diff --git a/model_zoo/research/cv/FaceRecognitionForTracking/README.md b/model_zoo/research/cv/FaceRecognitionForTracking/README.md index b0dadc903cb..60718da30fe 100644 --- a/model_zoo/research/cv/FaceRecognitionForTracking/README.md +++ b/model_zoo/research/cv/FaceRecognitionForTracking/README.md @@ -73,6 +73,7 @@ The entire code structure is as following: . └─ Face Recognition For Tracking ├─ README.md + ├─ ascend310_infer # application for 310 inference ├─ scripts ├─ run_standalone_train.sh # launch standalone training(1p) in ascend ├─ run_distribute_train.sh # launch distributed training(8p) in ascend @@ -84,6 +85,7 @@ The entire code structure is as following: ├─ run_export_gpu.sh # launch exporting mindir model in gpu ├─ run_train_cpu.sh # launch standalone training in cpu ├─ run_eval_cpu.sh # launch evaluating in cpu + ├─ run_infer_310.sh # launch inference on Ascend310 └─ run_export_cpu.sh # launch exporting mindir model in cpu ├─ src ├─ config.py # parameter configuration @@ -95,6 +97,8 @@ The entire code structure is as following: └─ me_init.py # network initialization ├─ train.py # training scripts ├─ eval.py # evaluation scripts + ├─ postprocess.py # postprocess script + ├─ preprocess.py # preprocess script └─ export.py # export air/mindir model ``` @@ -251,9 +255,11 @@ You will get the result as following in "./scripts/device0/eval.log" or txt file 1e-05: 0.035770748447963394@0.5053771466191392 ``` -### Convert model +### Inference process -If you want to infer the network on Ascend 310, you should convert the model to AIR: +#### Convert model + +If you want to infer the network on Ascend 310, you should convert the model to MINDIR or AIR: ```bash Ascend: @@ -278,6 +284,42 @@ cd ./scripts sh run_export_cpu.sh [PRETRAINED_BACKBONE] [BATCH_SIZE] [FILE_NAME](optional) ``` +Export MINDIR: + +```shell +# Ascend310 inference +python export.py --pretrained [PRETRAIN] --batch_size [BATCH_SIZE] --file_format [EXPORT_FORMAT] +``` + +The pretrained parameter is required. +`EXPORT_FORMAT` should be in ["AIR", "MINDIR"] +Current batch_size can only be set to 1. + +#### 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. + +```shell +# Ascend310 inference +bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DEVICE_ID] +``` + +- `DEVICE_ID` is optional, default value is 0. + +#### result + +Inference result is saved in current path, you can find result like this in recall.log file. + +```bash +0.5: 0.9096926774720119@0.012683006512816064 +0.3: 0.8121103841852932@0.06735802651382983 +0.1: 0.5893883112042262@0.147308789767686 +0.01: 0.25512525545944137@0.2586851498649049754 +0.001: 0.10664387347206335@0.341498649049754 +0.0001: 0.054125268312746624@0.41116268460973515 +1e-05: 0.03846994254572563@0.47234829963417724 +``` + # [Model Description](#contents) ## [Performance](#contents) @@ -313,6 +355,20 @@ sh run_export_cpu.sh [PRETRAINED_BACKBONE] [BATCH_SIZE] [FILE_NAME](optional) | Recall | 0.62(FAR=0.1) | 0.62(FAR=0.1) | 0.62(FAR=0.1) | | Model for inference | 17M (.ckpt file) | 17M (.ckpt file) | 17M (.ckpt file) | +### Inference Performance + +| Parameters | Ascend | +| ------------------- | --------------------------- | +| Model Version | FaceRecognitionForTracking | +| Resource | Ascend 310; Euler2.8 | +| Uploaded Date | 11/06/2021 (month/day/year) | +| MindSpore Version | 1.2.0 | +| Dataset | 2K images | +| batch_size | 1 | +| outputs | recall | +| Recall | 0.589(FAR=0.1) | +| Model for inference | 17M(.ckpt file) | + # [ModelZoo Homepage](#contents) Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo). diff --git a/model_zoo/research/cv/FaceRecognitionForTracking/ascend310_infer/CMakeLists.txt b/model_zoo/research/cv/FaceRecognitionForTracking/ascend310_infer/CMakeLists.txt new file mode 100644 index 00000000000..ee3c8544734 --- /dev/null +++ b/model_zoo/research/cv/FaceRecognitionForTracking/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/FaceRecognitionForTracking/ascend310_infer/build.sh b/model_zoo/research/cv/FaceRecognitionForTracking/ascend310_infer/build.sh new file mode 100644 index 00000000000..770a8851efa --- /dev/null +++ b/model_zoo/research/cv/FaceRecognitionForTracking/ascend310_infer/build.sh @@ -0,0 +1,23 @@ +#!