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update knowing application and framework from Tian_Chunyu

it is OK
master
xuedongliang 1 year ago
parent
commit
3f9904eb53
  1. 1
      .gitignore
  2. 3
      APP_Framework/Applications/knowing_app/Kconfig
  3. 1
      APP_Framework/Applications/knowing_app/face_detect/Kconfig
  4. 35
      APP_Framework/Applications/knowing_app/face_detect/README.md
  5. 36
      APP_Framework/Applications/knowing_app/face_detect/detect.json
  6. BIN
      APP_Framework/Applications/knowing_app/face_detect/detect.kmodel
  7. 416
      APP_Framework/Applications/knowing_app/face_detect/face_detect.c
  8. 8
      APP_Framework/Applications/knowing_app/helmet_detect/Kconfig
  9. 167
      APP_Framework/Applications/knowing_app/helmet_detect/README.md
  10. 9
      APP_Framework/Applications/knowing_app/helmet_detect/SConscript
  11. 38
      APP_Framework/Applications/knowing_app/helmet_detect/helmet.json
  12. BIN
      APP_Framework/Applications/knowing_app/helmet_detect/helmet.kmodel
  13. 380
      APP_Framework/Applications/knowing_app/helmet_detect/helmet_detect.c
  14. 8
      APP_Framework/Applications/knowing_app/instrusion_detect/Kconfig
  15. 5
      APP_Framework/Applications/knowing_app/instrusion_detect/README.md
  16. 9
      APP_Framework/Applications/knowing_app/instrusion_detect/SConscript
  17. 36
      APP_Framework/Applications/knowing_app/instrusion_detect/human.json
  18. BIN
      APP_Framework/Applications/knowing_app/instrusion_detect/human.kmodel
  19. 380
      APP_Framework/Applications/knowing_app/instrusion_detect/instrusion_detect.c
  20. 57
      APP_Framework/Applications/knowing_app/iris_ml_demo/DecisionTreeClassifierModel.h
  21. 3
      APP_Framework/Applications/knowing_app/iris_ml_demo/Kconfig
  22. 41
      APP_Framework/Applications/knowing_app/iris_ml_demo/LogisticRegressionModel.h
  23. 71
      APP_Framework/Applications/knowing_app/iris_ml_demo/README.md
  24. 9
      APP_Framework/Applications/knowing_app/iris_ml_demo/SConscript
  25. 78
      APP_Framework/Applications/knowing_app/iris_ml_demo/SVCModel.h
  26. 7
      APP_Framework/Applications/knowing_app/iris_ml_demo/iris.csv
  27. 98
      APP_Framework/Applications/knowing_app/iris_ml_demo/iris_ml_demo.c
  28. 10
      APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/README.md
  29. 220
      APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/region_layer.c
  30. 4
      APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/region_layer.h
  31. 6
      APP_Framework/lib/Kconfig
  32. 14
      APP_Framework/lib/SConscript
  33. 3
      APP_Framework/lib/cJSON/Kconfig
  34. 10
      APP_Framework/lib/cJSON/SConscript
  35. 3110
      APP_Framework/lib/cJSON/cJSON.c
  36. 293
      APP_Framework/lib/cJSON/cJSON.h
  37. 39
      Ubiquitous/RT_Thread/bsp/k210/.config
  38. 228
      Ubiquitous/RT_Thread/bsp/k210/.gitignore
  39. 3
      Ubiquitous/RT_Thread/bsp/k210/SConstruct
  40. 2
      Ubiquitous/RT_Thread/bsp/k210/base-drivers/drv_dvp.c
  41. 26
      Ubiquitous/RT_Thread/bsp/k210/rtconfig.h
  42. 6
      Ubiquitous/RT_Thread/bsp/stm32f407-atk-coreboard/.config
  43. 233
      Ubiquitous/RT_Thread/bsp/stm32f407-atk-coreboard/.gitignore
  44. 3
      Ubiquitous/RT_Thread/bsp/stm32f407-atk-coreboard/SConstruct
  45. 5
      Ubiquitous/RT_Thread/bsp/stm32f407-atk-coreboard/rtconfig.h
  46. 2
      Ubiquitous/RT_Thread/bsp/stm32f407-atk-coreboard/rtconfig.py
  47. 17
      Ubiquitous/RT_Thread/drivers/ov2640/ov2640_source/drv_ov2640.c
  48. 14
      Ubiquitous/RT_Thread/drivers/ov2640/ov2640_source/drv_ov2640.h

1
.gitignore

@ -1,2 +1,3 @@
*.vscode
*.o
.DS_Store

3
APP_Framework/Applications/knowing_app/Kconfig

@ -1,4 +1,7 @@
menu "knowing app"
source "$APP_DIR/Applications/knowing_app/mnist/Kconfig"
source "$APP_DIR/Applications/knowing_app/face_detect/Kconfig"
source "$APP_DIR/Applications/knowing_app/instrusion_detect/Kconfig"
source "$APP_DIR/Applications/knowing_app/helmet_detect/Kconfig"
source "$APP_DIR/Applications/knowing_app/iris_ml_demo/Kconfig"
endmenu

1
APP_Framework/Applications/knowing_app/face_detect/Kconfig

@ -4,4 +4,5 @@ config FACE_DETECT
depends on DRV_USING_OV2640
depends on USING_KPU_POSTPROCESSING
depends on USING_YOLOV2
select LIB_USING_CJSON
default n

35
APP_Framework/Applications/knowing_app/face_detect/README.md

@ -0,0 +1,35 @@
# Face detection demo
### A face object detection task demo. Running MobileNet-yolo on K210-based edge devices.
---
## Training
kmodel from [GitHub](https://github.com/kendryte/kendryte-standalone-demo/blob/develop/face_detect/detect.kmodel).
## Deployment
### compile and burn
Use `(scons --)menuconfig` in bsp folder *(Ubiquitous/RT_Thread/bsp/k210)*, open:
- More Drivers --> ov2640 driver
- Board Drivers Config --> Enable LCD on SPI0
- Board Drivers Config --> Enable SDCARD (spi1(ss0))
- Board Drivers Config --> Enable DVP(camera)
- RT-Thread Components --> POSIX layer and C standard library --> Enable pthreads APIs
- APP_Framework --> Framework --> support knowing framework --> kpu model postprocessing --> yolov2 region layer
- APP_Framework --> Applications --> knowing app --> enable apps/face detect
`scons -j(n)` to compile and burn in by *kflash*.
### json config and kmodel
Copy json config for deployment o SD card */kmodel*. Example config file is *detect.json* in this directory. Copy final kmodel to SD card */kmodel* either.
---
## Run
In serial terminal, `face_detect` to start a detection thread, `face_detect_delete` to stop it. Detection results can be found in output.

36
APP_Framework/Applications/knowing_app/face_detect/detect.json

@ -0,0 +1,36 @@
{
"net_input_size": [
240,
320
],
"net_output_shape": [
20,
15,
30
],
"sensor_output_size": [
240,
320
],
"anchors": [
1.889,
2.5245,
2.9465,
3.94056,
3.99987,
5.3658,
5.155437,
6.92275,
6.718375,
9.01025
],
"kmodel_path": "/kmodel/detect.kmodel",
"kmodel_size": 388776,
"obj_thresh": [
0.7
],
"labels": [
"face"
],
"nms_thresh": 0.3
}

BIN
APP_Framework/Applications/knowing_app/face_detect/detect.kmodel

Binary file not shown.

