m53297601
/
mindspore
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

add crnn 310 inference code

Browse Source
pull/12733/head
chenhaozhe 4 years ago
parent e1980d2386
commit fe3f905827
11 changed files with 551 additions and 4 deletions
Show Stats Download Patch File Download Diff File

6
model_zoo/official/cv/crnn/Dockerfile
Unescape View File

@ -0,0 +1,6 @@
ARG FROM_IMAGE_NAME
FROM ${FROM_IMAGE_NAME}
RUN apt install libgl1-mesa-glx -y
COPY requirements.txt .
RUN pip3.7 install -r requirements.txt

14
model_zoo/official/cv/crnn/ascend310_infer/CMakeLists.txt
Unescape View File

@ -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)

23
model_zoo/official/cv/crnn/ascend310_infer/build.sh
Unescape View File

@ -0,0 +1,23 @@
#!/bin/bash
# Copyright 2020-2021 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
mkdir out
fi
cd out
cmake .. \
-DMINDSPORE_PATH="`pip show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`"
make

32
model_zoo/official/cv/crnn/ascend310_infer/inc/utils.h
Unescape View File

@ -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 <sys/stat.h>
#include <dirent.h>
#include <vector>
#include <string>
#include <memory>
#include "include/api/types.h"
std::vector<std::string> GetAllFiles(std::string_view dirName);
DIR *OpenDir(std::string_view dirName);
std::string RealPath(std::string_view path);
mindspore::MSTensor ReadFileToTensor(const std::string &file);
int WriteResult(const std::string& imageFile, const std::vector<mindspore::MSTensor> &outputs);
#endif

