Hu Chunming / village_ascend_arm

Commit f171c20a79db5509e973484f142bdbdfad2ad28e

Authored by Hu Chunming
1 parent 4a273a4a

添加moter_rainshed 和 motor_phone

Inline Side-by-side
Showing 17 changed files with 1068 additions and 36 deletions
bin/models/motor_phone/motor_phone1127_310p.om 0 → 100755
View file @f171c20
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bin/models/rainshed/motor_rainshed_231123_310p.om 0 → 100755
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build/src/Makefile
  View file @f171c20
... ... @@ -18,6 +18,7 @@ ALGORITHM_PATH = $(PROJ_ALL_PATH)/algorithm
18 18  
19 19 INCLUDES = -I$(PROJ_ALL_PATH)/src/common \
20 20 -I$(PROJ_ALL_PATH)/src/common/dvpp \
  21 + -I$(PROJ_ALL_PATH)/src/common/cnn \
21 22 -I$(PROJ_ALL_PATH)/src/common/cnn_cls \
22 23 -I$(PROJ_ALL_PATH)/src/common/dvppx \
23 24 -I$(PROJ_ALL_PATH)/src/common/model_process \
... ... @@ -64,6 +65,7 @@ SRCS := $(wildcard $(CUR_PROJ_PATH)/*.cpp) \
64 65 $(wildcard $(CUR_PROJ_PATH)/common/*.cpp) \
65 66 $(wildcard $(CUR_PROJ_PATH)/common/dvpp/*.cpp) \
66 67 $(wildcard $(CUR_PROJ_PATH)/common/cnn_cls/*.cpp) \
  68 + $(wildcard $(CUR_PROJ_PATH)/common/cnn/*.cpp) \
67 69 $(wildcard $(CUR_PROJ_PATH)/common/dvppx/*.cpp) \
68 70 $(wildcard $(CUR_PROJ_PATH)/common/model_process/*.cpp) \
69 71  
... ... @@ -87,6 +89,9 @@ $(TARGET):$(OBJS)
87 89 %.o:$(CUR_PROJ_PATH)/common/dvpp/%.cpp
88 90 $(XX) $(CXXFLAGS) -c $<
89 91  
  92 +%.o:$(CUR_PROJ_PATH)/common/cnn/%.cpp
  93 + $(XX) $(CXXFLAGS) -c $<
  94 +
90 95 %.o:$(CUR_PROJ_PATH)/common/cnn_cls/%.cpp
91 96 $(XX) $(CXXFLAGS) -c $<
92 97  
... ...
src/PicAnalysis.cpp
  View file @f171c20
... ... @@ -17,30 +17,40 @@ int PicAnalysis::init(int dev_id) {
17 17  
18 18 int ret = SY_FAILED;
19 19  
20   - ret = m_vehicle_analysis.init(dev_id, 16);
21   - if(0 != ret){
22   - return -1;
23   - }
24   -
25   - head_tail_param ht_param;
26   - ht_param.devId = dev_id;
27   - ht_param.max_batch = 16;
28   - ret = m_head_tail_algorithm.init(ht_param);
29   - if(0 != ret){
30   - return -1;
31   - }
32   -
33   - ret = m_clothes_algorithm.init(dev_id);
34   - if(0 != ret){
35   - return -1;
36   - }
37   -
38   - ret = m_human_algorithm.init(dev_id);
39   - if(0 != ret){
40   - return -1;
41   - }
42   -
43   - ret = m_human_car_algorithm.init(dev_id);
  20 + // ret = m_vehicle_analysis.init(dev_id, 16);
  21 + // if(0 != ret){
  22 + // return -1;
  23 + // }
  24 +
  25 + // head_tail_param ht_param;
  26 + // ht_param.devId = dev_id;
  27 + // ht_param.max_batch = 16;
  28 + // ret = m_head_tail_algorithm.init(ht_param);
  29 + // if(0 != ret){
  30 + // return -1;
  31 + // }
  32 +
  33 + // ret = m_clothes_algorithm.init(dev_id);
  34 + // if(0 != ret){
  35 + // return -1;
  36 + // }
  37 +
  38 + // ret = m_human_algorithm.init(dev_id);
  39 + // if(0 != ret){
  40 + // return -1;
  41 + // }
  42 +
  43 + // ret = m_human_car_algorithm.init(dev_id);
  44 + // if(0 != ret){
  45 + // return -1;
  46 + // }
  47 +
  48 + // ret = m_motor_rainshed_algorithm.init(dev_id);
  49 + // if(0 != ret){
  50 + // return -1;
  51 + // }
  52 +
  53 + ret = m_motor_phone_algorithm.init(dev_id);
44 54 if(0 != ret){
45 55 return -1;
46 56 }
... ... @@ -90,20 +100,24 @@ int PicAnalysis::analysis_sync(vector&lt;string&gt; vec_file_path){
90 100 vec_img.push_back(img);
91 101 }
92 102  
93   - m_vehicle_analysis.detect(vec_img);
  103 + // m_vehicle_analysis.detect(vec_img);
94 104  
95   - vector<HeadTailResult> head_tail_result;
96   - ret = m_head_tail_algorithm.detect(vec_img, head_tail_result);
97   - if (0 != ret) {
98   - LOG_ERROR("m_head_tail_algorithm failed!");
99   - head_tail_result.clear();
100   - }
  105 + // vector<HeadTailResult> head_tail_result;
  106 + // ret = m_head_tail_algorithm.detect(vec_img, head_tail_result);
  107 + // if (0 != ret) {
  108 + // LOG_ERROR("m_head_tail_algorithm failed!");
  109 + // head_tail_result.clear();
  110 + // }
  111 +
  112 + // m_clothes_algorithm.detect(vec_img);
  113 +
  114 + // m_human_algorithm.detect(vec_img);
101 115  
102   - m_clothes_algorithm.detect(vec_img);
  116 + // m_human_car_algorithm.detect(vec_img);
103 117  
104   - m_human_algorithm.detect(vec_img);
  118 + // m_motor_rainshed_algorithm.detect(vec_img);
105 119  
106   - m_human_car_algorithm.detect(vec_img);
  120 + m_motor_phone_algorithm.detect(vec_img);
107 121  
108 122 LOG_INFO("analysis_sync finished!");
109 123  
... ...
