autotest
/
xiuos
forked from xuos/xiuos
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

refactor(knowing app): add common k210 yolov2 detection procedure

This commit is contained in:
yangtuo250 2021-12-08 08:38:05 +00:00
parent d368db9e76
commit c07c918150
29 changed files with 148 additions and 1069 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
APP_Framework/Applications/knowing_app/Kconfig
View File

@ -5,9 +5,7 @@ menu "knowing app"
if APPLICATION_KNOWING
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 "$APP_DIR/Applications/knowing_app/k210_detect_entry/Kconfig"
source "$APP_DIR/Applications/knowing_app/iris_ml_demo/Kconfig"
source "$APP_DIR/Applications/knowing_app/k210_fft_test/Kconfig"
source "$APP_DIR/Applications/knowing_app/image_processing/Kconfig"

9
APP_Framework/Applications/knowing_app/face_detect/Kconfig
View File

@ -1,9 +0,0 @@
config FACE_DETECT
bool "enable apps/face detect"
depends on BOARD_K210_EVB
depends on DRV_USING_OV2640
depends on USING_KPU_PROCESSING
depends on USING_YOLOV2
depends on USING_YOLOV2_JSONPARSER
select LIB_USING_CJSON
default n

9
APP_Framework/Applications/knowing_app/face_detect/SConscript
View File

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

8
APP_Framework/Applications/knowing_app/helmet_detect/Kconfig
View File

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

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

@ -1,167 +0,0 @@
# 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
View File

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

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

@ -1,380 +0,0 @@
#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
View File

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

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

@ -1,5 +0,0 @@
# 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***

390
APP_Framework/Applications/knowing_app/instrusion_detect/instrusion_detect.c
View File

@ -1,390 +0,0 @@
#include <transform.h>
#include <unistd.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)
static dmac_channel_number_t dma_ch = DMAC_CHANNEL_MAX;
extern void lcd_show_image(int x, int y, int wide, int height,const rt_uint8_t *buf);
// 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 *)rt_malloc_align(sensor_output_size[0] * sensor_output_size[1] * 2,64);
if (NULL == showbuffer) {
close(g_fd);
printf("showbuffer apply memory fail !!");
return;
}
kpurgbbuffer = (unsigned char *)rt_malloc_align(net_input_size[0] * net_input_size[1] * 3,64);
if (NULL == kpurgbbuffer) {
close(g_fd);
rt_free_align(showbuffer);
printf("kpurgbbuffer apply memory fail !!");
return;
}
model_data = (unsigned char *)malloc(kmodel_size + 255);
if (NULL == model_data) {
rt_free_align(showbuffer);
rt_free_align(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(&instrusion_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;
}
instrusion_detect_rl.anchor_number = ANCHOR_NUM;
instrusion_detect_rl.anchor = anchor;
instrusion_detect_rl.threshold = malloc(class_num * sizeof(float));
for (int idx = 0; idx < class_num; idx++) {
instrusion_detect_rl.threshold[idx] = obj_thresh[idx];
}
instrusion_detect_rl.nms_value = nms_thresh;
result = region_layer_init(&instrusion_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(&instrusiontid, &attr, thread_instrusion_detect_entry, NULL);
if (0 == result) {
printf("thread_instrusion_detect_entry successfully!\n");
} else {
printf("thread_instrusion_detect_entry failed! error code is %d\n", result);
close(g_fd);
}
}
#ifdef __RT_THREAD_H__
MSH_CMD_EXPORT(instrusion_detect, instrusion detect task);
#endif
extern void lcd_draw_picture(uint16_t x1, uint16_t y1, uint16_t width, uint16_t height, uint32_t * ptr);
extern void lcd_show_image(int x, int y, int wide, int height,const rt_uint8_t *buf);
extern void lcd_draw_16_picture(uint16_t x1, uint16_t y1, uint16_t width, uint16_t height, uint32_t * ptr);
static void *thread_instrusion_detect_entry(void *parameter)
{
printf("thread_instrusion_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;
}
if (dmalock_sync_take(&dma_ch, 2000))
{
printf("Fail to take DMA channel");
}
kpu_run_kmodel(&instrusion_detect_task, kpurgbbuffer, DMAC_CHANNEL5, ai_done, NULL);
while (!g_ai_done_flag)
;
dmalock_release(dma_ch);
float *output;
size_t output_size;
kpu_get_output(&instrusion_detect_task, 0, (uint8_t **)&output, &output_size);
instrusion_detect_rl.input = output;
region_layer_run(&instrusion_detect_rl, &instrusion_detect_info);
/* display result */
for (int instrusion_cnt = 0; instrusion_cnt < instrusion_detect_info.obj_number; instrusion_cnt++)
{
draw_edge((uint32_t *)showbuffer, &instrusion_detect_info, instrusion_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", instrusion_cnt, instrusion_detect_info.obj[instrusion_cnt].x1,
instrusion_detect_info.obj[instrusion_cnt].y1, instrusion_detect_info.obj[instrusion_cnt].x2,
instrusion_detect_info.obj[instrusion_cnt].y2, labels[instrusion_detect_info.obj[instrusion_cnt].class_id],
instrusion_detect_info.obj[instrusion_cnt].prob);
}
#ifdef BSP_USING_LCD
//lcd_show_image(0, 0,(uint16_t)sensor_output_size[1], (uint16_t)sensor_output_size[0],(unsigned int *)showbuffer);
lcd_draw_picture(0, 0, (uint16_t)sensor_output_size[1], (uint16_t)sensor_output_size[0], (uint32_t *)showbuffer);
#endif
if (0 != instrusion_detect_info.obj_number) {
printf("\n");
}
usleep(1);
if (1 == if_exit) {
if_exit = 0;
printf("thread_instrusion_detect_entry exit");
pthread_exit(NULL);
}
}
}
void instrusion_detect_delete()
{
if (showbuffer != NULL) {
int ret = 0;
close(g_fd);
close(kmodel_fd);
free(showbuffer);
free(kpurgbbuffer);
free(model_data);
printf("instrusion detect task cancel!!! ret %d ", ret);
if_exit = 1;
}
}
#ifdef __RT_THREAD_H__
MSH_CMD_EXPORT(instrusion_detect_delete, instrusion 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

