forked from mindspore-Ecosystem/mindspore
psenet 310 infer
modified: psenet/ascend310_infer/src/main.cc
modified: psenet/postprocess.py
modified: psenet/scripts/run_infer_310.sh
modified: psenet/README_CN.md
This commit is contained in:
unknown
parent
b82956cefc
commit
7320e6b3f6
|
|
@ -14,6 +14,10 @@
|
||||||
- [Distributed Training](#distributed-training)
|
- [Distributed Training](#distributed-training)
|
||||||
- [Evaluation Process](#evaluation-process)
|
- [Evaluation Process](#evaluation-process)
|
||||||
- [Evaluation](#evaluation)
|
- [Evaluation](#evaluation)
|
||||||
|
- [Inference Process](#inference-process)
|
||||||
|
- [Export MindIR](#export-mindir)
|
||||||
|
- [Infer on Ascend310](#infer-on-ascend310)
|
||||||
|
- [result](#result)
|
||||||
- [Model Description](#model-description)
|
- [Model Description](#model-description)
|
||||||
- [Performance](#performance)
|
- [Performance](#performance)
|
||||||
- [Evaluation Performance](#evaluation-performance)
|
- [Evaluation Performance](#evaluation-performance)
|
||||||
|
|
@ -180,6 +184,33 @@ sh ./script/run_eval_ascend.sh.sh
|
||||||
|
|
||||||
Calculated!{"precision": 0.814796668299853, "recall": 0.8006740491092923, "hmean": 0.8076736279747451, "AP": 0}
|
Calculated!{"precision": 0.814796668299853, "recall": 0.8006740491092923, "hmean": 0.8076736279747451, "AP": 0}
|
||||||
|
|
||||||
|
## 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
|
||||||
|
|
||||||
|
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. Before running the following process, please configure the environment by following the instructions provided in [Quick start](#quick-start).
|
||||||
|
|
||||||
|
```shell
|
||||||
|
# Ascend310 inference
|
||||||
|
bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DEVICE_ID]
|
||||||
|
```
|
||||||
|
|
||||||
|
- `DEVICE_ID` is optional, default value is 0.
|
||||||
|
|
||||||
|
### result
|
||||||
|
|
||||||
|
The `res` folder is generated in the upper-level directory. For details about the final precision calculation, see [Eval Script for ICDAR2015](#eval-script-for-icdar2015).
|
||||||
|
|
||||||
# [Model Description](#contents)
|
# [Model Description](#contents)
|
||||||
|
|
||||||
## [Performance](#contents)
|
## [Performance](#contents)
|
||||||
|
|
|
||||||
|
|
@ -16,7 +16,11 @@
|
||||||
- [运行测试代码](#运行测试代码)
|
- [运行测试代码](#运行测试代码)
|
||||||
- [ICDAR2015评估脚本](#icdar2015评估脚本)
|
- [ICDAR2015评估脚本](#icdar2015评估脚本)
|
||||||
- [用法](#用法)
|
- [用法](#用法)
|
||||||
- [结果](#结果)
|
- [结果](#结果)
|
||||||
|
- [推理过程](#推理过程)
|
||||||
|
- [导出MindIR](#导出mindir)
|
||||||
|
- [在Ascend310执行推理](#在ascend310执行推理)
|
||||||
|
- [结果](#结果)
|
||||||
- [模型描述](#模型描述)
|
- [模型描述](#模型描述)
|
||||||
- [性能](#性能)
|
- [性能](#性能)
|
||||||
- [评估性能](#评估性能)
|
- [评估性能](#评估性能)
|
||||||
|
|
@ -178,6 +182,33 @@ sh ./script/run_eval_ascend.sh.sh
|
||||||
|
|
||||||
Calculated!{"precision": 0.8147966668299853，"recall"：0.8006740491092923，"hmean"：0.8076736279747451，"AP"：0}
|
Calculated!{"precision": 0.8147966668299853，"recall"：0.8006740491092923，"hmean"：0.8076736279747451，"AP"：0}
|
||||||
|
|
||||||
|
## 推理过程
|
||||||
|
|
||||||
|
### [导出MindIR](#contents)
|