416
APP_Framework/Applications/knowing_app/face_detect/face_detect.c

@ -1,118 +1,245 @@
#include <transform.h>
#include"region_layer.h"
#define SHOW_RGB_BUF_SIZE (320*240*2)
#define AI_KPU_RGB_BUF_SIZE (320*240*3)
#define KMODEL_SIZE (388776) //face model size
#ifdef LIB_USING_CJSON
#include <cJSON.h>
#endif
#include "region_layer.h"
#define ANCHOR_NUM 5
#define KPUIMAGEWIDTH (320)
#define KPUIMAGEHEIGHT (240)
#define STACK_SIZE (128 * 1024)
#define JSON_FILE_PATH "/kmodel/detect.json"
#define JSON_BUFFER_SIZE (4 * 1024)
static float anchor[ANCHOR_NUM * 2] = {1.889,2.5245, 2.9465,3.94056, 3.99987,5.3658, 5.155437,6.92275, 6.718375,9.01025};
// params from json
static float anchor[ANCHOR_NUM * 2] = {};
static int net_output_shape[3] = {};
static int net_input_size[2] = {};
static int sensor_output_size[2] = {};
static char kmodel_path[127] = "";
static int kmodel_size = 0;
static float obj_thresh[20] = {};
static float nms_thresh = 0.0;
static char labels[20][32] = {};
static int class_num = 0;
#define THREAD_PRIORITY_FACE_D (11)
static pthread_t facetid = 0;
static void* thread_face_detcet_entry(void *parameter);
#define THREAD_PRIORITY_FACE_D (11)
static pthread_t facetid = 0;
static void *thread_face_detcet_entry(void *parameter);
static int g_fd = 0;
static int kmodel_fd = 0;
static int if_exit = 0;
static unsigned char * showbuffer = NULL ;
static unsigned char * kpurgbbuffer = NULL ;
static int if_exit = 0;
static unsigned char *showbuffer = NULL;
static unsigned char *kpurgbbuffer = NULL;
static _ioctl_shoot_para shoot_para_t = {0};
unsigned char * model_data = NULL; //kpu data load memory
unsigned char *model_data_align = NULL;
unsigned char *model_data = NULL; // kpu data load memory
unsigned char *model_data_align = NULL;
kpu_model_context_t face_detect_task;
static region_layer_t face_detect_rl;
static obj_info_t face_detect_info;
volatile uint32_t g_ai_done_flag;
static void ai_done(void *ctx)
static void ai_done(void *ctx) { g_ai_done_flag = 1; }
static void param_parse()
{
g_ai_done_flag = 1;
}
int fin;
char buffer[JSON_BUFFER_SIZE] = "";
// char *buffer;
// if (NULL != (buffer = (char*)malloc(JSON_BUFFER_SIZE * sizeof(char)))) {
// memset(buffer, 0, JSON_BUFFER_SIZE * sizeof(char));
// } else {
// printf("Json buffer malloc failed!");
// exit(-1);
// }
int array_size;
cJSON *json_obj;
cJSON *json_item;
cJSON *json_array_item;
fin = open(JSON_FILE_PATH, O_RDONLY);
if (!fin) {
printf("Error open file %s", JSON_FILE_PATH);
exit(-1);
}
read(fin, buffer, sizeof(buffer));
close(fin);
// read json string
json_obj = cJSON_Parse(buffer);
// free(buffer);
char *json_print_str = cJSON_Print(json_obj);
printf("Json file content: \n%s\n", json_print_str);
cJSON_free(json_print_str);
// get anchors
json_item = cJSON_GetObjectItem(json_obj, "anchors");
array_size = cJSON_GetArraySize(json_item);
if (ANCHOR_NUM * 2 != array_size) {
printf("Expect anchor size: %d, got %d in json file", ANCHOR_NUM * 2, array_size);
exit(-1);
} else {
printf("Got %d anchors from json file\n", ANCHOR_NUM);
}
for (int i = 0; i < ANCHOR_NUM * 2; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
anchor[i] = json_array_item->valuedouble;
printf("%d: %f\n", i, anchor[i]);
}
// net_input_size
json_item = cJSON_GetObjectItem(json_obj, "net_input_size");
array_size = cJSON_GetArraySize(json_item);
if (2 != array_size) {
printf("Expect net_input_size: %d, got %d in json file", 2, array_size);
exit(-1);
} else {
printf("Got %d net_input_size from json file\n", 2);
}
for (int i = 0; i < 2; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
net_input_size[i] = json_array_item->valueint;
printf("%d: %d\n", i, net_input_size[i]);
}
// net_output_shape
json_item = cJSON_GetObjectItem(json_obj, "net_output_shape");
array_size = cJSON_GetArraySize(json_item);
if (3 != array_size) {
printf("Expect net_output_shape: %d, got %d in json file", 3, array_size);
exit(-1);
} else {
printf("Got %d net_output_shape from json file\n", 3);
}
for (int i = 0; i < 3; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
net_output_shape[i] = json_array_item->valueint;
printf("%d: %d\n", i, net_output_shape[i]);
}
// sensor_output_size
json_item = cJSON_GetObjectItem(json_obj, "sensor_output_size");
array_size = cJSON_GetArraySize(json_item);
if (2 != array_size) {
printf("Expect sensor_output_size: %d, got %d in json file", 2, array_size);
exit(-1);
} else {
printf("Got %d sensor_output_size from json file\n", 2);
}
for (int i = 0; i < 2; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
sensor_output_size[i] = json_array_item->valueint;
printf("%d: %d\n", i, sensor_output_size[i]);
}
// kmodel_path
json_item = cJSON_GetObjectItem(json_obj, "kmodel_path");
memcpy(kmodel_path, json_item->valuestring, strlen(json_item->valuestring));
printf("Got kmodel_path: %s\n", kmodel_path);
// kmodel_size
json_item = cJSON_GetObjectItem(json_obj, "kmodel_size");
kmodel_size = json_item->valueint;
printf("Got kmodel_size: %d\n", kmodel_size);
// labels
json_item = cJSON_GetObjectItem(json_obj, "labels");
class_num = cJSON_GetArraySize(json_item);
if (0 >= class_num) {
printf("No labels!");
exit(-1);
} else {
printf("Got %d labels\n", class_num);
}
for (int i = 0; i < class_num; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
memcpy(labels[i], json_array_item->valuestring, strlen(json_array_item->valuestring));
printf("%d: %s\n", i, labels[i]);
}
// obj_thresh
json_item = cJSON_GetObjectItem(json_obj, "obj_thresh");
array_size = cJSON_GetArraySize(json_item);
if (class_num != array_size) {
printf("label number and thresh number mismatch! label number : %d, obj thresh number %d", class_num, array_size);
exit(-1);
} else {
printf("Got %d obj_thresh\n", array_size);
}
for (int i = 0; i < array_size; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
obj_thresh[i] = json_array_item->valuedouble;
printf("%d: %f\n", i, obj_thresh[i]);
}
// nms_thresh
json_item = cJSON_GetObjectItem(json_obj, "nms_thresh");
nms_thresh = json_item->valuedouble;
printf("Got nms_thresh: %f\n", nms_thresh);
cJSON_Delete(json_obj);
return;
}
void face_detect()
{
int ret = 0;
int result = 0;
int size = 0;
g_fd = open("/dev/ov2640",O_RDONLY);
if(g_fd < 0)
{
param_parse();
g_fd = open("/dev/ov2640", O_RDONLY);
if (g_fd < 0) {
printf("open ov2640 fail !!");
return;
}
showbuffer = (unsigned char*)malloc(SHOW_RGB_BUF_SIZE);
if(NULL ==showbuffer)
{
_ioctl_set_dvp_reso set_dvp_reso = {sensor_output_size[1], sensor_output_size[0]};
ioctl(g_fd, IOCTRL_CAMERA_SET_DVP_RESO, &set_dvp_reso);
showbuffer = (unsigned char *)malloc(sensor_output_size[0] * sensor_output_size[1] * 2);
if (NULL == showbuffer) {
close(g_fd);
printf("showbuffer apply memory fail !!");
return ;
return;
}
kpurgbbuffer = (unsigned char*)malloc(AI_KPU_RGB_BUF_SIZE);
if(NULL ==kpurgbbuffer)
{
kpurgbbuffer = (unsigned char *)malloc(net_input_size[0] * net_input_size[1] * 3);
if (NULL == kpurgbbuffer) {
close(g_fd);
free(showbuffer);
printf("kpurgbbuffer apply memory fail !!");
return ;
return;
}
model_data = (unsigned char *)malloc(KMODEL_SIZE + 255);
if(NULL ==model_data)
{
model_data = (unsigned char *)malloc(kmodel_size + 255);
if (NULL == model_data) {
free(showbuffer);
free(kpurgbbuffer);
close(g_fd);
printf("model_data apply memory fail !!");
return ;
return;
}
memset(model_data,0,KMODEL_SIZE + 255);
memset(showbuffer,0,SHOW_RGB_BUF_SIZE);
memset(kpurgbbuffer,0,AI_KPU_RGB_BUF_SIZE);
memset(model_data, 0, kmodel_size + 255);
memset(showbuffer, 0, sensor_output_size[0] * sensor_output_size[1] * 2);