16
APP_Framework/Applications/knowing_app/k210_detect_entry/Kconfig Normal file
View File

@ -0,0 +1,16 @@
config K210_DETECT_ENTRY
bool "enable apps/k210 detect entry"
depends on BOARD_K210_EVB
depends on DRV_USING_OV2640
depends on USING_KPU_PROCESSING
depends on USING_YOLOV2
depends on USING_YOLOV2_JSONPARSER
depends on USING_K210_DETECT
select LIB_USING_CJSON
default n
config K210_DETECT_CONFIGJSON
string "k210 detect config path"
default "/kmodel/face.json"
---help---
k210 detect task config json path

0
APP_Framework/Applications/knowing_app/face_detect/README.md → APP_Framework/Applications/knowing_app/k210_detect_entry/README.md
View File

2
APP_Framework/Applications/knowing_app/instrusion_detect/SConscript → APP_Framework/Applications/knowing_app/k210_detect_entry/SConscript
View File

@ -4,6 +4,6 @@ cwd = GetCurrentDir()
src = Glob('*.c') + Glob('*.cpp')
CPPPATH = [cwd]
group = DefineGroup('Applications', src, depend = ['INSTRUSION_DETECT'], LOCAL_CPPPATH = CPPPATH)
group = DefineGroup('Applications', src, depend = ['USING_K210_DETECT'], LOCAL_CPPPATH = CPPPATH)
Return('group')

2
APP_Framework/Applications/knowing_app/face_detect/detect.json → APP_Framework/Applications/knowing_app/k210_detect_entry/face.json
View File

@ -24,7 +24,7 @@
6.718375,
9.01025
],
"kmodel_path": "/kmodel/detect.kmodel",
"kmodel_path": "/kmodel/face.kmodel",
"kmodel_size": 388776,
"obj_thresh": [
0.7

0
APP_Framework/Applications/knowing_app/face_detect/detect.kmodel → APP_Framework/Applications/knowing_app/k210_detect_entry/face.kmodel
View File

0
APP_Framework/Applications/knowing_app/helmet_detect/helmet.json → APP_Framework/Applications/knowing_app/k210_detect_entry/helmet.json
View File