/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 + mkdir out +fi +cd out || exit +cmake .. \ + -DMINDSPORE_PATH="`pip show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`" +make diff --git a/model_zoo/research/cv/FaceRecognitionForTracking/ascend310_infer/inc/utils.h b/model_zoo/research/cv/FaceRecognitionForTracking/ascend310_infer/inc/utils.h new file mode 100644 index 00000000000..efebe03a8c1 --- /dev/null +++ b/model_zoo/research/cv/FaceRecognitionForTracking/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/FaceRecognitionForTracking/ascend310_infer/src/main.cc b/model_zoo/research/cv/FaceRecognitionForTracking/ascend310_infer/src/main.cc new file mode 100644 index 00000000000..4daec31d9a0 --- /dev/null +++ b/model_zoo/research/cv/FaceRecognitionForTracking/ascend310_infer/src/main.cc @@ -0,0 +1,127 @@ +/** + * 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 "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; + +DEFINE_string(mindir_path, "", "mindir path"); +DEFINE_string(input0_path, ".", "input0 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(); + auto ascend310 = std::make_shared(); + 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 model_inputs = model.GetInputs(); + if (model_inputs.empty()) { + std::cout << "Invalid model, inputs is empty." << std::endl; + return 1; + } + + auto input0_files = GetAllFiles(FLAGS_input0_path); + + if (input0_files.empty()) { + std::cout << "ERROR: input data empty." << std::endl; + return 1; + } + + std::map costTime_map; + size_t size = input0_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:" << input0_files[i] << std::endl; + + auto input0 = ReadFileToTensor(input0_files[i]); + inputs.emplace_back(model_inputs[0].Name(), model_inputs[0].DataType(), model_inputs[0].Shape(), + input0.Data().get(), input0.DataSize()); + + gettimeofday(&start, nullptr); + ret = model.Predict(inputs, &outputs); + gettimeofday(&end, nullptr); + if (ret != kSuccess) { + std::cout << "Predict " << input0_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(input0_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/FaceRecognitionForTracking/ascend310_infer/src/utils.cc b/model_zoo/research/cv/FaceRecognitionForTracking/ascend310_infer/src/utils.cc new file mode 100644 index 00000000000..b509c57f823 --- /dev/null +++ b/model_zoo/research/cv/FaceRecognitionForTracking/ascend310_infer/src/utils.cc @@ -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 +#include +#include + +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/FaceRecognitionForTracking/export.py b/model_zoo/research/cv/FaceRecognitionForTracking/export.py index fd8e50f8412..9c89610c354 100644 --- a/model_zoo/research/cv/FaceRecognitionForTracking/export.py +++ b/model_zoo/research/cv/FaceRecognitionForTracking/export.py @@ -63,12 +63,12 @@ if __name__ == "__main__": parser.add_argument('--device_target', type=str, choices=['Ascend', 'GPU', 'CPU'], default='Ascend', help='device_target') parser.add_argument('--file_name', type=str, default='FaceRecognitionForTracking', help='output file name') - parser.add_argument('--file_format', type=str, choices=['AIR', 'ONNX', 'MINDIR'], default='AIR', help='file format') + parser.add_argument('--file_format', type=str, choices=['AIR', 