src/PicAnalysis.h
  View file @f171c20
... ... @@ -4,6 +4,8 @@
4 4 #include "./ai_engine_module/VidClothes.h"
5 5 #include "./ai_engine_module/HumanAnalysis.h"
6 6 #include "./ai_engine_module/HumanCarAnalysis.h"
  7 +#include "./ai_engine_module/MotorRainshedAnalysis.h"
  8 +#include "./ai_engine_module/MotorPhoneAnalysis.h"
7 9  
8 10 using namespace std;
9 11  
... ... @@ -31,6 +33,8 @@ private:
31 33 VidClothes m_clothes_algorithm;
32 34 HumanAnalysis m_human_algorithm;
33 35 HumanCarAnalysis m_human_car_algorithm;
  36 + MotorRainshedAnalysis m_motor_rainshed_algorithm;
  37 + MotorPhoneAnalysis m_motor_phone_algorithm;
34 38 };
35 39  
36 40  
... ...
src/ai_engine_module/HumanAnalysis.cpp
  View file @f171c20
... ... @@ -41,7 +41,7 @@ int HumanAnalysis::detect(vector&lt;sy_img&gt; vec_img){
41 41 {
42 42 ret = hp_batch(m_handle, vec_img.data(), batchsize, results);
43 43 if (SY_SUCCESS != ret) {
44   - printf("vidclothesClassification process failed!");
  44 + printf("hp_batch failed!");
45 45 break;
46 46 }
47 47  
... ...
src/ai_engine_module/HumanCarAnalysis.cpp
  View file @f171c20
... ... @@ -41,7 +41,7 @@ int HumanCarAnalysis::detect(vector&lt;sy_img&gt; vec_img){
41 41 {
42 42 ret = hcp_batch(m_handle, vec_img.data(), batchsize, results);
43 43 if (SY_SUCCESS != ret) {
44   - printf("vidclothesClassification process failed!");
  44 + printf("hcp_batch failed!");
45 45 break;
46 46 }
47 47  
... ...
src/ai_engine_module/MotorPhoneAnalysis.cpp 0 → 100644
  View file @f171c20
  1 +#include "MotorPhoneAnalysis.h"
  2 +#include "motor_phone_det.h"
  3 +
  4 +MotorPhoneAnalysis::MotorPhoneAnalysis(/* args */)
  5 +{
  6 +}
  7 +
  8 +MotorPhoneAnalysis::~MotorPhoneAnalysis()
  9 +{
  10 + release();
  11 +}
  12 +
  13 +int MotorPhoneAnalysis::init(int devId){
  14 + ACL_CALL(aclrtCreateContext(&ctx, devId), SY_SUCCESS, SY_FAILED);
  15 +
  16 + motor_phone_param param;
  17 + param.modelNames = "./models/motor_phone/motor_phone1127_310p.om";
  18 + param.thresld = 0.25;
  19 + param.devId = devId;
  20 +
  21 + cout << "motor_phone_init start " << endl;
  22 + int ret = motor_phone_init(&m_handle, param);
  23 + if (ret != 0) {
  24 + return -1;
  25 + }
  26 +
  27 + cout << "motor_phone_init success " << endl;
  28 +
  29 + return SY_SUCCESS;
  30 +}
  31 +
  32 +int MotorPhoneAnalysis::detect(vector<sy_img> vec_img){
  33 +
  34 + ACL_CALL(aclrtSetCurrentContext(ctx), SY_SUCCESS, SY_FAILED);
  35 +
  36 + const int batchsize = vec_img.size();
  37 + motor_phone_result * results = new motor_phone_result[batchsize];
  38 +
  39 + int ret = SY_FAILED;
  40 +
  41 + do
  42 + {
  43 + ret = motor_phone_process_batch(m_handle, vec_img.data(), batchsize, results);
  44 + if (SY_SUCCESS != ret) {
  45 + printf("motor_phone_process_batch failed!");
  46 + break;
  47 + }
  48 +
  49 + for(int batchIdx = 0; batchIdx < batchsize; batchIdx ++){
  50 + printf("debug det num:%d\n",results[batchIdx].objcount);
  51 + for (int i = 0; i < results[batchIdx].objcount; i++) {
  52 + printf(" %d:%.2f \n", results[batchIdx].objinfo[i].index,results[batchIdx].objinfo[i].confidence);
  53 + }
  54 + }
  55 + } while (0);
  56 +
  57 + if (results) {
  58 + delete [] results;
  59 + }
  60 +
  61 + return ret;
  62 +}
  63 +
  64 +int MotorPhoneAnalysis::release() {
  65 +
  66 + ACL_CALL(aclrtSetCurrentContext(ctx), SY_SUCCESS, SY_FAILED);
  67 +
  68 + if (m_handle) {
  69 + motor_phone_release(&m_handle);
  70 + }
  71 +
  72 + if(ctx){
  73 + aclrtDestroyContext(ctx);
  74 + ctx = nullptr;
  75 + }
  76 +
  77 + return SY_SUCCESS;
  78 +}
0 79 \ No newline at end of file
... ...
src/ai_engine_module/MotorPhoneAnalysis.h 0 → 100644
  View file @f171c20
  1 +#include "include.h"
  2 +
  3 +class MotorPhoneAnalysis
  4 +{
  5 +public:
  6 + MotorPhoneAnalysis(/* args */);
  7 + ~MotorPhoneAnalysis();
  8 +
  9 + int init(int devId);
  10 +
  11 + int detect(vector<sy_img> vec_img);
  12 +
  13 +private:
  14 + int release();
  15 +
  16 +private:
  17 + void* m_handle{nullptr};
  18 + aclrtContext ctx{nullptr};
  19 +};
  20 +
... ...