0
APP_Framework/Applications/knowing_app/helmet_detect/helmet.kmodel → APP_Framework/Applications/knowing_app/k210_detect_entry/helmet.kmodel
View File

2
APP_Framework/Applications/knowing_app/instrusion_detect/human.json → APP_Framework/Applications/knowing_app/k210_detect_entry/instrusion.json
View File

@ -24,7 +24,7 @@
2.049,
4.6711
],
"kmodel_path": "/kmodel/human.kmodel",
"kmodel_path": "/kmodel/instrusion.kmodel",
"kmodel_size": 2713236,
"obj_thresh": [
0.7

0
APP_Framework/Applications/knowing_app/instrusion_detect/human.kmodel → APP_Framework/Applications/knowing_app/k210_detect_entry/instrusion.kmodel
View File

9
APP_Framework/Applications/knowing_app/k210_detect_entry/k210_detect_entry.c Normal file
View File

@ -0,0 +1,9 @@
#ifdef USING_K210_DETECT
#include "k210_detect.h"
#endif
#include <transform.h>
static void detect_app() { k210_detect(K210_DETECT_CONFIGJSON); }
#ifdef __RT_THREAD_H__
MSH_CMD_EXPORT(detect_app, detect app);
#endif

1
APP_Framework/Framework/knowing/kpu/Kconfig
View File

@ -4,4 +4,5 @@ menuconfig USING_KPU_PROCESSING
if USING_KPU_PROCESSING
source "$APP_DIR/Framework/knowing/kpu/yolov2/Kconfig"
source "$APP_DIR/Framework/knowing/kpu/yolov2_json/Kconfig"
source "$APP_DIR/Framework/knowing/kpu/k210_detect_procedure/Kconfig"
endif

7
APP_Framework/Framework/knowing/kpu/k210_detect_procedure/Kconfig Normal file
View File

@ -0,0 +1,7 @@
menuconfig USING_K210_DETECT
bool "k210 yolov2 detect procedure"
depends on USING_KPU_PROCESSING
default n

10
APP_Framework/Framework/knowing/kpu/k210_detect_procedure/SConscript Normal file
View File

@ -0,0 +1,10 @@
from building import *
import os
cwd = GetCurrentDir()
src = Glob('*.c')
group = DefineGroup('k210_detect_procedure', src, depend = ['USING_YOLOV2', 'USING_YOLOV2_JSONPARSER', 'USING_KPU_PROCESSING'], CPPPATH = [cwd])
Return('group')

83
APP_Framework/Applications/knowing_app/face_detect/face_detect.c → APP_Framework/Framework/knowing/kpu/k210_detect_procedure/k210_detect.c
View File