148
model_zoo/official/cv/crnn/ascend310_infer/src/main.cc
Unescape View File

@ -0,0 +1,148 @@
/**
* 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 "include/api/model.h"
#include "include/api/context.h"
#include "include/api/serialization.h"
#include "include/api/types.h"
#include "include/minddata/dataset/include/vision.h"
#include "include/minddata/dataset/include/execute.h"
#include "minddata/dataset/include/vision.h"
#include "inc/utils.h"
using mindspore::GlobalContext;
using mindspore::Serialization;
using mindspore::Model;
using mindspore::ModelContext;
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::Normalize;
using mindspore::dataset::vision::HWC2CHW;
using mindspore::dataset::transforms::TypeCast;
DEFINE_string(mindir_path, "", "mindir path");
DEFINE_string(dataset_path, ".", "dataset path");
DEFINE_int32(device_id, 0, "device id");
DEFINE_string(precision_mode, "allow_fp32_to_fp16", "precision mode");
DEFINE_string(op_select_impl_mode, "", "op select impl mode");
DEFINE_string(aipp_path, "", "aipp config file");
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;
}
GlobalContext::SetGlobalDeviceTarget(mindspore::kDeviceTypeAscend310);
GlobalContext::SetGlobalDeviceID(FLAGS_device_id);
auto graph = Serialization::LoadModel(FLAGS_mindir_path, ModelType::kMindIR);
auto model_context = std::make_shared<mindspore::ModelContext>();
if (!FLAGS_aipp_path.empty()) {
ModelContext::SetInsertOpConfigPath(model_context, FLAGS_aipp_path);
}
Model model(GraphCell(graph), model_context);
Status ret = model.Build();
if (ret != kSuccess) {
std::cout << "ERROR: Build failed." << std::endl;
return 1;
}
auto allFiles = GetAllFiles(FLAGS_dataset_path);
if (allFiles.empty()) {
std::cout << "ERROR: no input data." << std::endl;
return 1;
}
Execute compose({std::shared_ptr<Decode>(new Decode()),
std::shared_ptr<Resize>(new Resize({32, 100})),
std::shared_ptr<Normalize>(new Normalize({127.5, 127.5, 127.5},
{127.5, 127.5, 127.5})),
std::shared_ptr<HWC2CHW>(new HWC2CHW())});
Execute composeCast(std::shared_ptr<TypeCast>(new TypeCast("float16")));
struct timeval start;
struct timeval end;
double startTime_ms;
double endTime_ms;
std::map<double, double> costTime_map;
size_t size = allFiles.size();
for (size_t i = 0; i < size; ++i) {
std::vector<MSTensor> inputs;
std::vector<MSTensor> outputs;
std::cout << "Start predict input files:" << allFiles[i] << std::endl;
std::string suffix = allFiles[i].substr(allFiles[i].rfind("."));
if (suffix != ".jpg" && suffix != ".png" && suffix != ".JPG" && suffix != ".PNG") {
std::cout << "wrong file format: " << allFiles[i] << std::endl;
continue;
}
auto img = std::make_shared<MSTensor>();
compose(ReadFileToTensor(allFiles[i]), img.get());
inputs.emplace_back(img->Name(), img->DataType(), img->Shape(),
img->Data().get(), img->DataSize());
gettimeofday(&start, NULL);
ret = model.Predict(inputs, &outputs);
gettimeofday(&end, NULL);
if (ret != kSuccess) {
std::cout << "Predict " << allFiles[i] << " failed." << std::endl;
return 1;
}
startTime_ms = (1.0 * start.tv_sec * 1000000 + start.tv_usec) / 1000;
endTime_ms = (1.0 * end.tv_sec * 1000000 + end.tv_usec) / 1000;
costTime_map.insert(std::pair<double, double>(startTime_ms, endTime_ms));
WriteResult(allFiles[i], outputs);
}
double average = 0.0;
int infer_cnt = 0;
char tmpCh[256] = {0};
for (auto iter = costTime_map.begin(); iter != costTime_map.end(); iter++) {
double diff = 0.0;
diff = iter->second - iter->first;
average += diff;
infer_cnt++;
}
average = average/infer_cnt;
snprintf(tmpCh, sizeof(tmpCh), "NN inference cost average time: %4.3f ms of infer_count %d \n", average, infer_cnt);
std::cout << "NN inference cost average time: "<< average << "ms of infer_count " << infer_cnt << std::endl;
std::string file_name = "./time_Result" + std::string("/test_perform_static.txt");
std::ofstream file_stream(file_name.c_str(), std::ios::trunc);
file_stream << tmpCh;
file_stream.close();
costTime_map.clear();
return 0;
}

130
model_zoo/official/cv/crnn/ascend310_infer/src/utils.cc
Unescape View File

@ -0,0 +1,130 @@
/**
* 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 "inc/utils.h"
#include <fstream>
#include <algorithm>
#include <iostream>
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;
}
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;
}

81
model_zoo/official/cv/crnn/postprocess.py
Unescape View File

@ -0,0 +1,81 @@
# 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
#
# less 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 src.metric import CRNNAccuracy
from src.config import config1 as config
parser = argparse.ArgumentParser(description="yolov3_darknet53 inference")
parser.add_argument("--ann_file", type=str, required=True, help="ann file.")
parser.add_argument("--result_path", type=str, required=True, help="image file path.")
parser.add_argument("--dataset", type=str, default="ic03", choices=['ic03', 'ic13', 'svt', 'iiit5k'])
args = parser.parse_args()
def read_annotation(ann_file):
file = open(ann_file)
ann = {}
for line in file.readlines():
img_info = line.rsplit("/")[-1].split(",")
img_path = img_info[0].split('/')[-1]
ann[img_path] = img_info[1].strip()
return ann
def read_IC13_annotation(ann_file):
file = open(ann_file)
ann = {}
for line in file.readlines():
img_info = line.split(",")
img_path = img_info[0].split('/')[-1]
ann[img_path] = img_info[1].strip().replace('\"', '')
return ann
def read_svt_annotation(ann_file):
file = open(ann_file)
ann = {}
for line in file.readlines():
img_info = line.split(",")
img_path = img_info[0].split('/')[-1]
ann[img_path] = img_info[1].strip()
return ann
def get_eval_result(result_path, ann_file):
metrics = CRNNAccuracy(config)
if args.dataset == "ic03" or args.dataset == "iiit5k":
ann = read_annotation(args.ann_file)
elif args.dataset == "ic13":
ann = read_IC13_annotation(args.ann_file)
elif args.dataset == "svt":
ann = read_svt_annotation(args.ann_file)
for img_name, label in ann.items():
result_file = os.path.join(result_path, img_name[:-4] + "_0.bin")
pred_y = np.fromfile(result_file, dtype=np.float32).reshape(config.num_step, -1, config.class_num)
metrics.update(pred_y, [label])
print("result CRNNAccuracy is: ", metrics.eval())
metrics.clear()
if __name__ == '__main__':
get_eval_result(args.result_path, args.ann_file)