||||||
|
|
||||||
|
```shell
|
||||||
|
python export.py --ckpt_file [CKPT_PATH] --file_name [FILE_NAME] --file_format [FILE_FORMAT]
|
||||||
|
```
|
||||||
|
|
||||||
|
参数ckpt_file为必填项，
|
||||||
|
`EXPORT_FORMAT` 必须在 ["AIR", "MINDIR"]中选择。
|
||||||
|
|
||||||
|
### 在Ascend310执行推理
|
||||||
|
|
||||||
|
在执行推理前，mindir文件必须通过`export.py`脚本导出。以下展示了使用minir模型执行推理的示例。
|
||||||
|
目前仅支持batch_Size为1的推理。在执行推理前，请按照[快速入门](#快速入门)配置环境。
|
||||||
|
|
||||||
|
```shell
|
||||||
|
# Ascend310 推理
|
||||||
|
bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DEVICE_ID]
|
||||||
|
```
|
||||||
|
|
||||||
|
- `DEVICE_ID` 可选，默认值为0。
|
||||||
|
|
||||||
|
### result
|
||||||
|
|
||||||
|
在运行目录的上一级目录将生成`res`文件夹，最终精度计算过程，请参照[ICDAR2015评估脚本](#icdar2015评估脚本).
|
||||||
|
|
||||||
# 模型描述
|
# 模型描述
|
||||||
|
|
||||||
## 性能
|
## 性能
|
||||||
|
|
|
||||||
|
|
@ -0,0 +1,15 @@
|
||||||
|
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)
|
||||||
|
|
||||||
|
|
@ -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
|
||||||
|
|
@ -0,0 +1,35 @@
|
||||||
|
/**
|
||||||
|
* 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 <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);
|
||||||
|
std::vector<std::string> GetAllFiles(std::string dir_name);
|
||||||
|
std::vector<std::vector<std::string>> GetAllInputData(std::string dir_name);
|
||||||
|
|
||||||
|
#endif
|
||||||
|
|
@ -0,0 +1,161 @@
|
||||||
|
/**
|
||||||
|
* 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 <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/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::vision::Decode;
|
||||||
|
using mindspore::dataset::vision::Resize;
|
||||||
|
using mindspore::dataset::vision::Pad;
|
||||||
|
using mindspore::dataset::vision::Normalize;
|
||||||
|
using mindspore::dataset::vision::HWC2CHW;
|
||||||
|
|
||||||
|
DEFINE_string(mindir_path, "", "mindir path");
|
||||||
|
DEFINE_string(dataset_path, ".", "dataset 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 all_files = GetAllFiles(FLAGS_dataset_path);
|
||||||
|
if (all_files.empty()) {
|
||||||
|
std::cout << "ERROR: no input data." << std::endl;
|
||||||
|
return 1;
|
||||||
|
}
|
||||||
|
|
||||||
|
std::map<double, double> costTime_map;
|
||||||
|
size_t size = all_files.size();
|
||||||
|
auto decode = Decode();
|
||||||
|
Execute composeDecode(decode);
|
||||||
|
|
||||||
|
auto resize = Resize({1920, 1920});
|
||||||
|
auto normalize = Normalize({123.675, 116.28, 103.53}, {58.395, 57.12, 57.375});
|
||||||
|
auto hwc2chw = HWC2CHW();
|
||||||
|
|
||||||
|
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:" << all_files[i] <<std::endl;
|
||||||
|
auto imgDecode = MSTensor();
|
||||||
|
auto image = ReadFileToTensor(all_files[i]);
|
||||||
|
ret = composeDecode(image, &imgDecode);
|
||||||
|
if (ret != kSuccess) {
|
||||||
|
std::cout << "ERROR: Decode failed." << std::endl;
|
||||||
|
return 1;
|
||||||
|
}
|
||||||
|
std::vector<int64_t> shape = imgDecode.Shape();
|
||||||
|
int imgHeight = shape[0];
|
||||||
|
int imgWidth = shape[1];
|
||||||
|
std::vector<int> pad_size;
|
||||||
|
if (imgWidth < imgHeight) {
|
||||||
|