src/ai_engine_module/MotorRainshedAnalysis.cpp 0 → 100644
  View file @f171c20
  1 +#include "MotorRainshedAnalysis.h"
  2 +#include "motor_rainshed_cls.h"
  3 +
  4 +MotorRainshedAnalysis::MotorRainshedAnalysis(/* args */)
  5 +{
  6 +}
  7 +
  8 +MotorRainshedAnalysis::~MotorRainshedAnalysis()
  9 +{
  10 + release();
  11 +}
  12 +
  13 +int MotorRainshedAnalysis::init(int devId){
  14 + ACL_CALL(aclrtCreateContext(&ctx, devId), SY_SUCCESS, SY_FAILED);
  15 +
  16 + mrc_param param;
  17 + param.modelNames = "./models/rainshed/motor_rainshed_231123_310p.om";
  18 + param.thresld = 0.0;
  19 + param.devId = devId;
  20 +
  21 + cout << "mrc_init start " << endl;
  22 + int ret = mrc_init(&m_handle, param);
  23 + if (ret != 0) {
  24 + return -1;
  25 + }
  26 +
  27 + cout << "mrc_init success " << endl;
  28 +
  29 + return SY_SUCCESS;
  30 +}
  31 +
  32 +int MotorRainshedAnalysis::detect(vector<sy_img> vec_img){
  33 +
  34 + ACL_CALL(aclrtSetCurrentContext(ctx), SY_SUCCESS, SY_FAILED);
  35 +
  36 + const int batchsize = vec_img.size();
  37 + mrc_result * results = new mrc_result[batchsize];
  38 +
  39 + int ret = SY_FAILED;
  40 +
  41 + do
  42 + {
  43 + ret = mrc_batch(m_handle, vec_img.data(), batchsize, results);
  44 + if (SY_SUCCESS != ret) {
  45 + printf("mrc_batch failed!");
  46 + break;
  47 + }
  48 +
  49 + for(int batchIdx = 0;batchIdx<batchsize;batchIdx++){
  50 + printf("index:%d,confidence:%f\n",results[batchIdx].index,results[batchIdx].score);
  51 + }
  52 + } while (0);
  53 +
  54 + if (results) {
  55 + delete [] results;
  56 + }
  57 +
  58 + return ret;
  59 +}
  60 +
  61 +int MotorRainshedAnalysis::release() {
  62 +
  63 + ACL_CALL(aclrtSetCurrentContext(ctx), SY_SUCCESS, SY_FAILED);
  64 +
  65 + if (m_handle) {
  66 + mrc_release(&m_handle);
  67 + }
  68 +
  69 + if(ctx){
  70 + aclrtDestroyContext(ctx);
  71 + ctx = nullptr;
  72 + }
  73 +
  74 + return SY_SUCCESS;
  75 +}
0 76 \ No newline at end of file
... ...
src/ai_engine_module/MotorRainshedAnalysis.h 0 → 100644
  View file @f171c20
  1 +#include "include.h"
  2 +
  3 +class MotorRainshedAnalysis
  4 +{
  5 +public:
  6 + MotorRainshedAnalysis(/* args */);
  7 + ~MotorRainshedAnalysis();
  8 +
  9 + int init(int devId);
  10 +
  11 + int detect(vector<sy_img> vec_img);
  12 +
  13 +private:
  14 + int release();
  15 +
  16 +private:
  17 + void* m_handle{nullptr};
  18 + aclrtContext ctx{nullptr};
  19 +};
  20 +
... ...
src/ai_engine_module/motor_phone_det.cpp 0 → 100755
  View file @f171c20
  1 +#include "motor_phone_det.h"
  2 +#include "sy_errorinfo.h"
  3 +#include "cnn_extractor.h"
  4 +#include "dvpp_processx.h"
  5 +#include <time.h>
  6 +#include <sys/time.h>
  7 +#include "stream_data.h"
  8 +#include <algorithm>
  9 +#include <map>
  10 +#include <cstring>
  11 +
  12 +
  13 +using namespace atlas_utils;
  14 +using namespace std;
  15 +
  16 +struct Resource {
  17 + aclrtContext ctx;
  18 + aclrtStream stream;
  19 +};
  20 +
  21 +typedef struct Tools {
  22 + Resource src;
  23 + CNNExtract* phoneDetMotor;
  24 + DvppProcessx* dvpp;
  25 +}Tools;
  26 +
  27 +
  28 +int motor_phone_init(void **handle, motor_phone_param param){
  29 +
  30 + int ret = SY_SUCCESS;
  31 + Tools* tools = new Tools;
  32 + // init resource
  33 + // ACL_CALL(aclInit(nullptr), ACL_SUCCESS, SY_FAILED);
  34 + // ACL_CALL(aclrtSetDevice(param.devId), ACL_SUCCESS, SY_FAILED);
  35 + // ACL_CALL(aclrtCreateContext(&tools->src.ctx, param.devId), ACL_SUCCESS, SY_FAILED);
  36 + ACL_CALL(aclrtCreateStream(&tools->src.stream), ACL_SUCCESS, SY_FAILED);
  37 +
  38 + // head_shoulder detection init
  39 + tools->phoneDetMotor = new CNNExtract();
  40 + tools->phoneDetMotor->config.confThr = param.thresld;
  41 +
  42 + ret = tools->phoneDetMotor->Init(param.modelNames);
  43 + if (ret != SY_SUCCESS) {
  44 + delete tools->phoneDetMotor;
  45 + tools->phoneDetMotor = nullptr;
  46 + return SY_FAILED;
  47 + }
  48 +
  49 + tools->dvpp = new DvppProcessx();
  50 + tools->dvpp->InitResource(tools->src.stream);
  51 +
  52 + *handle = tools;
  53 +
  54 + return SY_SUCCESS;
  55 +}
  56 +
  57 +
  58 +//======================= yolo v8 postprocess ============================//
  59 +float iou(float *lbox, float *rbox) {
  60 + float interBox[] = {
  61 + (std::max)(lbox[0] - lbox[2] / 2.f , rbox[0] - rbox[2] / 2.f), //left
  62 + (std::min)(lbox[0] + lbox[2] / 2.f , rbox[0] + rbox[2] / 2.f), //right
  63 + (std::max)(lbox[1] - lbox[3] / 2.f , rbox[1] - rbox[3] / 2.f), //top
  64 + (std::min)(lbox[1] + lbox[3] / 2.f , rbox[1] + rbox[3] / 2.f), //bottom
  65 + };
  66 +
  67 + if (interBox[2] > interBox[3] || interBox[0] > interBox[1])
  68 + return 0.0f;
  69 +
  70 + float interBoxS = (interBox[1] - interBox[0])*(interBox[3] - interBox[2]);
  71 + return interBoxS / (lbox[2] * lbox[3] + rbox[2] * rbox[3] - interBoxS);
  72 +}
  73 +
  74 +bool cmp(const vector<float>& a, const vector<float>& b) {
  75 + return a[4] > b[4];
  76 +}
  77 +
  78 +//wh20230330
  79 +//yolov5的数据结构是4个bbox + 检测置信度+ 多cls