@ -1,4 +1,4 @@
#include <transform.h>
#include "k210_detect.h"
#include "cJSON.h"
#ifdef USING_YOLOV2_JSONPARSER
@ -6,13 +6,12 @@
#endif
#include "region_layer.h"
#define STACK_SIZE (128 * 1024)
#define JSON_FILE_PATH "/kmodel/detect.json"
static dmac_channel_number_t dma_ch = DMAC_CHANNEL_MAX;
#define THREAD_PRIORITY_FACE_D (11)
static pthread_t facetid = 0;
static void *thread_face_detcet_entry(void *parameter);
#define THREAD_PRIORITY_D (11)
static pthread_t tid = 0;
static void *thread_detect_entry(void *parameter);
static int g_fd = 0;
static int kmodel_fd = 0;
static int if_exit = 0;
@ -23,19 +22,19 @@ 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 face_detect_task;
static region_layer_t face_detect_rl;
static obj_info_t face_detect_info;
kpu_model_context_t detect_task;
static region_layer_t detect_rl;
static obj_info_t detect_info;
volatile uint32_t g_ai_done_flag;
static void ai_done(void *ctx) { g_ai_done_flag = 1; }
void face_detect()
void k210_detect(char *json_file_path)
{
int ret = 0;
int result = 0;
int size = 0;
yolov2_params_t detect_params = param_parse(JSON_FILE_PATH);
yolov2_params_t detect_params = param_parse(json_file_path);
g_fd = open("/dev/ov2640", O_RDONLY);
if (g_fd < 0) {
printf("open ov2640 fail !!");
@ -73,6 +72,7 @@ void face_detect()
/*
load memory
*/
printf("%s\n", detect_params.kmodel_path);
kmodel_fd = open(detect_params.kmodel_path, O_RDONLY);
if (kmodel_fd < 0) {
printf("open kmodel fail");
@ -100,7 +100,7 @@ void face_detect()
dvp_set_ai_addr((uint32_t)kpurgbbuffer,
(uint32_t)(kpurgbbuffer + detect_params.net_input_size[0] * detect_params.net_input_size[1]),
(uint32_t)(kpurgbbuffer + detect_params.net_input_size[0] * detect_params.net_input_size[1] * 2));
if (kpu_load_kmodel(&face_detect_task, model_data_align) != 0) {
if (kpu_load_kmodel(&detect_task, model_data_align) != 0) {
printf("\nmodel init error\n");
close(g_fd);
close(kmodel_fd);
@ -109,15 +109,15 @@ void face_detect()
free(model_data);
return;
}
face_detect_rl.anchor_number = ANCHOR_NUM;
face_detect_rl.anchor = detect_params.anchor;
face_detect_rl.threshold = malloc(detect_params.class_num * sizeof(float));
detect_rl.anchor_number = ANCHOR_NUM;
detect_rl.anchor = detect_params.anchor;
detect_rl.threshold = malloc(detect_params.class_num * sizeof(float));
for (int idx = 0; idx < detect_params.class_num; idx++) {
face_detect_rl.threshold[idx] = detect_params.obj_thresh[idx];
detect_rl.threshold[idx] = detect_params.obj_thresh[idx];
}
face_detect_rl.nms_value = detect_params.nms_thresh;
detect_rl.nms_value = detect_params.nms_thresh;
result =
region_layer_init(&face_detect_rl, detect_params.net_output_shape[0], detect_params.net_output_shape[1],
region_layer_init(&detect_rl, detect_params.net_output_shape[0], detect_params.net_output_shape[1],
detect_params.net_output_shape[2], detect_params.net_input_size[1], detect_params.net_input_size[0]);
printf("region_layer_init result %d \n\r", result);
size_t stack_size = STACK_SIZE;
@ -129,23 +129,23 @@ void face_detect()
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, &detect_params);
result = pthread_create(&tid, &attr, thread_detect_entry, &detect_params);
if (0 == result) {
printf("thread_face_detcet_entry successfully!\n");
printf("thread_detect_entry successfully!\n");
} else {
printf("thread_face_detcet_entry failed! error code is %d\n", result);
printf("thread_detect_entry failed! error code is %d\n", result);
close(g_fd);
}
}
#ifdef __RT_THREAD_H__
MSH_CMD_EXPORT(face_detect, face detect task);
#endif
// #ifdef __RT_THREAD_H__
// MSH_CMD_EXPORT(detect, detect task);
// #endif
static void *thread_face_detcet_entry(void *parameter)
static void *thread_detect_entry(void *parameter)
{
yolov2_params_t detect_params = *(yolov2_params_t *)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");
printf("thread_detect_entry start!\n");
int ret = 0;
// sysctl_enable_irq();
while (1) {
@ -162,24 +162,23 @@ static void *thread_face_detcet_entry(void *parameter)
if (dmalock_sync_take(&dma_ch, 2000)) {
printf("Fail to take DMA channel");
}
kpu_run_kmodel(&face_detect_task, kpurgbbuffer, DMAC_CHANNEL5, ai_done, NULL);
kpu_run_kmodel(&detect_task, kpurgbbuffer, DMAC_CHANNEL5, ai_done, NULL);
while (!g_ai_done_flag)
;
dmalock_release(dma_ch);
float *output;
size_t output_size;
kpu_get_output(&face_detect_task, 0, (uint8_t **)&output, &output_size);
face_detect_rl.input = output;
region_layer_run(&face_detect_rl, &face_detect_info);
kpu_get_output(&detect_task, 0, (uint8_t **)&output, &output_size);
detect_rl.input = output;
region_layer_run(&detect_rl, &detect_info);
/* display result */
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)detect_params.sensor_output_size[1], (uint16_t)detect_params.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, detect_params.labels[face_detect_info.obj[face_cnt].class_id],
// face_detect_info.obj[face_cnt].prob);
for (int cnt = 0; cnt < detect_info.obj_number; cnt++) {
draw_edge((uint32_t *)showbuffer, &detect_info, cnt, 0xF800, (uint16_t)detect_params.sensor_output_size[1],
(uint16_t)detect_params.sensor_output_size[0]);
printf("%d: (%d, %d, %d, %d) cls: %s conf: %f\t", cnt, detect_info.obj[cnt].x1, detect_info.obj[cnt].y1,
detect_info.obj[cnt].x2, detect_info.obj[cnt].y2, detect_params.labels[detect_info.obj[cnt].class_id],
detect_info.obj[cnt].prob);
}
#ifdef BSP_USING_LCD
lcd_draw_picture(0, 0, (uint16_t)detect_params.sensor_output_size[1], (uint16_t)detect_params.sensor_output_size[0],
@ -190,13 +189,13 @@ static void *thread_face_detcet_entry(void *parameter)
usleep(500);
if (1 == if_exit) {
if_exit = 0;
printf("thread_face_detcet_entry exit");
printf("thread_detect_entry exit");
pthread_exit(NULL);
}
}
}
void face_detect_delete()
void detect_delete()
{
if (showbuffer != NULL) {
int ret = 0;
@ -205,13 +204,13 @@ void face_detect_delete()
free(showbuffer);
free(kpurgbbuffer);
free(model_data);
printf("face detect task cancel!!! ret %d ", ret);
printf("detect task cancel!!! ret %d ", ret);
if_exit = 1;
}
}
#ifdef __RT_THREAD_H__
MSH_CMD_EXPORT(face_detect_delete, face detect task delete);
#endif
// #ifdef __RT_THREAD_H__
// MSH_CMD_EXPORT(detect_delete, detect task delete);
// #endif
// void kmodel_load(unsigned char *model_data)
// {