pad_size = {0, 0, (imgHeight - imgWidth), 0};
|
||||||
|
} else {
|
||||||
|
pad_size = {0, 0, 0, (imgWidth - imgHeight)};
|
||||||
|
}
|
||||||
|
auto pad = Pad(pad_size, {0});
|
||||||
|
Execute trans_list({pad, resize, normalize, hwc2chw});
|
||||||
|
auto img = MSTensor();
|
||||||
|
ret = trans_list(imgDecode, &img);
|
||||||
|
if (ret != kSuccess) {
|
||||||
|
std::cout << "ERROR: Image transfer failed." << 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<double, double>(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;
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,185 @@
|
||||||
|
/**
|
||||||
|
* 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 <fstream>
|
||||||
|
#include <algorithm>
|
||||||
|
#include <iostream>
|
||||||
|
#include "inc/utils.h"
|
||||||
|
|
||||||
|
using mindspore::MSTensor;
|
||||||
|
using mindspore::DataType;
|
||||||
|
|
||||||
|
|
||||||
|
std::vector<std::vector<std::string>> GetAllInputData(std::string dir_name) {
|
||||||
|
std::vector<std::vector<std::string>> ret;
|
||||||
|
|
||||||
|
DIR *dir = OpenDir(dir_name);
|
||||||
|
if (dir == nullptr) {
|
||||||
|
return {};
|
||||||
|
}
|
||||||
|
struct dirent *filename;
|
||||||
|
/* read all the files in the dir ~ */
|
||||||
|
std::vector<std::string> sub_dirs;
|
||||||
|
while ((filename = readdir(dir)) != nullptr) {
|
||||||
|
std::string d_name = std::string(filename->d_name);
|
||||||
|
// get rid of "." and ".."
|
||||||
|
if (d_name == "." || d_name == ".." || d_name.empty()) {
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
std::string dir_path = RealPath(std::string(dir_name) + "/" + filename->d_name);
|
||||||
|
struct stat s;
|
||||||
|
lstat(dir_path.c_str(), &s);
|
||||||
|
if (!S_ISDIR(s.st_mode)) {
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
|
||||||
|
sub_dirs.emplace_back(dir_path);
|
||||||
|
}
|
||||||
|
std::sort(sub_dirs.begin(), sub_dirs.end());
|
||||||
|
|
||||||
|
(void)std::transform(sub_dirs.begin(), sub_dirs.end(), std::back_inserter(ret),
|
||||||
|
[](const std::string &d) { return GetAllFiles(d); });
|
||||||
|
|
||||||
|
return ret;
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
std::vector<std::string> GetAllFiles(std::string dir_name) {
|
||||||
|
struct dirent *filename;
|
||||||
|
DIR *dir = OpenDir(dir_name);
|
||||||
|
if (dir == nullptr) {
|
||||||
|
return {};
|
||||||
|
}
|
||||||
|
|
||||||
|
std::vector<std::string> res;
|
||||||
|
while ((filename = readdir(dir)) != nullptr) {
|
||||||
|
std::string d_name = std::string(filename->d_name);
|
||||||
|
if (d_name == "." || d_name == ".." || d_name.size() <= 3) {
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
res.emplace_back(std::string(dir_name) + "/" + filename->d_name);
|
||||||
|
}
|
||||||
|
std::sort(res.begin(), res.end());
|
||||||
|
|
||||||
|
return res;
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
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";
|
||||||
|
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('.'), '_' + 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<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;