  80 +//yolov8的数据结构是4个bbox + 多cls ，选多cls中最大值作为检测置信度
  81 +// void nms_yolov8(std::vector<vector<float>>& res, float *output, int outnum, int CLS_NUM, float conf_thresh, float nms_thresh = 0.5)
  82 +void nms_yolov8(std::vector<vector<float>>& res, std::vector<float> &output, int outnum, int CLS_NUM, float conf_thresh, float nms_thresh = 0.5)
  83 +{
  84 + //printf("nms_yolov8:outnum=%d,CLS_NUM=%d,conf_thresh=%f,nms_thresh=%f \n",outnum,CLS_NUM,conf_thresh,nms_thresh);
  85 + int det_size = 6;// sizeof(Yolo::Detection) / sizeof(float);
  86 + std::map<float, std::vector<vector<float>>> m;
  87 + for (int i = 0; i < outnum; i++)
  88 + {
  89 + //vector<float> cls_prob(CLS_NUM - 5);
  90 + vector<float> cls_prob(CLS_NUM - 4);//wh多cls的值
  91 + //memcpy(cls_prob.data(), &output[CLS_NUM * i + 5], (CLS_NUM - 5) * sizeof(float));
  92 + memcpy(cls_prob.data(), &output[CLS_NUM * i + 4], (CLS_NUM - 4) * sizeof(float));
  93 + auto maxPosition = max_element(cls_prob.begin(), cls_prob.end());//wh多cls的最大值
  94 +
  95 + //if (output[CLS_NUM * i + 4] <= conf_thresh) continue;
  96 + if (*maxPosition <= conf_thresh ) continue;
  97 + //if(1)
  98 + //{
  99 + // printf("nms_yolov8:output:[");
  100 + // for(int kk=0;kk<CLS_NUM;kk++)
  101 + // {
  102 + // printf("%f ",output[CLS_NUM * i + kk]);
  103 + // }
  104 + // printf(" ]\n");
  105 + //}
  106 +
  107 + vector<float> det(det_size);
  108 + //Yolo::Detection det;
  109 + //memcpy(&det[0], &output[CLS_NUM * i], (det_size - 1) * sizeof(float));
  110 + memcpy(&det[0], &output[CLS_NUM * i], (det_size - 2) * sizeof(float));
  111 + //det[4] = det[4]*(*maxPosition);
  112 + det[4] = (*maxPosition);
  113 + det[5] = maxPosition - cls_prob.begin();
  114 + //printf("nms_yolov8 det =%f-%f-%f-%f %f %f \n",det[0],det[1],det[2],det[3],det[4],det[5]);
  115 +
  116 + if (m.count(det[5]) == 0)
  117 + m.emplace(det[5], std::vector<vector<float>>());
  118 + m[det[5]].push_back(det);
  119 +
  120 + /*det.conf = det.conf*(*maxPosition);
  121 + det.class_id = maxPosition - cls_prob.begin();
  122 + if (m.count(det.class_id) == 0)
  123 + m.emplace(det.class_id, std::vector<Yolo::Detection>());
  124 + m[det.class_id].push_back(det);*/
  125 + }
  126 +
  127 + for (auto it = m.begin(); it != m.end(); it++) {
  128 + //std::cout << it->second[0].class_id << " --- " << std::endl;
  129 + auto& dets = it->second;
  130 + std::sort(dets.begin(), dets.end(), cmp);
  131 +
  132 + for (size_t m = 0; m < dets.size(); ++m) {
  133 + auto& item = dets[m];
  134 +
  135 + vector<float> det_temp(det_size);
  136 + //Yolo::Detection det_temp;
  137 + /*det_temp.conf = item.conf;
  138 + det_temp.class_id = item.class_id;
  139 + det_temp.bbox[0] = item.bbox[0] - item.bbox[2] / 2;
  140 + det_temp.bbox[1] = item.bbox[1] - item.bbox[3] / 2;
  141 + det_temp.bbox[2] = item.bbox[2];
  142 + det_temp.bbox[3] = item.bbox[3];*/
  143 +
  144 + det_temp[4] = item[4];
  145 + det_temp[5] = item[5];
  146 + det_temp[0] = item[0] - item[2] / 2;
  147 + det_temp[1] = item[1] - item[3] / 2;
  148 + det_temp[2] = item[2];
  149 + det_temp[3] = item[3];
  150 +
  151 + res.push_back(det_temp);
  152 +
  153 + for (size_t n = m + 1; n < dets.size(); ++n) {
  154 + if (iou(&item[0], &dets[n][0]) > nms_thresh) {
  155 + dets.erase(dets.begin() + n);
  156 + --n;
  157 + }
  158 + }
  159 + }
  160 + }
  161 +}
  162 +
  163 +int motor_phone_process_batch(void * handle, sy_img *image_data_array, int batchsize, motor_phone_result *result){
  164 + Tools* tools = (Tools*) handle;
  165 +
  166 + int inputW = tools->phoneDetMotor->GetInputWidth();
  167 + int inputH = tools->phoneDetMotor->GetInputHeight();
  168 +
  169 + //printf("debug inputw:%d,inputh:%d\n",inputW,inputH);
  170 +
  171 + for (int b = 0; b < batchsize; b++) {
  172 + if (image_data_array[b].data_ == NULL || image_data_array[b].w_ == 0 || image_data_array[b].h_ == 0) {
  173 + ERROR_LOG(" Headshoulder get null input ptr!");
  174 + return SY_FAILED;
  175 + }
  176 +
  177 + ImageData resizeImg, src;
  178 + // Utils::CopysyImageDataToDvpp(src, image_data_array[b]);
  179 + ACL_CALL(Utils::CopysyImageDataToDvppV2(src, image_data_array[b]), SY_SUCCESS, SY_FAILED);
  180 + ACL_CALL(tools->dvpp->CropAndPadding(resizeImg, src, inputW, inputH), SY_SUCCESS, SY_FAILED);
  181 + // forward
  182 + // double t1, t2;
  183 + // t1 = msecond();
  184 + int ret = tools->phoneDetMotor->Inference(resizeImg);
  185 + if (ret != SY_SUCCESS) {
  186 + return SY_MODEL_FORWARD_ERROR;
  187 + }
  188 + // t2 = msecond();
  189 + // printf("debug infer time: %.2f\n", t2 - t1);
  190 +
  191 + vector<float> detRes;
  192 + ret = tools->phoneDetMotor->PostProcess(detRes);
  193 + if (ret != SY_SUCCESS) {
  194 + return SY_MODEL_GETRESULT_ERROR;
  195 + }
  196 +
  197 + int img_w = image_data_array[b].w_;
  198 + int img_h = image_data_array[b].h_;
  199 + int INPUT_W = 224;//模型输入
  200 + int INPUT_H = 224;
  201 + // int max_obj_data_count = 10;//4+多类置信度(这里是6类) 0912/1013
  202 + int max_obj_data_count = 9;//4+多类置信度(这里是5类) 1127模型
  203 +