8
APP_Framework/Framework/knowing/kpu/k210_detect_procedure/k210_detect.h Normal file
View File

@ -0,0 +1,8 @@
#ifndef _K210_DETECT_H_
#define _K210_DETECT_H_
#include <transform.h>
void k210_detect(char *json_file_path);
#endif

2
APP_Framework/Framework/knowing/kpu/yolov2_json/SConscript
View File

@ -5,6 +5,6 @@ cwd = GetCurrentDir()
src = Glob('*.c')
group = DefineGroup('yolov2_json', src, depend = ['USING_YOLOV2_JSONPARSER', 'LIB_USING_CJSON'], CPPPATH = [cwd])
group = DefineGroup('yolov2_json', src, depend = ['LIB_USING_CJSON'], CPPPATH = [cwd])
Return('group')

2
APP_Framework/Framework/knowing/kpu/yolov2_json/json_parser.c
View File

@ -93,6 +93,7 @@ yolov2_params_t param_parse(char *json_file_path)
}
// kmodel_path
json_item = cJSON_GetObjectItem(json_obj, "kmodel_path");
memset(params_return.kmodel_path, 0, 127);
memcpy(params_return.kmodel_path, json_item->valuestring, strlen(json_item->valuestring));
printf("Got kmodel_path: %s\n", params_return.kmodel_path);
// kmodel_size
@ -110,6 +111,7 @@ yolov2_params_t param_parse(char *json_file_path)
}
for (int i = 0; i < params_return.class_num; i++) {
json_array_item = cJSON_GetArrayItem(json_item, i);
memset(params_return.labels[i], 0, 127);
memcpy(params_return.labels[i], json_array_item->valuestring, strlen(json_array_item->valuestring));
printf("%d: %s\n", i, params_return.labels[i]);
}

