fwkacllib/python/site-packages:${TBE_IMPL_PATH}:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/python/site-packages:$PYTHONPATH + export ASCEND_OPP_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp +else + export PATH=$ASCEND_HOME/fwkacllib/bin:$ASCEND_HOME/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/atc/ccec_compiler/bin:$ASCEND_HOME/atc/bin:$PATH + export LD_LIBRARY_PATH=$ASCEND_HOME/fwkacllib/lib64:/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/fwkacllib/python/site-packages:$ASCEND_HOME/atc/python/site-packages:$PYTHONPATH + export ASCEND_OPP_PATH=$ASCEND_HOME/opp +fi + +function compile_app() +{ + cd ../ascend310_infer || exit + bash build.sh &> build.log +} + +function infer() +{ + cd - || exit + if [ -d result_Files ]; then + rm -rf ./result_Files + fi + if [ -d time_Result ]; then + rm -rf ./time_Result + fi + mkdir result_Files + mkdir time_Result + ../ascend310_infer/out/main --mindir_path=$model --dataset_path=$data_path --cpu_dvpp='CPU' --device_id=$device_id --image_height=320 --image_width=320 &> infer.log +} + +function cal_acc() +{ + python3.7 ../postprocess.py --result_path=./result_Files --img_path=$data_path --anno_path=$anno --drop &> acc.log & +} + +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 +cal_acc +if [ $? -ne 0 ]; then + echo "calculate accuracy failed" + exit 1 +fi \ No newline at end of file