  204 + // printf("datacount:%d\n",detRes.size());
  205 + int num_det = detRes.size() / max_obj_data_count;
  206 +
  207 + int w, h, x, y;
  208 + float r_w = (float)INPUT_W / (img_w*1.0);
  209 + float r_h = (float)INPUT_H / (img_h*1.0);
  210 + float ratio = r_w < r_h ? r_w : r_h;
  211 + if (r_h > r_w) {
  212 + w = INPUT_W;
  213 + h = r_w * img_h;
  214 + x = 0;
  215 + y = (INPUT_H - h) / 2;
  216 + }
  217 + else {
  218 + w = r_h * img_w;
  219 + h = INPUT_H;
  220 + x = (INPUT_W - w) / 2;
  221 + y = 0;
  222 + }
  223 +
  224 +
  225 + vector<vector<float>> nms_res;
  226 + //printf("%d %d %d %d %d %d\n", img_w, img_h, w, h, x, y);
  227 + nms_yolov8(nms_res, detRes, num_det, max_obj_data_count, tools->phoneDetMotor->config.confThr, 0.7);
  228 +
  229 + int obj_count = 0;
  230 + result[b].objcount = 0;
  231 + for (int i = 0; i < nms_res.size(); i++)
  232 + {
  233 + //class_id, score, x1, y1, x2, y2
  234 + int index = nms_res[i][5];
  235 +
  236 + float detect_score = nms_res[i][4];
  237 + if(detect_score > tools->phoneDetMotor->config.confThr)
  238 + {
  239 +
  240 + int x1 = (nms_res[i][0] - x) / ratio;
  241 + int y1 = (nms_res[i][1] - y) / ratio;
  242 + int x2 = nms_res[i][2] / ratio + x1;
  243 + int y2 = nms_res[i][3] / ratio + y1;
  244 +
  245 + //边界判断
  246 + if(x1<0)x1=0;
  247 + if(y1<0)y1=0;
  248 + if(x2>=img_w) x2 = img_w-1;
  249 + if(y2>=img_h) y2 = img_h-1;
  250 +
  251 + result[b].objinfo[obj_count].left = x1;
  252 + result[b].objinfo[obj_count].top = y1;
  253 + result[b].objinfo[obj_count].right = x2;
  254 + result[b].objinfo[obj_count].bottom = y2;
  255 +
  256 + result[b].objinfo[obj_count].confidence = detect_score;
  257 + result[b].objinfo[obj_count].index = index;
  258 +
  259 + obj_count++;
  260 + }
  261 + }
  262 + result[b].objcount =obj_count;
  263 +
  264 + vector<vector<float>>().swap(nms_res);
  265 + vector<float>().swap(detRes);
  266 +
  267 +
  268 +
  269 + // result[i].objcount = detRes.size() > MAX_OBJ_COUNT ? MAX_OBJ_COUNT : detRes.size();
  270 + // int objIdx = 0;
  271 + // for (auto& det : detRes) {
  272 + // if (objIdx >= MAX_OBJ_COUNT) continue;
  273 + // result[i].objinfo[objIdx].left = det[2];
  274 + // result[i].objinfo[objIdx].top = det[3];
  275 + // result[i].objinfo[objIdx].right = det[4];
  276 + // result[i].objinfo[objIdx].bottom = det[5];
  277 + // result[i].objinfo[objIdx].confidence = det[1];
  278 + // objIdx++;
  279 +
  280 + // }
  281 +
  282 +
  283 + }
  284 +
  285 + return SY_SUCCESS;
  286 +}
  287 +
  288 +void motor_phone_release(void **handle) {
  289 + Tools* tools = (Tools*) handle;
  290 + if (tools) {
  291 + if (tools->phoneDetMotor) {
  292 + //delete tools->phoneDetMotor;
  293 + tools->phoneDetMotor = nullptr;
  294 + }
  295 + if (tools->dvpp) {
  296 + //delete tools->dvpp;
  297 + tools->dvpp = nullptr;
  298 + }
  299 + // aclFinalize();
  300 + //delete tools;
  301 + tools = NULL;
  302 + }
  303 +}
  304 +
  305 +const char * motor_phone_getversion() {
  306 + return "motor_phone_vdec_arm_v310p_0.0.2.20231127_without_timelimit";
  307 +}
... ...
src/ai_engine_module/motor_phone_det.h 0 → 100755
  View file @f171c20
  1 +/*******************************************************************************************
  2 +* Version: motor_phone_det_x64_v0.0.1
  3 +* CopyRight: 中科视语（北京）科技有限公司
  4 +* UpdateDate: 20230911
  5 +* Content：二轮车玩手机检测
  6 +********************************************************************************************/
  7 +#ifndef MOTOR_PHONE_DET_H_
  8 +#define MOTOR_PHONE_DET_H_
  9 +
  10 +#ifdef _MSC_VER
  11 +#ifdef MOTOR_PHONE_DET_EXPORTS
  12 +#define MOTOR_PHONE_DET_API __declspec(dllexport)
  13 +#else
  14 +#define MOTOR_PHONE_DET_API __declspec(dllimport)
  15 +#endif
  16 +#else
  17 +#define MOTOR_PHONE_DET_API __attribute__ ((visibility ("default")))
  18 +#endif
  19 +
  20 +#include "sy_common.h"
  21 +
  22 +#define MAX_OBJ_COUNT 1000
  23 +
  24 +#ifdef __cplusplus
  25 +extern "C"
  26 +{
  27 +#endif
  28 +
  29 + typedef struct motor_phone_info //结果结构体
  30 + {
  31 + int left;
  32 + int top;
  33 + int right;
  34 + int bottom;
  35 + int index;
  36 + double confidence; // 置信度
  37 + }motor_phone_info;
  38 +
  39 + typedef struct motor_phone_result
  40 + {
  41 + motor_phone_info objinfo[MAX_OBJ_COUNT];
  42 + int objcount;
  43 + };
  44 +
  45 + typedef struct motor_phone_param
  46 + {
  47 + //int mode; //运行模式 GPU_MODE 或者 CPU_MODE
  48 + int devId; //运行卡号 GPU模式下有效
  49 + char* modelNames;
  50 + float thresld; //检测阈值 默认为0.3
  51 +
  52 + //int engine; //指定运行引擎(ENGINE_MCAFFE2 / ENGINE_TENSORRT)
  53 + //int max_batch; //ָ指定trt最大batch数
  54 + //char* trt_serialize_file;
  55 + //motor_phone_param() :mode(DEVICE_GPU), gpuid(0), thresld(0.4), engine(ENGINE_MCAFFE2), max_batch(10){};
  56 + }motor_phone_param;
  57 +
  58 + /*************************************************************************
  59 + * FUNCTION: hst_init
  60 + * PURPOSE: 初始化
  61 + * PARAM:
  62 + [in] handle -处理句柄
  63 + [in] param -初始化参数