'MINDIR'], default='AIR', help='file format') arg = parser.parse_args() if arg.device_target == 'Ascend': - devid = int(os.getenv('DEVICE_ID')) + devid = int(os.getenv('DEVICE_ID', '0')) context.set_context(device_id=devid) context.set_context(mode=context.GRAPH_MODE, device_target=arg.device_target) diff --git a/model_zoo/research/cv/FaceRecognitionForTracking/postprocess.py b/model_zoo/research/cv/FaceRecognitionForTracking/postprocess.py new file mode 100644 index 00000000000..7215ca98b9f --- /dev/null +++ b/model_zoo/research/cv/FaceRecognitionForTracking/postprocess.py @@ -0,0 +1,128 @@ +# 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 re +import warnings +import argparse +import numpy as np +from tqdm import tqdm + +warnings.filterwarnings('ignore') + +parser = argparse.ArgumentParser(description='FaceRecognitionForTracking calcul Recall') +parser.add_argument("--result_path", type=str, required=True, default='', help="result file path") +parser.add_argument("--data_dir", type=str, required=True, default='', help="data dir") +args = parser.parse_args() + + +def inclass_likehood(ims_info, types='cos'): + '''Inclass likehood.''' + obj_feas = {} + likehoods = [] + for name, _, fea in ims_info: + if re.split('_\\d\\d\\d\\d', name)[0] not in obj_feas: + obj_feas[re.split('_\\d\\d\\d\\d', name)[0]] = [] + obj_feas[re.split('_\\d\\d\\d\\d', name)[0]].append(fea) # pylint: "_\d\d\d\d" -> "_\\d\\d\\d\\d" + for _, feas in tqdm(obj_feas.items()): + feas = np.array(feas) + if types == 'cos': + likehood_mat = np.dot(feas, np.transpose(feas)).tolist() + for row in likehood_mat: + likehoods += row + else: + for fea in feas.tolist(): + likehoods += np.sum(-(fea - feas) ** 2, axis=1).tolist() + + likehoods = np.array(likehoods) + return likehoods + + +def btclass_likehood(ims_info, types='cos'): + '''Btclass likehood.''' + likehoods = [] + count = 0 + for name1, _, fea1 in tqdm(ims_info): + count += 1 + # pylint: "_\d\d\d\d" -> "_\\d\\d\\d\\d" + frame_id1, _ = re.split('_\\d\\d\\d\\d', name1)[0], name1.split('_')[-1] + fea1 = np.array(fea1) + for name2, _, fea2 in ims_info: + # pylint: "_\d\d\d\d" -> "_\\d\\d\\d\\d" + frame_id2, _ = re.split('_\\d\\d\\d\\d', name2)[0], name2.split('_')[-1] + if frame_id1 == frame_id2: + continue + fea2 = np.array(fea2) + if types == 'cos': + likehoods.append(np.sum(fea1 * fea2)) + else: + likehoods.append(np.sum(-(fea1 - fea2) ** 2)) + + likehoods = np.array(likehoods) + return likehoods + + +def tar_at_far(inlikehoods, btlikehoods): + test_point = [0.5, 0.3, 0.1, 0.01, 0.001, 0.0001, 0.00001] + tar_far = [] + for point in test_point: + thre = btlikehoods[int(btlikehoods.size * point)] + n_ta = np.sum(inlikehoods > thre) + tar_far.append((point, float(n_ta) / inlikehoods.size, thre)) + + return tar_far + + +def main(): + with open("result.txt", 'a+') as result_fw: + root_path = args.data_dir + root_file_list = os.listdir(root_path) + ims_info = [] + for sub_path in root_file_list: + for im_path in os.listdir(os.path.join(root_path, sub_path)): + ims_info.append((im_path.split('.')[0], os.path.join(root_path, sub_path, im_path))) + + paths = [path for name, path in ims_info] + names = [name for name, path in ims_info] + print("exact feature...") + result_shape = (1, 128) + result_path = args.result_path + l_t = [] + for file in [name + "_0.bin" for name in names]: + full_file_path = os.path.join(result_path, file) + if os.path.isfile(full_file_path): + result = np.fromfile(full_file_path, dtype=np.float32).reshape(result_shape).astype(np.float16) + l_t.append(result) + feas = np.concatenate(l_t, axis=0) + ims_info = list(zip(names, paths, feas.tolist())) + + print("exact inclass likehood...") + inlikehoods = inclass_likehood(ims_info) + inlikehoods[::-1].sort() + + print("exact