memset(kpurgbbuffer, 0, net_input_size[0] * net_input_size[1] * 3);
shoot_para_t.pdata = (unsigned int *)(showbuffer);
shoot_para_t.length = SHOW_RGB_BUF_SIZE;
shoot_para_t.length = (size_t)(sensor_output_size[0] * sensor_output_size[1] * 2);
/*
load memory
load memory
*/
kmodel_fd = open("/kmodel/detect.kmodel",O_RDONLY);
if(kmodel_fd <0)
{
printf("open kmodel fail");
close(g_fd);
free(showbuffer);
free(kpurgbbuffer);
free(model_data);
return;
}
else
{
size = read(kmodel_fd, model_data, KMODEL_SIZE);
if(size != KMODEL_SIZE)
{
printf("read kmodel error size %d\n",size);
kmodel_fd = open(kmodel_path, O_RDONLY);
if (kmodel_fd < 0) {
printf("open kmodel fail");
close(g_fd);
free(showbuffer);
free(kpurgbbuffer);
free(model_data);
return;
} else {
size = read(kmodel_fd, model_data, kmodel_size);
if (size != kmodel_size) {
printf("read kmodel error size %d\n", size);
close(g_fd);
close(kmodel_fd);
free(showbuffer);
free(kpurgbbuffer);
free(model_data);
return;
}
else
{
printf("read kmodel success \n");
}
}
unsigned char *model_data_align = (unsigned char *)(((unsigned int)model_data+255)&(~255));
dvp_set_ai_addr((uint32_t)kpurgbbuffer, (uint32_t)(kpurgbbuffer + 320 * 240), (uint32_t)(kpurgbbuffer + 320 * 240 * 2));
if (kpu_load_kmodel(&face_detect_task, model_data_align) != 0)
{
} else {
printf("read kmodel success \n");
}
}
unsigned char *model_data_align = (unsigned char *)(((unsigned int)model_data + 255) & (~255));
dvp_set_ai_addr((uint32_t)kpurgbbuffer, (uint32_t)(kpurgbbuffer + net_input_size[0] * net_input_size[1]),
(uint32_t)(kpurgbbuffer + net_input_size[0] * net_input_size[1] * 2));
if (kpu_load_kmodel(&face_detect_task, model_data_align) != 0) {
printf("\nmodel init error\n");
close(g_fd);
close(kmodel_fd);
@ -123,131 +250,124 @@ void face_detect()
}
face_detect_rl.anchor_number = ANCHOR_NUM;
face_detect_rl.anchor = anchor;
face_detect_rl.threshold = 0.7;
face_detect_rl.nms_value = 0.3;
result = region_layer_init(&face_detect_rl, 20, 15, 30, KPUIMAGEWIDTH, KPUIMAGEHEIGHT);
printf("region_layer_init result %d \n\r",result);
size_t stack_size = 32*1024;
pthread_attr_t attr; /* 线程属性 */
struct sched_param prio; /* 线程优先级 */
prio.sched_priority = 8; /* 优先级设置为 8 */
pthread_attr_init(&attr); /* 先使用默认值初始化属性 */
pthread_attr_setschedparam(&attr,&prio); /* 修改属性对应的优先级 */
face_detect_rl.threshold = malloc(class_num * sizeof(float));
for (int idx = 0; idx < class_num; idx++) {
face_detect_rl.threshold[idx] = obj_thresh[idx];
}
face_detect_rl.nms_value = nms_thresh;
result = region_layer_init(&face_detect_rl, net_output_shape[0], net_output_shape[1], net_output_shape[2],
net_input_size[1], net_input_size[0]);
printf("region_layer_init result %d \n\r", result);
size_t stack_size = STACK_SIZE;
pthread_attr_t attr; /* 线程属性 */
struct sched_param prio; /* 线程优先级 */
prio.sched_priority = 8; /* 优先级设置为 8 */
pthread_attr_init(&attr); /* 先使用默认值初始化属性 */
pthread_attr_setschedparam(&attr, &prio); /* 修改属性对应的优先级 */
pthread_attr_setstacksize(&attr, stack_size);
/* 创建线程 1, 属性为 attr,入口函数是 thread_entry,入口函数参数是 1 */
result = pthread_create(&facetid,&attr,thread_face_detcet_entry,NULL);
if (0 == result)
{
result = pthread_create(&facetid, &attr, thread_face_detcet_entry, NULL);
if (0 == result) {
printf("thread_face_detcet_entry successfully!\n");
}
else
{
printf("thread_face_detcet_entry failed! error code is %d\n",result);
} else {
printf("thread_face_detcet_entry failed! error code is %d\n", result);
close(g_fd);
}
}
}
#ifdef __RT_THREAD_H__
MSH_CMD_EXPORT(face_detect,face detect task);
MSH_CMD_EXPORT(face_detect, face detect task);
#endif
static void* thread_face_detcet_entry(void *parameter)
{
extern void lcd_draw_picture(uint16_t x1, uint16_t y1, uint16_t width, uint16_t height, uint32_t *ptr);
static void *thread_face_detcet_entry(void *parameter)
{
extern void lcd_draw_picture(uint16_t x1, uint16_t y1, uint16_t width, uint16_t height, uint32_t * ptr);
printf("thread_face_detcet_entry start!\n");
int ret = 0;
//sysctl_enable_irq();
while(1)
{
//memset(showbuffer,0,320*240*2);
// sysctl_enable_irq();
while (1) {
// memset(showbuffer,0,320*240*2);
g_ai_done_flag = 0;
ret = ioctl(g_fd,IOCTRL_CAMERA_START_SHOT,&shoot_para_t);
if(RT_ERROR == ret)
{
ret = ioctl(g_fd, IOCTRL_CAMERA_START_SHOT, &shoot_para_t);
if (RT_ERROR == ret) {
printf("ov2640 can't wait event flag");
rt_free(showbuffer);
close(g_fd);
pthread_exit(NULL);
pthread_exit(NULL);
return NULL;
}
kpu_run_kmodel(&face_detect_task, kpurgbbuffer, DMAC_CHANNEL5, ai_done, NULL);
while(!g_ai_done_flag);
while (!g_ai_done_flag)
;
float *output;
size_t output_size;
kpu_get_output(&face_detect_task, 0, (uint8_t **)&output, &output_size);
face_detect_rl.input = output;
face_detect_rl.input = output;
region_layer_run(&face_detect_rl, &face_detect_info);
/* display result */
#ifdef BSP_USING_LCD
for (int face_cnt = 0; face_cnt < face_detect_info.obj_number; face_cnt++)
{
draw_edge((uint32_t *)showbuffer, &face_detect_info, face_cnt, 0xF800);
/* display result */
#ifdef BSP_USING_LCD
for (int face_cnt = 0; face_cnt < face_detect_info.obj_number; face_cnt++) {
draw_edge((uint32_t *)showbuffer, &face_detect_info, face_cnt, 0xF800, (uint16_t)sensor_output_size[1],
(uint16_t)sensor_output_size[0]);
printf("%d: (%d, %d, %d, %d) cls: %s conf: %f\t", face_cnt, face_detect_info.obj[face_cnt].x1,
face_detect_info.obj[face_cnt].y1, face_detect_info.obj[face_cnt].x2, face_detect_info.obj[face_cnt].y2,
labels[face_detect_info.obj[face_cnt].class_id], face_detect_info.obj[face_cnt].prob);
}
if (0 != face_detect_info.obj_number) printf("\n");
lcd_draw_picture(0, 0, (uint16_t)sensor_output_size[1], (uint16_t)sensor_output_size[0], (unsigned int *)showbuffer);
#endif
usleep(1);
if (1 == if_exit) {
if_exit = 0;
printf("thread_face_detcet_entry exit");
pthread_exit(NULL);
}
lcd_draw_picture(0, 0, 320, 240, (unsigned int*)showbuffer);
#endif
usleep(1);
if(1 == if_exit)
{
if_exit = 0;
printf("thread_face_detcet_entry exit");
pthread_exit(NULL);
}
}
}
void face_detect_delete()
{
if(showbuffer != NULL)
{
if (showbuffer != NULL) {
int ret = 0;
close(g_fd);
close(kmodel_fd);
free(showbuffer);
free(kpurgbbuffer);
free(model_data);
printf("face detect task cancel!!! ret %d ",ret);
printf("face detect task cancel!!! ret %d ", ret);
if_exit = 1;
}
}
#ifdef __RT_THREAD_H__
MSH_CMD_EXPORT(face_detect_delete,face detect task delete);
MSH_CMD_EXPORT(face_detect_delete, face detect task delete);
#endif
void kmodel_load(unsigned char * model_data)
void kmodel_load(unsigned char *model_data)
{
int kmodel_fd = 0;
int size = 0;
kmodel_fd = open("/kmodel/detect.kmodel",O_RDONLY);
model_data = (unsigned char *)malloc(KMODEL_SIZE + 255);
if(NULL ==model_data)
{
kmodel_fd = open(kmodel_path, O_RDONLY);
model_data = (unsigned char *)malloc(kmodel_size + 255);
if (NULL == model_data) {
printf("model_data apply memory fail !!");
return ;
}
memset(model_data,0,KMODEL_SIZE + 255);
if (kmodel_fd>= 0)
{
size = read(kmodel_fd, model_data, KMODEL_SIZE);
if(size != KMODEL_SIZE)
{
printf("read kmodel error size %d\n",size);
}
else
{
printf("read kmodel success");
}
}
else
{
return;
}
memset(model_data, 0, kmodel_size + 255);
if (kmodel_fd >= 0) {
size = read(kmodel_fd, model_data, kmodel_size);
if (size != kmodel_size) {
printf("read kmodel error size %d\n", size);
} else {
printf("read kmodel success");
}
} else {
free(model_data);
printf("open kmodel fail");
}
}
#ifdef __RT_THREAD_H__
MSH_CMD_EXPORT(kmodel_load,kmodel load memory);
MSH_CMD_EXPORT(kmodel_load, kmodel load memory);
#endif