  64 + * RETURN: handle
  65 + * NOTES:成功(0)或者错误代码(<0)
  66 + *************************************************************************/
  67 + MOTOR_PHONE_DET_API int motor_phone_init(void **handle, motor_phone_param param);
  68 + MOTOR_PHONE_DET_API int motor_phone_process_batch(void * handle, sy_img *image_data_array, int batchsize, motor_phone_result *result);
  69 +
  70 + /*************************************************************************
  71 + * FUNCTION: hst_release
  72 + * PURPOSE: 资源释放
  73 + * PARAM:
  74 + [in] handle - 处理句柄
  75 + * RETURN: NULL
  76 + * NOTES:
  77 + *************************************************************************/
  78 + MOTOR_PHONE_DET_API void motor_phone_release(void **handle);
  79 +
  80 +
  81 + /*************************************************************************
  82 + * FUNCTION: hst_process_gpu
  83 + * PURPOSE:
  84 + * PARAM:
  85 + [in] handle - 处理句柄
  86 + [in] rgb - 图片数据（3通道BGR数据 cv::Mat格式）
  87 + [in] width - 图片宽度
  88 + [in] height - 图片高度
  89 + [in] result - 搜索结果，在外部申请足够内存
  90 + * RETURN: -1：图像错误； 其他：检测到的个数
  91 + * NOTES:
  92 + *************************************************************************/
  93 + MOTOR_PHONE_DET_API int motor_phone_process(void * handle, sy_img image, motor_phone_result *result);
  94 +
  95 + /*************************************************************************
  96 + * FUNCTION: hst_getversion
  97 + * PURPOSE: 释放
  98 + * PARAM: NULL
  99 + * RETURN: 版本号
  100 + * NOTES:
  101 + *************************************************************************/
  102 + MOTOR_PHONE_DET_API const char * motor_phone_getversion();
  103 +
  104 +#ifdef __cplusplus
  105 +};
  106 +#endif
  107 +
  108 +#endif
... ...
src/ai_engine_module/motor_rainshed_cls.cpp 0 → 100755
  View file @f171c20
  1 +#include "motor_rainshed_cls.h"
  2 +#include "sy_errorinfo.h"
  3 +#include "cnn_cls.h"
  4 +#include "dvpp_processx.h"
  5 +#include <time.h>
  6 +#include <sys/time.h>
  7 +#include "stream_data.h"
  8 +
  9 +
  10 +using namespace atlas_utils;
  11 +using namespace std;
  12 +
  13 +struct Resource {
  14 + aclrtContext ctx;
  15 + aclrtStream stream;
  16 +};
  17 +
  18 +typedef struct Tools {
  19 + Resource src;
  20 + CnnCls* mRainCls;
  21 + DvppProcessx* dvpp;
  22 +}Tools;
  23 +
  24 +int mrc_init(void** handle, mrc_param param) {
  25 +
  26 + int ret = SY_SUCCESS;
  27 + Tools* tools = new Tools;
  28 + // init resource
  29 + // ACL_CALL(aclInit(nullptr), ACL_SUCCESS, SY_FAILED);
  30 + // ACL_CALL(aclrtSetDevice(param.devId), ACL_SUCCESS, SY_FAILED);
  31 + // ACL_CALL(aclrtCreateContext(&tools->src.ctx, param.devId), ACL_SUCCESS, SY_FAILED);
  32 + ACL_CALL(aclrtCreateStream(&tools->src.stream), ACL_SUCCESS, SY_FAILED);
  33 +
  34 + // motor rainshed classfication init
  35 + tools->mRainCls = new CnnCls();
  36 + tools->mRainCls->config.confThr = param.thresld;
  37 + ret = tools->mRainCls->Init(param.modelNames);
  38 + if (ret != SY_SUCCESS) {
  39 + delete tools->mRainCls;
  40 + tools->mRainCls = nullptr;
  41 + return SY_FAILED;
  42 + }
  43 +
  44 + tools->dvpp = new DvppProcessx();
  45 + tools->dvpp->InitResource(tools->src.stream);
  46 +
  47 + *handle = tools;
  48 +
  49 + return SY_SUCCESS;
  50 +}
  51 +
  52 +
  53 +// double msecond() {
  54 +// struct timeval tv;
  55 +// gettimeofday(&tv, 0);
  56 +// return (tv.tv_sec * 1000.0 + tv.tv_usec / 1000.0);
  57 +// }
  58 +
  59 +int mrc_batch(void * handle, sy_img *img_data_array, int batch_size, mrc_result *result) {
  60 + Tools* tools = (Tools*) handle;
  61 +
  62 + int inputW = tools->mRainCls->GetInputWidth();
  63 + int inputH = tools->mRainCls->GetInputHeight();
  64 +
  65 + // printf("debug inputw:%d,inputh:%d\n",inputW,inputH);
  66 +
  67 + for (int i = 0; i < batch_size; i++) {
  68 + if (img_data_array[i].data_ == NULL || img_data_array[i].w_ == 0 || img_data_array[i].h_ == 0) {
  69 + ERROR_LOG("mRainCls get null input ptr!");
  70 + return SY_FAILED;
  71 + }
  72 + ImageData resizeImg, src;
  73 + //debug========================================================================
  74 + // src.width = img_data_array[i].w_;
  75 + // src.height = img_data_array[i].h_;
  76 + // src.alignWidth = ((src.width + 127) & ~(127));
  77 + // src.alignHeight = ((src.height + 15) & ~(15));
  78 + // src.size = src.alignWidth * src.alignHeight * 1.5;
  79 + // src.data.reset((uint8_t*)img_data_array[i].data_, [](uint8_t* p) { acldvppFree((void *)p); });
  80 + //debug end====================================================================
  81 + // Utils::CopysyImageDataToDvpp(src, img_data_array[i]);
  82 + ACL_CALL(Utils::CopysyImageDataToDvppV2(src, img_data_array[i]), SY_SUCCESS, SY_FAILED);
  83 + ACL_CALL(tools->dvpp->CropAndPaste(resizeImg, src, inputW, inputH), SY_SUCCESS, SY_FAILED);
  84 + // forward
  85 + //double t1, t2;
  86 + //t1 = msecond();
  87 + int ret = tools->mRainCls->Inference(resizeImg);
  88 + if (ret != SY_SUCCESS) {
  89 + return SY_MODEL_FORWARD_ERROR;
  90 + }
  91 + //t2 = msecond();