53
Ubiquitous/RT_Thread/aiit_board/k210/.config
View File

@ -12,6 +12,7 @@ CONFIG_BOARD_K210_EVB=y
# RT-Thread Kernel
#
CONFIG_RT_NAME_MAX=8
# CONFIG_RT_USING_BIG_ENDIAN is not set
# CONFIG_RT_USING_ARCH_DATA_TYPE is not set
CONFIG_RT_USING_SMP=y
CONFIG_RT_CPUS_NR=2
@ -26,6 +27,7 @@ CONFIG_RT_USING_HOOK=y
CONFIG_RT_USING_IDLE_HOOK=y
CONFIG_RT_IDLE_HOOK_LIST_SIZE=4
CONFIG_IDLE_THREAD_STACK_SIZE=4096
CONFIG_SYSTEM_THREAD_STACK_SIZE=4096
# CONFIG_RT_USING_TIMER_SOFT is not set
#
@ -33,6 +35,7 @@ CONFIG_IDLE_THREAD_STACK_SIZE=4096
#
# CONFIG_RT_KSERVICE_USING_STDLIB is not set
# CONFIG_RT_KSERVICE_USING_TINY_SIZE is not set
# CONFIG_RT_USING_ASM_MEMCPY is not set
CONFIG_RT_DEBUG=y
CONFIG_RT_DEBUG_COLOR=y
CONFIG_RT_DEBUG_INIT_CONFIG=y
@ -79,6 +82,7 @@ CONFIG_RT_USING_DEVICE=y
CONFIG_RT_USING_CONSOLE=y
CONFIG_RT_CONSOLEBUF_SIZE=128
CONFIG_RT_CONSOLE_DEVICE_NAME="uarths"
# CONFIG_RT_PRINTF_LONGLONG is not set
CONFIG_RT_VER_NUM=0x40004
CONFIG_ARCH_CPU_64BIT=y
# CONFIG_RT_USING_CPU_FFS is not set
@ -100,24 +104,25 @@ CONFIG_RT_MAIN_THREAD_PRIORITY=10
# C++ features
#
CONFIG_RT_USING_CPLUSPLUS=y
# CONFIG_RT_USING_CPLUSPLUS11 is not set
#
# Command shell
#
CONFIG_RT_USING_FINSH=y
CONFIG_RT_USING_MSH=y
CONFIG_FINSH_USING_MSH=y
CONFIG_FINSH_THREAD_NAME="tshell"
CONFIG_FINSH_THREAD_PRIORITY=20
CONFIG_FINSH_THREAD_STACK_SIZE=16384
CONFIG_FINSH_USING_HISTORY=y
CONFIG_FINSH_HISTORY_LINES=5
CONFIG_FINSH_USING_SYMTAB=y
CONFIG_FINSH_CMD_SIZE=80
CONFIG_MSH_USING_BUILT_IN_COMMANDS=y
CONFIG_FINSH_USING_DESCRIPTION=y
# CONFIG_FINSH_ECHO_DISABLE_DEFAULT is not set
CONFIG_FINSH_THREAD_PRIORITY=20
CONFIG_FINSH_THREAD_STACK_SIZE=16384
CONFIG_FINSH_CMD_SIZE=80
# CONFIG_FINSH_USING_AUTH is not set
CONFIG_FINSH_USING_MSH=y
CONFIG_FINSH_USING_MSH_DEFAULT=y
# CONFIG_FINSH_USING_MSH_ONLY is not set
CONFIG_FINSH_ARG_MAX=10
#
@ -151,6 +156,7 @@ CONFIG_RT_DFS_ELM_DRIVES=2
CONFIG_RT_DFS_ELM_MAX_SECTOR_SIZE=4096
# CONFIG_RT_DFS_ELM_USE_ERASE is not set
CONFIG_RT_DFS_ELM_REENTRANT=y
CONFIG_RT_DFS_ELM_MUTEX_TIMEOUT=3000
CONFIG_RT_USING_DFS_DEVFS=y
# CONFIG_RT_USING_DFS_ROMFS is not set
# CONFIG_RT_USING_DFS_RAMFS is not set
@ -165,6 +171,8 @@ CONFIG_RT_USING_SYSTEM_WORKQUEUE=y
CONFIG_RT_SYSTEM_WORKQUEUE_STACKSIZE=2048
CONFIG_RT_SYSTEM_WORKQUEUE_PRIORITY=23
CONFIG_RT_USING_SERIAL=y
CONFIG_RT_USING_SERIAL_V1=y
# CONFIG_RT_USING_SERIAL_V2 is not set
CONFIG_RT_SERIAL_USING_DMA=y
CONFIG_RT_SERIAL_RB_BUFSZ=64
# CONFIG_RT_USING_CAN is not set
@ -246,8 +254,9 @@ CONFIG_RT_USING_POSIX=y