8
APP_Framework/Applications/knowing_app/helmet_detect/Kconfig

@ -0,0 +1,8 @@
config HELMET_DETECT
bool "enable apps/helmet detect"
depends on BOARD_K210_EVB
depends on DRV_USING_OV2640
depends on USING_KPU_POSTPROCESSING
depends on USING_YOLOV2
select LIB_USING_CJSON
default n

167
APP_Framework/Applications/knowing_app/helmet_detect/README.md

@ -0,0 +1,167 @@
# Helmet detection demo
### A helmet and head without helmet object detection task demo. Running MobileNet-yolo on K210-based edge devices.
---
## Training
### Enviroment preparation
Model generated by [aXeleRate](https://forgeplus.trustie.net/projects/yangtuo250/aXeleRate) and converted to kmodel by [nncase](https://github.com/kendryte/nncase/tree/v0.1.0-rc5).
```shell
# master branch for MobileNetv1-yolov2 and unstable branch to test MobileNetv1(v2)-yolov2(v3)
git clone https://git.trustie.net/yangtuo250/aXeleRate.git (-b unstable)
cd aXeleRate
pip install -r requirments.txt && pip install -e .
```
### training config setting
Example [config](https://forgeplus.trustie.net/projects/yangtuo250/aXeleRate/tree/master/configs/detector.json), some hyper-parameters:
- architecture: backbone, MobileNet7_5 for default, MobileNet1_0(α = 1.0) and above cannot run on K210 because of OOM on feature map in master branch. For unstable branch MobileNetV2_1_0 is OK.
- input_size: fixed model input size, single integer for height equals to width, otherwise a list([height, width]).
- anchors: yolov2 anchor(for master) or anchor scaled to 1.0(for unstable), can be generate by [darknet](https://github.com/AlexeyAB/darknet).
- labels: labels of all classes.
- train(valid)_image(annot)_folder: path of images and annoations for training and validation.
- saved_folder: path for trainig result storage(models, checkpoints, logs ...).
Mine config for unstable:
```json
{
"model": {
"type": "Detector",
"architecture": "MobileNetV2_1_0",
"input_size": [
224,
320
],
"anchors": [
[
[
0.1043,
0.1560
],
[
0.0839,
0.3036
],
[
0.1109,
0.3923
],
[
0.1378,
0.5244
],
[
0.2049,
0.6673
]
]
],
"labels": [
"human"
],
"obj_thresh": 0.5,
"iou_thresh": 0.45,
"coord_scale": 1.0,
"class_scale": 0.0,
"object_scale": 5.0,
"no_object_scale": 3.0
},
"weights": {
"full": "",
"backend": ""
},
"train": {
"actual_epoch": 2000,
"train_image_folder": "mydata/human/Images/train",
"train_annot_folder": "mydata/human/Annotations/train",
"train_times": 2,
"valid_image_folder": "mydata/human/Images/val",
"valid_annot_folder": "mydata/human/Annotations/val",
"valid_times": 1,
"valid_metric": "precision",
"batch_size": 32,
"learning_rate": 2e-5,
"saved_folder": "mydata/human/results",
"first_trainable_layer": "",
"augmentation": true,
"is_only_detect": false,
"validation_freq": 5,
"quantize": false,
"class_weights": [1.0]
},
"converter": {
"type": [
"k210"
]
}
}
```
*(For more detailed config usage, please refer to original aXeleRate repo.)*
### data preparation
Please refer to [VOC format](https://towardsdatascience.com/coco-data-format-for-object-detection-a4c5eaf518c5), path as config above.
### train it!
```shell
python -m aXeleRate.train -c PATH_TO_YOUR_CONFIG
```
### model convert
Please refer to [nncase repo](https://github.com/kendryte/nncase/tree/v0.1.0-rc5).
---
## Deployment
### compile and burn
Use `(scons --)menuconfig` in bsp folder *(Ubiquitous/RT_Thread/bsp/k210)*, open:
- More Drivers --> ov2640 driver
- Board Drivers Config --> Enable LCD on SPI0
- Board Drivers Config --> Enable SDCARD (spi1(ss0))
- Board Drivers Config --> Enable DVP(camera)
- RT-Thread Components --> POSIX layer and C standard library --> Enable pthreads APIs
- APP_Framework --> Framework --> support knowing framework --> kpu model postprocessing --> yolov2 region layer
- APP_Framework --> Applications --> knowing app --> enable apps/helmet detect
`scons -j(n)` to compile and burn in by *kflash*.
### json config and kmodel
Copy json config for deployment o SD card */kmodel*. Example config file is *helmet.json* in this directory. Something to be modified:
- net_input_size: same as *input_size* in training config file, but array only.
- net_output_shape: final feature map size, can be found in **nncase** output.
- sensor_output_size: image height and width from camera.
- kmodel_size: kmodel size shown in file system.
- anchors: same as *anchor* in training config file(multi-dimention anchors flatten to 1 dim).
- labels: same as *label* in training config file.
- obj_thresh: array, object threshold of each label.
- nms_thresh: NMS threshold of boxes.
Copy final kmodel to SD card */kmodel* either.
---
## Run
In serial terminal, `helmet_detect` to start a detection thread, `helmet_detect_delete` to stop it. Detection results can be found in output.
---
## TODO
- [ ] Fix LCD real-time result display.
- [ ] Test more object detection backbone and algorithm(like yolox).

9
APP_Framework/Applications/knowing_app/helmet_detect/SConscript

@ -0,0 +1,9 @@
from building import *
cwd = GetCurrentDir()
src = Glob('*.c') + Glob('*.cpp')
CPPPATH = [cwd]
group = DefineGroup('Applications', src, depend = ['HELMET_DETECT'], LOCAL_CPPPATH = CPPPATH)
Return('group')

38
APP_Framework/Applications/knowing_app/helmet_detect/helmet.json

@ -0,0 +1,38 @@
{
"net_input_size": [
256,
256
],
"net_output_shape": [
8,
8,
35
],
"sensor_output_size": [
256,
256
],
"anchors": [
0.1384,
0.276,
0.308,
0.504,
0.5792,
0.8952,
1.072,
1.6184,
2.1128,
3.184
],
"kmodel_path": "/kmodel/helmet.kmodel",
"kmodel_size": 2714044,
"obj_thresh": [
0.7,
0.9
],
"labels": [
"head",
"helmet"
],
"nms_thresh": 0.45
}

BIN
APP_Framework/Applications/knowing_app/helmet_detect/helmet.kmodel

Binary file not shown.