  92 + //printf("debug infer time: %.2f\n", t2 - t1);
  93 +
  94 + vector<float> mRainClsRes;
  95 + ret = tools->mRainCls->PostProcess(mRainClsRes);
  96 + if (ret != SY_SUCCESS) {
  97 + return SY_MODEL_GETRESULT_ERROR;
  98 + }
  99 + result[i].index = mRainClsRes[0];
  100 + result[i].score = mRainClsRes[1];
  101 + // printf("debug index:%d,confidence:%f\n",result[i].index,result[i].score);
  102 + // for (auto res : mRainClsRes) {
  103 + // printf("debug info: %f\n",res);
  104 + // }
  105 +
  106 + }
  107 +
  108 + return SY_SUCCESS;
  109 +}
  110 +
  111 +void mrc_release(void **handle) {
  112 + Tools* tools = (Tools*) handle;
  113 + // printf("debug line:%d\n",__LINE__);
  114 + if (tools) {
  115 + if (tools->mRainCls) {
  116 + // delete tools->mRainCls;
  117 + tools->mRainCls = nullptr;
  118 + }
  119 + // printf("debug line:%d\n",__LINE__);
  120 + if (tools->dvpp) {
  121 + // delete tools->dvpp;
  122 + tools->dvpp = nullptr;
  123 + }
  124 + //printf("debug line:%d\n",__LINE__);
  125 + // aclFinalize();
  126 + aclrtDestroyStream(&tools->src.stream);
  127 + // delete tools;
  128 + tools = NULL;
  129 + //printf("debug line:%d\n",__LINE__);
  130 + }
  131 +}
  132 +
  133 +const char * mrc_get_version() {
  134 + return "motorrc_arm_vdec_310p_v0.0.1.20230921_without_timelimit";
  135 +}
0 136 \ No newline at end of file
... ...
src/ai_engine_module/motor_rainshed_cls.h 0 → 100755
  View file @f171c20
  1 +/*************************************************************************
  2 +* Version: motor_rainshed_cls_v0.0.0.20230921
  3 +* CopyRight : 中国科学院自动化所模式识别实验室图像视频组
  4 +* UpdateDate：20230921
  5 +* Content : 二轮车是否加装雨棚
  6 +*************************************************************************/
  7 +#ifndef MOTORRAINCLS_H_
  8 +#define MOTORRAINCLS_H_
  9 +
  10 +#if _MSC_VER
  11 +#ifdef MOTORRAINCLS_EXPORTS
  12 +#define MOTORRAINCLS_API __declspec(dllexport)
  13 +#else
  14 +#define MOTORRAINCLS_API __declspec(dllimport)
  15 +#endif
  16 +#else
  17 +#define MOTORRAINCLS_API __attribute__ ((visibility ("default")))
  18 +#endif
  19 +
  20 +#include "sy_common.h"
  21 +
  22 +
  23 +
  24 +#ifndef MAX_BATCH_SIZE
  25 +#define MAX_BATCH_SIZE 16
  26 +#endif
  27 +
  28 +
  29 +#ifdef __cplusplus
  30 +extern "C"
  31 +{
  32 +#endif
  33 +
  34 +
  35 +
  36 +//分类结果
  37 +#ifndef MRCRESULT_
  38 +#define MRCRESULT_
  39 +typedef struct mrc_result
  40 +{
  41 + float score;
  42 + int index;
  43 +}mrc_result;
  44 +#endif
  45 +
  46 +
  47 +#ifndef __MRCPARAM__
  48 +#define __MRCPARAM__
  49 + typedef struct mrc_param
  50 + {
  51 + //int mode; //运行模式(DEVICE_GPU / DEVICE_CPU)
  52 + //mrc_param() :mode(DEVICE_GPU), gpuid(0) {};
  53 + int devId; //ָ指定显卡id
  54 + char* modelNames;
  55 + float thresld; //阈值
  56 + }mrc_param;
  57 +#endif
  58 +
  59 + /*************************************************************************
  60 + * FUNCTION: mrc_init
  61 + * PURPOSE: 载入模型
  62 + * PARAM:
  63 + [in] handle - 句柄
  64 + [in] params - 参数
  65 + * RETURN: 成功（0）或者错误代码
  66 + * NOTES:
  67 + *************************************************************************/
  68 + MOTORRAINCLS_API int mrc_init(void ** handle, mrc_param param);
  69 +
  70 + /*************************************************************************
  71 + * FUNCTION: mrc_process
  72 + * PURPOSE: 二轮车加装雨棚分类
  73 + * PARAM:
  74 + [in] handle - 检测句柄
  75 + [in] img_data - 图像数据
  76 + [in] result - 结果 内存在外部申请
  77 + * RETURN: 成功(0) 或 错误代码（< 0）
  78 + * NOTES:
  79 + *************************************************************************/
  80 + MOTORRAINCLS_API int mrc_process(void *handle, sy_img img_data, mrc_result * result);
  81 +
  82 + /*************************************************************************
  83 + * FUNCTION: mrc_batch
  84 + * PURPOSE: 二轮车加装雨棚分类 batch
  85 + * PARAM:
  86 + [in] handle - 检测句柄
  87 + [in] img_data_array - 图像数据
  88 + [in] batch_size - 图像数目
  89 + [in] result - 结果 内存在外部申请
  90 + * RETURN: 成功(0) 或 错误代码（< 0）
  91 + * NOTES:
  92 + *************************************************************************/
  93 + MOTORRAINCLS_API int mrc_batch(void *handle, sy_img* img_data_array, int batch_size, mrc_result * result);
  94 +
  95 +
  96 + /*************************************************************************
  97 + * FUNCTION: mrc_release
  98 + * PURPOSE: 释放
  99 + * PARAM:
  100 + [in] handle - handle
  101 + * RETURN: NULL
  102 + * NOTES:
  103 + *************************************************************************/
  104 + MOTORRAINCLS_API void mrc_release(void ** handle);
  105 +
  106 +
  107 + /*************************************************************************
  108 + * FUNCTION: mrc_get_version
  109 + * PURPOSE:
  110 + * PARAM: NULL
  111 + * RETURN: 版本号
  112 + * NOTES:
  113 + *************************************************************************/
  114 + MOTORRAINCLS_API const char * mrc_get_version();
  115 +
  116 +#ifdef __cplusplus
  117 +};
  118 +#endif
  119 +
  120 +#endif
... ...