# CONFIG_RT_USING_POSIX_TERMIOS is not set
# CONFIG_RT_USING_POSIX_GETLINE is not set
# CONFIG_RT_USING_POSIX_AIO is not set
CONFIG_RT_LIBC_USING_TIME=y
# CONFIG_RT_USING_MODULE is not set
CONFIG_RT_LIBC_FIXED_TIMEZONE=8
CONFIG_RT_LIBC_DEFAULT_TIMEZONE=8
#
# Network
@ -284,6 +293,7 @@ CONFIG_NETDEV_IPV6=0
CONFIG_RT_USING_LWIP=y
# CONFIG_RT_USING_LWIP141 is not set
CONFIG_RT_USING_LWIP202=y
# CONFIG_RT_USING_LWIP203 is not set
# CONFIG_RT_USING_LWIP212 is not set
# CONFIG_RT_USING_LWIP_IPV6 is not set
CONFIG_RT_LWIP_MEM_ALIGNMENT=8
@ -353,6 +363,7 @@ CONFIG_RT_LWIP_USING_PING=y
# CONFIG_RT_USING_RYM is not set
# CONFIG_RT_USING_ULOG is not set
# CONFIG_RT_USING_UTEST is not set
# CONFIG_RT_USING_VAR_EXPORT is not set
# CONFIG_RT_USING_RT_LINK is not set
#
@ -415,9 +426,6 @@ CONFIG_BSP_DVP_CMOS_PWDN_PIN=44
CONFIG_BSP_DVP_CMOS_XCLK_PIN=46
CONFIG_BSP_DVP_CMOS_PCLK_PIN=47
CONFIG_BSP_DVP_CMOS_HREF_PIN=45
CONFIG_RW007_SPIDEV_NAME="spi11"
CONFIG_RW007_INT_BUSY_PIN=7
CONFIG_RW007_RST_PIN=6
#
# Kendryte SDK Config
@ -427,10 +435,7 @@ CONFIG_PKG_KENDRYTE_SDK_VERNUM=0x0055
#
# More Drivers
#
CONFIG_PKG_USING_RW007=y
CONFIG_RW007_NOT_USE_EXAMPLE_DRIVERS=y
# CONFIG_RW007_USING_STM32_DRIVERS is not set
CONFIG_RW007_SPI_MAX_HZ=20000000
# CONFIG_PKG_USING_RW007 is not set
CONFIG_DRV_USING_OV2640=y
#
@ -446,6 +451,11 @@ CONFIG_DRV_USING_OV2640=y
#
CONFIG_MAIN_KTASK_STACK_SIZE=1024
#
# ota app
#
# CONFIG_APPLICATION_OTA is not set
#
# test app
#
@ -464,10 +474,9 @@ CONFIG_MAIN_KTASK_STACK_SIZE=1024
# knowing app
#
CONFIG_APPLICATION_KNOWING=y
CONFIG_APP_MNIST=y
CONFIG_FACE_DETECT=y
# CONFIG_INSTRUSION_DETECT is not set
# CONFIG_HELMET_DETECT is not set
# CONFIG_APP_MNIST is not set
CONFIG_K210_DETECT_ENTRY=y
CONFIG_K210_DETECT_CONFIGJSON="/kmodel/face.json"
# CONFIG_IRIS_ML_DEMO is not set
# CONFIG_K210_FFT_TEST is not set
# CONFIG_USING_IMAGE_PROCESSING_APP is not set
@ -507,12 +516,14 @@ CONFIG_USING_TENSORFLOWLITEMICRO=y
CONFIG_USING_TENSORFLOWLITEMICRO_NORMAL=y
# CONFIG_USING_TENSORFLOWLITEMICRO_CMSISNN is not set
# CONFIG_USING_TENSORFLOWLITEMICRO_DEMOAPP is not set
CONFIG_USING_KPU_PROCESSING=y
CONFIG_USING_YOLOV2=y
CONFIG_USING_YOLOV2_JSONPARSER=y
# CONFIG_USING_KNOWING_FILTER is not set
# CONFIG_USING_OTA_MODEL is not set
# CONFIG_USING_IMAGE_PROCESSING is not set
# CONFIG_USING_CMSIS_5 is not set
CONFIG_USING_KPU_PROCESSING=y
CONFIG_USING_YOLOV2=y
CONFIG_USING_YOLOV2_JSONPARSER=y
CONFIG_USING_K210_DETECT=y
# CONFIG_SUPPORT_CONTROL_FRAMEWORK is not set
#