380
APP_Framework/Applications/knowing_app/helmet_detect/helmet_detect.c

@ -0,0 +1,380 @@
#include <transform.h>
#ifdef LIB_USING_CJSON
#include <cJSON.h>
#endif
#include "region_layer.h"
#define ANCHOR_NUM 5
#define STACK_SIZE (128 * 1024)
#define JSON_FILE_PATH "/kmodel/helmet.json"
#define JSON_BUFFER_SIZE (4 * 1024)
// params from json
static float anchor[ANCHOR_NUM * 2] = {};
static int net_output_shape[3] = {};
static int net_input_size[2] = {};
static int sensor_output_size[2] = {};
static char kmodel_path[127] = "";
static int kmodel_size = 0;
static float obj_thresh[20] = {};
static float nms_thresh = 0.0;
static char labels[20][32] = {};
static int class_num = 0;
#define THREAD_PRIORITY_HELMET_D (11)
static pthread_t helmettid = 0;
static void *thread_helmet_detect_entry(void *parameter);
static int g_fd = 0;
static int kmodel_fd = 0;
static int if_exit = 0;
static unsigned char *showbuffer = NULL;
static unsigned char *kpurgbbuffer = NULL;
static _ioctl_shoot_para shoot_para_t = {0};
unsigned char *model_data = NULL; // kpu data load memory
unsigned char *model_data_align = NULL;
kpu_model_context_t helmet_detect_task;
static region_layer_t helmet_detect_rl;
static obj_info_t helmet_detect_info;
volatile uint32_t g_ai_done_flag;
static void ai_done(void *ctx) { g_ai_done_flag = 1; }
static void param_parse()
{
int fin;
char buffer[JSON_BUFFER_SIZE] = "";
// char *buffer;
// if (NULL != (buffer = (char*)malloc(JSON_BUFFER_SIZE * sizeof(char)))) {
// memset(buffer, 0, JSON_BUFFER_SIZE * sizeof(char));
// } else {
// printf("Json buffer malloc failed!");
// exit(-1);
// }
int array_size;
cJSON *json_obj;
cJSON *json_item;
cJSON *json_array_item;
fin = open(JSON_FILE_PATH, O_RDONLY);
if (!fin) {
printf("Error open file %s", JSON_FILE_PATH);
exit(-1);
}
read(fin, buffer, sizeof(buffer));
close(fin);
// read json string
json_obj = cJSON_Parse(buffer);
// free(buffer);
char *json_print_str = cJSON_Print(json_obj);
printf("Json file content: \n%s\n", json_print_str);
cJSON_free(json_print_str);
// get anchors
json_item = cJSON_GetObjectItem(json_obj, "anchors");
array_size = cJSON_GetArraySize(json_item);
if (ANCHOR_NUM * 2 != array_size) {
printf("Expect anchor size: %d, got %d in json file", ANCHOR_NUM * 2, array_size);
exit(-1);
} else {
printf("Got %d anchors from json file\n", ANCHOR_NUM);
}
for (int i = 0; i < ANCHOR_NUM * 2; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
anchor[i] = json_array_item->valuedouble;
printf("%d: %f\n", i, anchor[i]);
}
// net_input_size
json_item = cJSON_GetObjectItem(json_obj, "net_input_size");
array_size = cJSON_GetArraySize(json_item);
if (2 != array_size) {
printf("Expect net_input_size: %d, got %d in json file", 2, array_size);
exit(-1);
} else {
printf("Got %d net_input_size from json file\n", 2);
}
for (int i = 0; i < 2; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
net_input_size[i] = json_array_item->valueint;
printf("%d: %d\n", i, net_input_size[i]);
}
// net_output_shape
json_item = cJSON_GetObjectItem(json_obj, "net_output_shape");
array_size = cJSON_GetArraySize(json_item);
if (3 != array_size) {
printf("Expect net_output_shape: %d, got %d in json file", 3, array_size);
exit(-1);
} else {
printf("Got %d net_output_shape from json file\n", 3);
}
for (int i = 0; i < 3; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
net_output_shape[i] = json_array_item->valueint;
printf("%d: %d\n", i, net_output_shape[i]);
}
// sensor_output_size
json_item = cJSON_GetObjectItem(json_obj, "sensor_output_size");
array_size = cJSON_GetArraySize(json_item);
if (2 != array_size) {
printf("Expect sensor_output_size: %d, got %d in json file", 2, array_size);
exit(-1);
} else {
printf("Got %d sensor_output_size from json file\n", 2);
}
for (int i = 0; i < 2; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
sensor_output_size[i] = json_array_item->valueint;
printf("%d: %d\n", i, sensor_output_size[i]);
}
// kmodel_path
json_item = cJSON_GetObjectItem(json_obj, "kmodel_path");
memcpy(kmodel_path, json_item->valuestring, strlen(json_item->valuestring));
printf("Got kmodel_path: %s\n", kmodel_path);
// kmodel_size
json_item = cJSON_GetObjectItem(json_obj, "kmodel_size");
kmodel_size = json_item->valueint;
printf("Got kmodel_size: %d\n", kmodel_size);
// labels
json_item = cJSON_GetObjectItem(json_obj, "labels");
class_num = cJSON_GetArraySize(json_item);
if (0 >= class_num) {
printf("No labels!");
exit(-1);
} else {
printf("Got %d labels\n", class_num);
}
for (int i = 0; i < class_num; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
memcpy(labels[i], json_array_item->valuestring, strlen(json_array_item->valuestring));
printf("%d: %s\n", i, labels[i]);
}
// obj_thresh
json_item = cJSON_GetObjectItem(json_obj, "obj_thresh");
array_size = cJSON_GetArraySize(json_item);
if (class_num != array_size) {
printf("label number and thresh number mismatch! label number : %d, obj thresh number %d", class_num, array_size);
exit(-1);
} else {
printf("Got %d obj_thresh\n", array_size);
}
for (int i = 0; i < array_size; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
obj_thresh[i] = json_array_item->valuedouble;
printf("%d: %f\n", i, obj_thresh[i]);
}
// nms_thresh
json_item = cJSON_GetObjectItem(json_obj, "nms_thresh");
nms_thresh = json_item->valuedouble;
printf("Got nms_thresh: %f\n", nms_thresh);
cJSON_Delete(json_obj);
return;
}
void helmet_detect()
{
int ret = 0;
int result = 0;
int size = 0;
param_parse();
g_fd = open("/dev/ov2640", O_RDONLY);
if (g_fd < 0) {
printf("open ov2640 fail !!");
return;
}
_ioctl_set_dvp_reso set_dvp_reso = {sensor_output_size[1], sensor_output_size[0]};
ioctl(g_fd, IOCTRL_CAMERA_SET_DVP_RESO, &set_dvp_reso);
showbuffer = (unsigned char *)malloc(sensor_output_size[0] * sensor_output_size[1] * 2);