src/common/cnn/cnn_extractor.cpp 0 → 100755
  View file @f171c20
  1 +#include "cnn_extractor.h"
  2 +#include <iostream>
  3 +#include "acl/acl.h"
  4 +#include "model_process.h"
  5 +#include "sy_errorinfo.h"
  6 +#include <time.h>
  7 +#include <sys/time.h>
  8 +#include <algorithm>
  9 +
  10 +using namespace std;
  11 +
  12 +namespace atlas_utils {
  13 +
  14 +int CNNExtract::Init(const char* modelPath) {
  15 + ACL_CALL(aclrtGetRunMode(&runMode_), SY_SUCCESS, SY_FAILED);//获取当前昇腾AI软件栈的运行模式，根据不同的运行模式，后续的接口调用方式不同
  16 + ACL_CALL(model_.LoadModelFromFileWithMem(modelPath), SY_SUCCESS, SY_FAILED);//从文件加载离线模型数据，由用户自行管理模型运行的内存
  17 + ACL_CALL(model_.CreateDesc(), SY_SUCCESS, SY_FAILED);//获取模型的描述信息
  18 + ACL_CALL(model_.CreateOutput(outDims_), SY_SUCCESS, SY_FAILED);
  19 + ACL_CALL(model_.GetInputDims(inDims_), SY_SUCCESS, SY_FAILED);
  20 + modelHeight_ = inDims_[0][1];
  21 + modelWidth_ = inDims_[0][2];
  22 +
  23 + return SY_SUCCESS;
  24 +}
  25 +
  26 +
  27 +int CNNExtract::Inference(ImageData& input) {
  28 + model_.CreateInput(input.data.get(), input.size);
  29 + ACL_CALL(model_.Execute(), SY_SUCCESS, SY_FAILED);
  30 + model_.DestroyInput(); //需调用CreateInput的销毁类接口DestroyInput！！！
  31 + return SY_SUCCESS;
  32 +}
  33 +
  34 +int CNNExtract::GetInputWidth() {
  35 + return modelWidth_;
  36 +}
  37 +
  38 +int CNNExtract::GetInputHeight() {
  39 + return modelHeight_;
  40 +}
  41 +
  42 +int CNNExtract::PostProcess(vector<float>& results) {
  43 + aclmdlDataset* modelOutput = model_.GetModelOutputData();
  44 + int outDatasetNum = aclmdlGetDatasetNumBuffers(modelOutput);
  45 + for (int i = 0; i < outDatasetNum; i++) {
  46 + aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(modelOutput, i);
  47 + if (dataBuffer == nullptr) {
  48 + return SY_FAILED;
  49 + }
  50 + uint32_t dataBufferSize = aclGetDataBufferSize(dataBuffer);
  51 + void* data = aclGetDataBufferAddr(dataBuffer);
  52 + if (data == nullptr) {
  53 + return SY_FAILED;
  54 + }
  55 +
  56 + int length = dataBufferSize/sizeof(float);
  57 + float outInfo[length];
  58 +
  59 + if (runMode_ == ACL_HOST) {
  60 + ACL_CALL(aclrtMemcpy(outInfo, sizeof(outInfo), data, sizeof(outInfo), ACL_MEMCPY_DEVICE_TO_HOST),
  61 + ACL_SUCCESS, SY_FAILED);
  62 + } else {
  63 + ACL_CALL(aclrtMemcpy(outInfo, sizeof(outInfo), data, sizeof(outInfo), ACL_MEMCPY_DEVICE_TO_DEVICE),ACL_SUCCESS, SY_FAILED);
  64 + //return SY_FAILED;
  65 + }
  66 +
  67 + // //归一化
  68 + // float sum = 0.0;
  69 + // for(int j=0;j<length;j++){
  70 + // sum = sum + outInfo[j]*outInfo[j];
  71 + // }
  72 + // sum = sqrt(sum) + 1e-6;
  73 + // for(int j=0;j<length;j++){
  74 + // results.emplace_back(outInfo[j]/sum);
  75 + // }
  76 +
  77 +
  78 + for(uint32_t b = 0; b < length; b++) {
  79 + results.emplace_back(outInfo[b]);
  80 + }
  81 +
  82 + }
  83 +
  84 +
  85 + return SY_SUCCESS;
  86 +}
  87 +
  88 +void CNNExtract::Release() {
  89 + model_.Unload();
  90 + model_.DestroyDesc();
  91 + model_.DestroyOutput();
  92 +}
  93 +
  94 +}
... ...
src/common/cnn/cnn_extractor.h 0 → 100755
  View file @f171c20
  1 +#ifndef _CNN_EXTRACT_H_
  2 +#define _CNN_EXTRACT_H_
  3 +
  4 +#include <memory>
  5 +#include "utils.h"
  6 +#include "acl/acl.h"
  7 +#include "model_process.h"
  8 +
  9 +using namespace std;
  10 +
  11 +namespace atlas_utils {
  12 +
  13 +
  14 +#ifndef DATA_TYPE_SIZE
  15 +#define DATA_TYPE_SIZE 4
  16 +#endif
  17 +
  18 +class CNNExtract {
  19 +public:
  20 + struct ConfigParams {
  21 + float confThr = 0.0;
  22 + };
  23 +
  24 + CNNExtract() {}
  25 + ~CNNExtract() {
  26 + Release();
  27 + }
  28 +
  29 + int Init(const char* modelPath);
  30 + int Inference(ImageData& input);
  31 + int PostProcess(vector<float>& result);
  32 +
  33 + int GetInputWidth();
  34 + int GetInputHeight();
  35 +
  36 + ConfigParams config;
  37 +
  38 +private:
  39 + void Release();
  40 +
  41 + vector<vector<int>> outDims_;
  42 + vector<vector<int>> inDims_;
  43 + ModelProcess model_;
  44 + uint32_t modelWidth_;
  45 + uint32_t modelHeight_;
  46 + aclrtRunMode runMode_;
  47 +
  48 +};
  49 +
  50 +}
  51 +
  52 +#endif
... ...