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,104 @@
|
||||||
|
# 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.
|
||||||
|
# ============================================================================
|
||||||
|
|
||||||
|
|
||||||
|
import os
|
||||||
|
import math
|
||||||
|
import operator
|
||||||
|
from functools import reduce
|
||||||
|
import argparse
|
||||||
|
import numpy as np
|
||||||
|
import cv2
|
||||||
|
|
||||||
|
from src.config import config
|
||||||
|
from src.ETSNET.pse import pse
|
||||||
|
|
||||||
|
def sort_to_clockwise(points):
|
||||||
|
center = tuple(map(operator.truediv, reduce(lambda x, y: map(operator.add, x, y), points), [len(points)] * 2))
|
||||||
|
clockwise_points = sorted(points, key=lambda coord: (-135 - math.degrees(
|
||||||
|
math.atan2(*tuple(map(operator.sub, coord, center))[::-1]))) % 360, reverse=True)
|
||||||
|
return clockwise_points
|
||||||
|
|
||||||
|
def write_result_as_txt(image_name, img_bboxes, path):
|
||||||
|
if not os.path.isdir(path):
|
||||||
|
os.makedirs(path)
|
||||||
|
filename = os.path.join(path, 'res_{}.txt'.format(os.path.splitext(image_name)[0]))
|
||||||
|
lines = []
|
||||||
|
for _, img_bbox in enumerate(img_bboxes):
|
||||||
|
img_bbox = img_bbox.reshape(-1, 2)
|
||||||
|
img_bbox = np.array(list(sort_to_clockwise(img_bbox)))[[3, 0, 1, 2]].copy().reshape(-1)
|
||||||
|
values = [int(v) for v in img_bbox]
|
||||||
|
line = "%d,%d,%d,%d,%d,%d,%d,%d\n" % tuple(values)
|
||||||
|
lines.append(line)
|
||||||
|
with open(filename, 'w') as f:
|
||||||
|
for line in lines:
|
||||||
|
f.write(line)
|
||||||
|
|
||||||
|
def get_img(image_path):
|
||||||
|
image = cv2.imread(image_path)
|
||||||
|
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
|
||||||
|
return image
|
||||||
|
|
||||||
|
parser = argparse.ArgumentParser(description='postprocess')
|
||||||
|
parser.add_argument("--result_path", type=str, default="./scripts/result_Files", help='result Files path.')
|
||||||
|
parser.add_argument("--img_path", type=str, default="", help='image files path.')
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
if not os.path.isdir('./res/submit_ic15/'):
|
||||||
|
os.makedirs('./res/submit_ic15/')
|
||||||
|
if not os.path.isdir('./res/vis_ic15/'):
|
||||||
|
os.makedirs('./res/vis_ic15/')
|
||||||
|
|
||||||
|
file_list = os.listdir(args.img_path)
|
||||||
|
for k in file_list:
|
||||||
|
if os.path.splitext(k)[-1].lower() in ['.jpg', '.jpeg', '.png']:
|
||||||
|
img_path = os.path.join(args.img_path, k)
|
||||||
|
img = get_img(img_path).reshape(1, 720, 1280, 3)
|
||||||
|
img = img[0].astype(np.uint8).copy()
|
||||||
|
img_name = os.path.split(img_path)[-1]
|
||||||
|
|
||||||
|
score = np.fromfile(os.path.join(args.result_path, k.split('.')[0] + '_0.bin'), np.float32)
|
||||||
|
score = score.reshape(1, 1, config.INFER_LONG_SIZE, config.INFER_LONG_SIZE)
|
||||||
|
kernels = np.fromfile(os.path.join(args.result_path, k.split('.')[0] + '_1.bin'), bool)
|
||||||
|
kernels = kernels.reshape(1, config.KERNEL_NUM, config.INFER_LONG_SIZE, config.INFER_LONG_SIZE)
|
||||||
|