if (NULL == showbuffer) {
close(g_fd);
printf("showbuffer apply memory fail !!");
return;
}
kpurgbbuffer = (unsigned char *)malloc(net_input_size[0] * net_input_size[1] * 3);
if (NULL == kpurgbbuffer) {
close(g_fd);
free(showbuffer);
printf("kpurgbbuffer apply memory fail !!");
return;
}
model_data = (unsigned char *)malloc(kmodel_size + 255);
if (NULL == model_data) {
free(showbuffer);
free(kpurgbbuffer);
close(g_fd);
printf("model_data apply memory fail !!");
return;
}
memset(model_data, 0, kmodel_size + 255);
memset(showbuffer, 0, sensor_output_size[0] * sensor_output_size[1] * 2);
memset(kpurgbbuffer, 127, net_input_size[0] * net_input_size[1] * 3);
shoot_para_t.pdata = (unsigned int *)(showbuffer);
shoot_para_t.length = (size_t)(sensor_output_size[0] * sensor_output_size[1] * 2);
/*
load memory
*/
kmodel_fd = open(kmodel_path, O_RDONLY);
if (kmodel_fd < 0) {
printf("open kmodel fail");
close(g_fd);
free(showbuffer);
free(kpurgbbuffer);
free(model_data);
return;
} else {
size = read(kmodel_fd, model_data, kmodel_size);
if (size != kmodel_size) {
printf("read kmodel error size %d\n", size);
close(g_fd);
close(kmodel_fd);
free(showbuffer);
free(kpurgbbuffer);
free(model_data);
return;
} else {
printf("read kmodel success \n");
}
}
unsigned char *model_data_align = (unsigned char *)(((unsigned int)model_data + 255) & (~255));
dvp_set_ai_addr((uint32_t)(kpurgbbuffer + net_input_size[1] * (net_input_size[0] - sensor_output_size[0])),
(uint32_t)(kpurgbbuffer + net_input_size[1] * (net_input_size[0] - sensor_output_size[0]) +
net_input_size[0] * net_input_size[1]),
(uint32_t)(kpurgbbuffer + net_input_size[0] * net_input_size[1] * 2 +
net_input_size[1] * (net_input_size[0] - sensor_output_size[0])));
if (kpu_load_kmodel(&helmet_detect_task, model_data_align) != 0) {
printf("\nmodel init error\n");
close(g_fd);
close(kmodel_fd);
free(showbuffer);
free(kpurgbbuffer);
free(model_data);
return;
}
helmet_detect_rl.anchor_number = ANCHOR_NUM;
helmet_detect_rl.anchor = anchor;
helmet_detect_rl.threshold = malloc(class_num * sizeof(float));
for (int idx = 0; idx < class_num; idx++) {
helmet_detect_rl.threshold[idx] = obj_thresh[idx];
}
helmet_detect_rl.nms_value = nms_thresh;
result = region_layer_init(&helmet_detect_rl, net_output_shape[0], net_output_shape[1], net_output_shape[2],
net_input_size[1], net_input_size[0]);
printf("region_layer_init result %d \n\r", result);
size_t stack_size = STACK_SIZE;
pthread_attr_t attr; /* 线程属性 */
struct sched_param prio; /* 线程优先级 */
prio.sched_priority = 8; /* 优先级设置为 8 */
pthread_attr_init(&attr); /* 先使用默认值初始化属性 */
pthread_attr_setschedparam(&attr, &prio); /* 修改属性对应的优先级 */
pthread_attr_setstacksize(&attr, stack_size);
/* 创建线程 1, 属性为 attr,入口函数是 thread_entry,入口函数参数是 1 */
result = pthread_create(&helmettid, &attr, thread_helmet_detect_entry, NULL);
if (0 == result) {
printf("thread_helmet_detect_entry successfully!\n");
} else {
printf("thread_helmet_detect_entry failed! error code is %d\n", result);
close(g_fd);
}
}
#ifdef __RT_THREAD_H__
MSH_CMD_EXPORT(helmet_detect, helmet detect task);
#endif
static void *thread_helmet_detect_entry(void *parameter)
{
extern void lcd_draw_picture(uint16_t x1, uint16_t y1, uint16_t width, uint16_t height, uint32_t * ptr);
printf("thread_helmet_detect_entry start!\n");
int ret = 0;
// sysctl_enable_irq();
while (1) {
// memset(showbuffer,0,320*240*2);
g_ai_done_flag = 0;
ret = ioctl(g_fd, IOCTRL_CAMERA_START_SHOT, &shoot_para_t);
if (RT_ERROR == ret) {
printf("ov2640 can't wait event flag");
rt_free(showbuffer);
close(g_fd);
pthread_exit(NULL);
return NULL;
}
kpu_run_kmodel(&helmet_detect_task, kpurgbbuffer, DMAC_CHANNEL5, ai_done, NULL);
while (!g_ai_done_flag)
;
float *output;
size_t output_size;
kpu_get_output(&helmet_detect_task, 0, (uint8_t **)&output, &output_size);
helmet_detect_rl.input = output;
region_layer_run(&helmet_detect_rl, &helmet_detect_info);
/* display result */
#ifdef BSP_USING_LCD
for (int helmet_cnt = 0; helmet_cnt < helmet_detect_info.obj_number; helmet_cnt++) {
// draw_edge((uint32_t *)showbuffer, &helmet_detect_info, helmet_cnt, 0xF800,
// (uint16_t)sensor_output_size[1],
// (uint16_t)sensor_output_size[0]);
printf("%d: (%d, %d, %d, %d) cls: %s conf: %f\t", helmet_cnt, helmet_detect_info.obj[helmet_cnt].x1,
helmet_detect_info.obj[helmet_cnt].y1, helmet_detect_info.obj[helmet_cnt].x2,
helmet_detect_info.obj[helmet_cnt].y2, labels[helmet_detect_info.obj[helmet_cnt].class_id],
helmet_detect_info.obj[helmet_cnt].prob);
}
if (0 != helmet_detect_info.obj_number) {
printf("\n");
}
lcd_draw_picture(0, 0, (uint16_t)sensor_output_size[1], (uint16_t)sensor_output_size[0], (unsigned int *)showbuffer);
#endif
usleep(1);
if (1 == if_exit) {
if_exit = 0;
printf("thread_helmet_detect_entry exit");
pthread_exit(NULL);
}
}
}
void helmet_detect_delete()
{
if (showbuffer != NULL) {
int ret = 0;
close(g_fd);
close(kmodel_fd);
free(showbuffer);
free(kpurgbbuffer);
free(model_data);
printf("helmet detect task cancel!!! ret %d ", ret);
if_exit = 1;
}
}
#ifdef __RT_THREAD_H__
MSH_CMD_EXPORT(helmet_detect_delete, helmet detect task delete);
#endif
void kmodel_load(unsigned char *model_data)
{
int kmodel_fd = 0;
int size = 0;
kmodel_fd = open(kmodel_path, O_RDONLY);
model_data = (unsigned char *)malloc(kmodel_size + 255);
if (NULL == model_data) {
printf("model_data apply memory fail !!");
return;
}
memset(model_data, 0, kmodel_size + 255);
if (kmodel_fd >= 0) {
size = read(kmodel_fd, model_data, kmodel_size);
if (size != kmodel_size) {
printf("read kmodel error size %d\n", size);
} else {
printf("read kmodel success");
}
} else {
free(model_data);
printf("open kmodel fail");
}
}
#ifdef __RT_THREAD_H__
MSH_CMD_EXPORT(kmodel_load, kmodel load memory);
#endif