31
Ubiquitous/RT_Thread/aiit_board/k210/rtconfig.h
View File

@ -24,6 +24,7 @@
#define RT_USING_IDLE_HOOK
#define RT_IDLE_HOOK_LIST_SIZE 4
#define IDLE_THREAD_STACK_SIZE 4096
#define SYSTEM_THREAD_STACK_SIZE 4096
/* kservice optimization */
@ -75,16 +76,17 @@
/* Command shell */
#define RT_USING_FINSH
#define RT_USING_MSH
#define FINSH_USING_MSH
#define FINSH_THREAD_NAME "tshell"
#define FINSH_THREAD_PRIORITY 20
#define FINSH_THREAD_STACK_SIZE 16384
#define FINSH_USING_HISTORY
#define FINSH_HISTORY_LINES 5
#define FINSH_USING_SYMTAB
#define FINSH_USING_DESCRIPTION
#define FINSH_THREAD_PRIORITY 20
#define FINSH_THREAD_STACK_SIZE 16384
#define FINSH_CMD_SIZE 80
#define FINSH_USING_MSH
#define FINSH_USING_MSH_DEFAULT
#define MSH_USING_BUILT_IN_COMMANDS
#define FINSH_USING_DESCRIPTION
#define FINSH_ARG_MAX 10
/* Device virtual file system */
@ -108,6 +110,7 @@
#define RT_DFS_ELM_DRIVES 2
#define RT_DFS_ELM_MAX_SECTOR_SIZE 4096
#define RT_DFS_ELM_REENTRANT
#define RT_DFS_ELM_MUTEX_TIMEOUT 3000
#define RT_USING_DFS_DEVFS
/* Device Drivers */
@ -118,6 +121,7 @@
#define RT_SYSTEM_WORKQUEUE_STACKSIZE 2048
#define RT_SYSTEM_WORKQUEUE_PRIORITY 23
#define RT_USING_SERIAL
#define RT_USING_SERIAL_V1
#define RT_SERIAL_USING_DMA
#define RT_SERIAL_RB_BUFSZ 64
#define RT_USING_PIN
@ -164,7 +168,8 @@
#define RT_USING_PTHREADS
#define PTHREAD_NUM_MAX 8
#define RT_USING_POSIX
#define RT_LIBC_FIXED_TIMEZONE 8
#define RT_LIBC_USING_TIME
#define RT_LIBC_DEFAULT_TIMEZONE 8
/* Network */
@ -286,9 +291,6 @@
#define BSP_DVP_CMOS_XCLK_PIN 46
#define BSP_DVP_CMOS_PCLK_PIN 47
#define BSP_DVP_CMOS_HREF_PIN 45
#define RW007_SPIDEV_NAME "spi11"
#define RW007_INT_BUSY_PIN 7
#define RW007_RST_PIN 6
/* Kendryte SDK Config */
@ -296,9 +298,6 @@
/* More Drivers */
#define PKG_USING_RW007
#define RW007_NOT_USE_EXAMPLE_DRIVERS
#define RW007_SPI_MAX_HZ 20000000
#define DRV_USING_OV2640
/* APP_Framework */
@ -309,6 +308,9 @@
#define MAIN_KTASK_STACK_SIZE 1024
/* ota app */
/* test app */
@ -320,8 +322,8 @@
/* knowing app */
#define APPLICATION_KNOWING
#define APP_MNIST
#define FACE_DETECT
#define K210_DETECT_ENTRY
#define K210_DETECT_CONFIGJSON "/kmodel/face.json"
/* sensor app */
@ -345,6 +347,7 @@
#define USING_KPU_PROCESSING
#define USING_YOLOV2
#define USING_YOLOV2_JSONPARSER
#define USING_K210_DETECT
/* Security */