score = np.squeeze(score)
|
||||||
|
kernels = np.squeeze(kernels)
|
||||||
|
|
||||||
|
# post-process
|
||||||
|
pred = pse(kernels, 5.0)
|
||||||
|
scale = max(img.shape[:2]) * 1.0 / config.INFER_LONG_SIZE
|
||||||
|
label = pred
|
||||||
|
label_num = np.max(label) + 1
|
||||||
|
bboxes = []
|
||||||
|
|
||||||
|
for i in range(1, label_num):
|
||||||
|
pot = np.array(np.where(label == i)).transpose((1, 0))[:, ::-1]
|
||||||
|
if pot.shape[0] < 600:
|
||||||
|
continue
|
||||||
|
|
||||||
|
score_i = np.mean(score[label == i])
|
||||||
|
if score_i < 0.93:
|
||||||
|
continue
|
||||||
|
|
||||||
|
rect = cv2.minAreaRect(pot)
|
||||||
|
bbox = cv2.boxPoints(rect) * scale
|
||||||
|
bbox = bbox.astype('int32')
|
||||||
|
cv2.drawContours(img, [bbox], 0, (0, 255, 0), 3)
|
||||||
|
bboxes.append(bbox)
|
||||||
|
|
||||||
|
# save res
|
||||||
|
cv2.imwrite('./res/vis_ic15/{}'.format(img_name), img[:, :, [2, 1, 0]].copy())
|
||||||
|
write_result_as_txt(img_name, bboxes, './res/submit_ic15/')
|
||||||
|
|
@ -0,0 +1,96 @@
|
||||||
|
#!/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 2 || $# -gt 3 ]]; then
|
||||||
|
echo "Usage: bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DEVICE_ID]
|
||||||
|
DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero"
|
||||||
|
exit 1
|
||||||
|
fi
|
||||||
|
|
||||||
|
get_real_path(){
|
||||||
|
if [ "${1:0:1}" == "/" ]; then
|
||||||
|
echo "$1"
|
||||||
|
else
|
||||||
|
echo "$(realpath -m $PWD/$1)"
|
||||||
|
fi
|
||||||
|
}
|
||||||
|
model=$(get_real_path $1)
|
||||||
|
data_path=$(get_real_path $2)
|
||||||
|
|
||||||
|
device_id=0
|
||||||
|
if [ $# == 3 ]; then
|
||||||
|
device_id=$3
|
||||||
|
fi
|
||||||
|
|
||||||
|
echo "mindir name: "$model
|
||||||
|
echo "dataset path: "$data_path
|
||||||
|
echo "device id: "$device_id
|
||||||
|
|
||||||
|
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 PYTHONPATH=${TBE_IMPL_PATH}:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/python/site-packages:$PYTHONPATH
|
||||||
|
export ASCEND_OPP_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp
|
||||||
|
else
|
||||||
|
export PATH=$ASCEND_HOME/atc/ccec_compiler/bin:$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=$ASCEND_HOME/opp
|
||||||
|
fi
|
||||||
|
|
||||||
|
function compile_app()
|
||||||
|
{
|
||||||
|
cd ../ascend310_infer/ || exit
|
||||||
|
bash build.sh &> build.log
|
||||||
|
}
|
||||||
|
|
||||||
|
function infer()
|
||||||
|
{
|
||||||
|
cd - || exit
|
||||||
|
if [ -d result_Files ]; then
|
||||||
|
rm -rf ./result_Files
|
||||||
|
fi
|
||||||
|
if [ -d time_Result ]; then
|
||||||
|
rm -rf ./time_Result
|
||||||
|
fi
|
||||||
|
mkdir result_Files
|
||||||
|
mkdir time_Result
|
||||||
|
../ascend310_infer/out/main --mindir_path=$model --dataset_path=$data_path --device_id=$device_id &> infer.log
|
||||||
|
}
|
||||||
|
|
||||||
|
function cal_acc()
|
||||||
|
{
|
||||||
|
cd .. || exit
|
||||||
|
python3.7 postprocess.py --result_path=./scripts/result_Files --img_path=$data_path &> ./scripts/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
|
||||||
Loading…
Reference in New Issue