8
APP_Framework/Applications/knowing_app/instrusion_detect/Kconfig

@ -0,0 +1,8 @@
config INSTRUSION_DETECT
bool "enable apps/instrusion detect"
depends on BOARD_K210_EVB
depends on DRV_USING_OV2640
depends on USING_KPU_POSTPROCESSING
depends on USING_YOLOV2
select LIB_USING_CJSON
default n

5
APP_Framework/Applications/knowing_app/instrusion_detect/README.md

@ -0,0 +1,5 @@
# Instrusion detect demo
### A human object detection task demo. Running MobileNet-yolo on K210-based edge devices.
***Training, deployment and running, please see helmet_detect***

9
APP_Framework/Applications/knowing_app/instrusion_detect/SConscript

@ -0,0 +1,9 @@
from building import *
cwd = GetCurrentDir()
src = Glob('*.c') + Glob('*.cpp')
CPPPATH = [cwd]
group = DefineGroup('Applications', src, depend = ['INSTRUSION_DETECT'], LOCAL_CPPPATH = CPPPATH)
Return('group')

36
APP_Framework/Applications/knowing_app/instrusion_detect/human.json

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{
"net_input_size": [
224,
320
],
"net_output_shape": [
10,
7,
30
],
"sensor_output_size": [
240,
320
],
"anchors": [
1.043,
1.092,
0.839,
2.1252,
1.109,
2.7461,
1.378,
3.6708,
2.049,
4.6711
],
"kmodel_path": "/kmodel/human.kmodel",
"kmodel_size": 2713236,
"obj_thresh": [
0.55
],
"labels": [
"human"
],
"nms_thresh": 0.35
}

BIN
APP_Framework/Applications/knowing_app/instrusion_detect/human.kmodel

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380
APP_Framework/Applications/knowing_app/instrusion_detect/instrusion_detect.c