btclass likehood...") + btlikehoods = btclass_likehood(ims_info) + btlikehoods[::-1].sort() + tar_far = tar_at_far(inlikehoods, btlikehoods) + + for far, tar, thre in tar_far: + print('---{}: {}@{}'.format(far, tar, thre)) + + for far, tar, thre in tar_far: + result_fw.write('{}: {}@{} \n'.format(far, tar, thre)) + + +if __name__ == '__main__': + main() diff --git a/model_zoo/research/cv/FaceRecognitionForTracking/preprocess.py b/model_zoo/research/cv/FaceRecognitionForTracking/preprocess.py new file mode 100644 index 00000000000..dad3c2795b1 --- /dev/null +++ b/model_zoo/research/cv/FaceRecognitionForTracking/preprocess.py @@ -0,0 +1,73 @@ +# 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. +# ============================================================================ +"""pre process for 310 inference""" +import os +import argparse +import numpy as np +from PIL import Image + +import mindspore.dataset.vision.py_transforms as V +import mindspore.dataset.transforms.py_transforms as T + + +def load_images(paths, batch_size=1): + '''Load images.''' + ll = [] + resize = V.Resize((96, 64)) + transform = T.Compose([ + V.ToTensor(), + V.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])]) + for i, _ in enumerate(paths): + im = Image.open(paths[i]) + im = resize(im) + img = np.array(im) + ts = transform(img) + ll.append(ts[0]) + if len(ll) == batch_size: + yield np.stack(ll, axis=0) + ll.clear() + if ll: + yield np.stack(ll, axis=0) + + +def preprocess_data(args): + """ preprocess data""" + root_path = args.data_dir + root_file_list = os.listdir(root_path) + ims_info = [] + for sub_path in root_file_list: + for im_path in os.listdir(os.path.join(root_path, sub_path)): + ims_info.append((im_path.split('.')[0], os.path.join(root_path, sub_path, im_path))) + + paths = [path for name, path in ims_info] + names = [name for name, path in ims_info] + i = 0 + + for img in load_images(paths): + img = img.astype(np.float32) + file_name = names[i] + ".bin" + file_path = os.path.join(args.output_path, file_name) + img.tofile(file_path) + i += 1 + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description='preprocess data bin') + parser.add_argument('--data_dir', type=str, default='', help='data dir, e.g. /home/test') + parser.add_argument('--output_path', type=str, default='', help='output image path, e.g. /home/output') + + arg = parser.parse_args() + + preprocess_data(arg) diff --git a/model_zoo/research/cv/FaceRecognitionForTracking/scripts/run_infer_310.sh b/model_zoo/research/cv/FaceRecognitionForTracking/scripts/run_infer_310.sh new file mode 100644 index 00000000000..f48e1ef0424 --- /dev/null +++ b/model_zoo/research/cv/FaceRecognitionForTracking/scripts/run_infer_310.sh @@ -0,0 +1,110 @@ +#!/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=$ASCEND_HOME/opp +fi + +function preprocess_data() +{ + if [ -d preprocess_Result ]; then + rm -rf ./preprocess_Result + fi + mkdir preprocess_Result + python ../preprocess.py --output_path=./preprocess_Result --data_dir=$data_path &> preprocess.log + preprocess_data_path=./preprocess_Result +} + +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=$model --input0_path=$preprocess_data_path --device_id=$device_id &> infer.log +} + +function cal_recall() +{ + python3.7 ../postprocess.py --result_path=./result_Files --data_dir=$data_path &> recall.log & +} + +preprocess_data +if [ $? -ne 0 ]; then + echo "preprocess data failed" + exit 1 +fi +compile_app +if [ $? -ne 0 ]; then + echo "compile app code failed" + exit 1 +fi +infer +if [ $? -ne 0 ]; then + echo " execute inference failed" + exit 1 +fi +cal_recall +if [ $? -ne 0 ]; then + echo "calculate recall failed" + exit 1 +fi \ No newline at end of file