4
model_zoo/official/cv/crnn/requirements.txt
Unescape View File

@ -1 +1,3 @@
python-Levenshtein
python-Levenshtein
Pillow
xml-python

108
model_zoo/official/cv/crnn/scripts/run_infer_310.sh
Unescape View File

@ -0,0 +1,108 @@
#!/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 4 || $# -gt 5 ]]; then
echo "Usage: sh run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANN_FILE_PATH] [DATASET] [DEVICE_ID]
DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero"
exit 1
fi
get_real_path(){
if [ "${1:0:1}" == "/" ]; then
echo "$1"
else
echo "$(realpath -m $PWD/$1)"
fi
}
model=$(get_real_path $1)
data_path=$(get_real_path $2)
ann_file=$(get_real_path $3)
dataset=$4
if [ $# == 5 ]; then
device_id=$5
elif [ $# == 4 ]; then
if [ -z $device_id ]; then
device_id=0
else
device_id=$device_id
fi
fi
echo $model
echo $data_path
echo $ann_file
echo $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
if [ -f "Makefile" ]; then
make clean
fi
sh build.sh &> build.log
if [ $? -ne 0 ]; then
echo "compile app code failed"
exit 1
fi
cd -
}
function infer()
{
if [ -d result_Files ]; then
rm -rf ./result_Files
fi
if [ -d time_Result ]; then
rm -rf ./time_Result
fi
mkdir result_Files
mkdir time_Result
../ascend310_infer/out/main --mindir_path=$model --dataset_path=$data_path --device_id=$device_id &> infer.log
if [ $? -ne 0 ]; then
echo "execute inference failed"
exit 1
fi
}
function cal_acc()
{
python ../postprocess.py --ann_file=$ann_file --result_path=result_Files --dataset=$dataset &> acc.log &
if [ $? -ne 0 ]; then
echo "calculate accuracy failed"
exit 1
fi
}
compile_app
infer
cal_acc

7
model_zoo/official/cv/crnn/src/metric.py
Unescape View File

@ -37,9 +37,12 @@ class CRNNAccuracy(nn.Metric):
if len(inputs) != 2:
raise ValueError('CRNNAccuracy need 2 inputs (y_pred, y), but got {}'.format(len(inputs)))
y_pred = self._convert_data(inputs[0])
y = self._convert_data(inputs[1])
str_pred = self._ctc_greedy_decoder(y_pred)
str_label = self._convert_labels(y)
if isinstance(inputs[1], list) and isinstance(inputs[1][0], str):
str_label = [x.lower() for x in inputs[1]]
else:
y = self._convert_data(inputs[1])
str_label = self._convert_labels(y)
for pred, label in zip(str_pred, str_label):
print(pred, " :: ", label)

2
model_zoo/official/cv/ssd/ascend310_infer/src/CMakeLists.txt
Unescape View File

@ -1,5 +1,5 @@
cmake_minimum_required(VERSION 3.14.1)
project(MindSporeCxxTestcase[CXX])
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}/)

Write Preview
Loading…
Cancel
Save