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#include <transform.h>
#ifdef LIB_USING_CJSON
#include <cJSON.h>
#endif
#include "region_layer.h"
#define ANCHOR_NUM 5
#define STACK_SIZE (128 * 1024)
#define JSON_FILE_PATH "/kmodel/human.json"
#define JSON_BUFFER_SIZE (4 * 1024)
// params from json
static float anchor[ANCHOR_NUM * 2] = {};
static int net_output_shape[3] = {};
static int net_input_size[2] = {};
static int sensor_output_size[2] = {};
static char kmodel_path[127] = "";
static int kmodel_size = 0;
static float obj_thresh[20] = {};
static float nms_thresh = 0.0;
static char labels[20][32] = {};
static int class_num = 0;
#define THREAD_PRIORITY_HUMAN_D (11)
static pthread_t instrusiontid = 0;
static void *thread_instrusion_detect_entry(void *parameter);
static int g_fd = 0;
static int kmodel_fd = 0;
static int if_exit = 0;
static unsigned char *showbuffer = NULL;
static unsigned char *kpurgbbuffer = NULL;
static _ioctl_shoot_para shoot_para_t = {0};
unsigned char *model_data = NULL; // kpu data load memory
unsigned char *model_data_align = NULL;
kpu_model_context_t instrusion_detect_task;
static region_layer_t instrusion_detect_rl;
static obj_info_t instrusion_detect_info;
volatile uint32_t g_ai_done_flag;
static void ai_done(void *ctx) { g_ai_done_flag = 1; }
static void param_parse()
{
int fin;
char buffer[JSON_BUFFER_SIZE] = "";
// char *buffer;
// if (NULL != (buffer = (char*)malloc(JSON_BUFFER_SIZE * sizeof(char)))) {
// memset(buffer, 0, JSON_BUFFER_SIZE * sizeof(char));
// } else {
// printf("Json buffer malloc failed!");
// exit(-1);
// }
int array_size;
cJSON *json_obj;
cJSON *json_item;
cJSON *json_array_item;
fin = open(JSON_FILE_PATH, O_RDONLY);
if (!fin) {
printf("Error open file %s", JSON_FILE_PATH);
exit(-1);
}
read(fin, buffer, sizeof(buffer));
close(fin);
// read json string
json_obj = cJSON_Parse(buffer);
// free(buffer);
char *json_print_str = cJSON_Print(json_obj);
printf("Json file content: \n%s\n", json_print_str);
cJSON_free(json_print_str);
// get anchors
json_item = cJSON_GetObjectItem(json_obj, "anchors");
array_size = cJSON_GetArraySize(json_item);
if (ANCHOR_NUM * 2 != array_size) {
printf("Expect anchor size: %d, got %d in json file", ANCHOR_NUM * 2, array_size);
exit(-1);
} else {
printf("Got %d anchors from json file\n", ANCHOR_NUM);
}
for (int i = 0; i < ANCHOR_NUM * 2; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
anchor[i] = json_array_item->valuedouble;
printf("%d: %f\n", i, anchor[i]);
}
// net_input_size
json_item = cJSON_GetObjectItem(json_obj, "net_input_size");
array_size = cJSON_GetArraySize(json_item);
if (2 != array_size) {
printf("Expect net_input_size: %d, got %d in json file", 2, array_size);
exit(-1);
} else {
printf("Got %d net_input_size from json file\n", 2);
}
for (int i = 0; i < 2; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
net_input_size[i] = json_array_item->valueint;
printf("%d: %d\n", i, net_input_size[i]);
}
// net_output_shape
json_item = cJSON_GetObjectItem(json_obj, "net_output_shape");
array_size = cJSON_GetArraySize(json_item);
if (3 != array_size) {
printf("Expect net_output_shape: %d, got %d in json file", 3, array_size);
exit(-1);
} else {
printf("Got %d net_output_shape from json file\n", 3);
}
for (int i = 0; i < 3; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
net_output_shape[i] = json_array_item->valueint;
printf("%d: %d\n", i, net_output_shape[i]);
}
// sensor_output_size
json_item = cJSON_GetObjectItem(json_obj, "sensor_output_size");
array_size = cJSON_GetArraySize(json_item);
if (2 != array_size) {
printf("Expect sensor_output_size: %d, got %d in json file", 2, array_size);
exit(-1);
} else {
printf("Got %d sensor_output_size from json file\n", 2);
}
for (int i = 0; i < 2; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
sensor_output_size[i] = json_array_item->valueint;
printf("%d: %d\n", i, sensor_output_size[i]);
}
// kmodel_path
json_item = cJSON_GetObjectItem(json_obj, "kmodel_path");
memcpy(kmodel_path, json_item->valuestring, strlen(json_item->valuestring));
printf("Got kmodel_path: %s\n", kmodel_path);
// kmodel_size
json_item = cJSON_GetObjectItem(json_obj, "kmodel_size");
kmodel_size = json_item->valueint;
printf("Got kmodel_size: %d\n", kmodel_size);
// labels
json_item = cJSON_GetObjectItem(json_obj, "labels");
class_num = cJSON_GetArraySize(json_item);
if (0 >= class_num) {
printf("No labels!");
exit(-1);
} else {
printf("Got %d labels\n", class_num);
}
for (int i = 0; i < class_num; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
memcpy(labels[i], json_array_item->valuestring, strlen(json_array_item->valuestring));
printf("%d: %s\n", i, labels[i]);
}
// obj_thresh
json_item = cJSON_GetObjectItem(json_obj, "obj_thresh");
array_size = cJSON_GetArraySize(json_item);
if (class_num != array_size) {
printf("label number and thresh number mismatch! label number : %d, obj thresh number %d", class_num, array_size);
exit(-1);
} else {
printf("Got %d obj_thresh\n", array_size);
}
for (int i = 0; i < array_size; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
obj_thresh[i] = json_array_item->valuedouble;
printf("%d: %f\n", i, obj_thresh[i]);
}
// nms_thresh
json_item = cJSON_GetObjectItem(json_obj, "nms_thresh");
nms_thresh = json_item->valuedouble;
printf("Got nms_thresh: %f\n", nms_thresh);
cJSON_Delete(json_obj);
return;
}
void instrusion_detect()
{
int ret = 0;
int result = 0;
int size = 0;
param_parse();
g_fd = open("/dev/ov2640", O_RDONLY);
if (g_fd < 0) {
printf("open ov2640 fail !!");
return;
}
_ioctl_set_dvp_reso set_dvp_reso = {sensor_output_size[1], sensor_output_size[0]};
ioctl(g_fd, IOCTRL_CAMERA_SET_DVP_RESO, &set_dvp_reso);
showbuffer = (unsigned char *)malloc(sensor_output_size[0] * sensor_output_size[1] * 2);
if (NULL == showbuffer) {
close(g_fd);
printf("showbuffer apply memory fail !!");
return;
}
kpurgbbuffer = (unsigned char *)malloc(net_input_size[0] * net_input_size[1] * 3);
if (NULL == kpurgbbuffer) {
close(g_fd);
free(showbuffer);
printf("kpurgbbuffer apply memory fail !!");
return;
}
model_data = (unsigned char *)malloc(kmodel_size + 255);
if (NULL == model_data) {
free(showbuffer);
free(kpurgbbuffer);
close(g_fd);
printf("model_data apply memory fail !!");
return;
}
memset(model_data, 0, kmodel_size + 255);
memset(showbuffer, 0, sensor_output_size[0] * sensor_output_size[1] * 2);
memset(kpurgbbuffer, 127, net_input_size[0] * net_input_size[1] * 3);
shoot_para_t.pdata = (unsigned int *)(showbuffer);
shoot_para_t.length = (size_t)(sensor_output_size[0] * sensor_output_size[1] * 2);
/*
load memory
*/
kmodel_fd = open(kmodel_path, O_RDONLY);
if (kmodel_fd < 0) {
printf("open kmodel fail");
close(g_fd);
free(showbuffer);
free(kpurgbbuffer);
free(model_data);
return;
} else {
size = read(kmodel_fd, model_data, kmodel_size);
if (size != kmodel_size) {
printf("read kmodel error size %d\n", size);
close(g_fd);
close(kmodel_fd);
free(showbuffer);
free(kpurgbbuffer);
free(model_data);
return;
} else {
printf("read kmodel success \n");
}
}
unsigned char *model_data_align = (unsigned