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monskatemonskate
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‎examples/usercmodule/BSP/Image-Recognition/esp_cat_detection.cpp‎

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#include <freertos/FreeRTOS.h>
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#include <freertos/task.h>
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#include <freertos/queue.h>
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#include <list>
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extern "C"
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{
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#include "esp_config.h"
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#include "esp_log.h"
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#include "py/obj.h"
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#include "py/runtime.h"
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#include "py/builtin.h"
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#include "py/mphal.h"
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#include "esp_camera.h"
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#include "fb_gfx.h"
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#include "img_converters.h" // 包含图像转换的库
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#include "extmod/modmachine.h"
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}
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#include "who_ai_utils.hpp"
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#include "dl_image.hpp"
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#include "cat_face_detect_mn03.hpp"
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// 定义队列的数据结构
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static struct {
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int num;
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int x;
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int y;
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} cat_result = {0, 0, 0};
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static TaskHandle_t cat_task_handle = NULL;
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static SemaphoreHandle_t cat_mutex = NULL;
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// 猫脸识别任务
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void cat_detection_task(void *pvParameters) {
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CatFaceDetectMN03 detector(0.4F, 0.3F, 10, 0.3F);
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while (true) {
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camera_fb_t *frame = esp_camera_fb_get();
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if (frame != NULL) {
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std::list<dl::detect::result_t> &detect_results = detector.infer((uint16_t *)frame->buf, {(int)frame->height, (int)frame->width, 3});
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cat_result.x = 0;
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cat_result.y = 0;
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cat_result.num = detect_results.size();
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if (!detect_results.empty()) {
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auto prediction = detect_results.begin();
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cat_result.x = ((prediction->box[0] + prediction->box[2]) / 2) - 160;
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cat_result.y = 120 - ((prediction->box[1] + prediction->box[3]) / 2);
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}
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esp_camera_fb_return(frame);
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}
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vTaskDelay(pdMS_TO_TICKS(50)); // 降低CPU占用
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}
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}
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// 初始化函数
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mp_obj_t esp_cat_detection_init(void) {
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if (cat_task_handle == NULL) {
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xTaskCreate(cat_detection_task, "cat_detection_task", 10 * 1024, NULL, 10, &cat_task_handle);
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}
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return mp_const_none;
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}
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// 反初始化函数
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mp_obj_t esp_cat_detection_deinit(void) {
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if (cat_task_handle != NULL) {
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vTaskDelete(cat_task_handle);
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cat_task_handle = NULL;
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}
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return mp_const_none;
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}
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// Python接口：获取最新的人脸检测结果
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mp_obj_t esp_cat_detection(void) {
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// xSemaphoreTake(cat_mutex, portMAX_DELAY);
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mp_obj_t elements[] = {
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mp_obj_new_int(cat_result.num),
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mp_obj_new_int(cat_result.x),
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mp_obj_new_int(cat_result.y),
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};
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return mp_obj_new_list(3, elements);
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}
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‎examples/usercmodule/BSP/Image-Recognition/esp_color_detection.cpp‎

Lines changed: 4 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -116,8 +116,8 @@ static void color_recognition_task(void *arg) {
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for (int j = 0; j < results[i].size(); ++j) {
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int x = results[i][j].center[0];
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int y = results[i][j].center[1];
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color_result.x = x;
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color_result.y = y;
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color_result.x = x - 160;
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color_result.y = 120 - y;
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}
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}
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}
@@ -156,7 +156,8 @@ mp_obj_t esp_color_discern(void) {
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// 返回颜色位置
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mp_obj_t elements[] = {x, y};
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return mp_obj_new_list(2, elements);}
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return mp_obj_new_list(2, elements);
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}
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mp_obj_t esp_color_deinit(void) {
162163
if (color_task_handle != NULL) {

‎examples/usercmodule/BSP/Image-Recognition/esp_color_rgb.cpp‎

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extern "C"
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{
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#include "esp_config.h"
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#include "esp_log.h"
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#include "py/obj.h"
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#include "py/runtime.h"
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#include "py/builtin.h"
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#include "py/mphal.h"
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#include "esp_camera.h"
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#include "extmod/modmachine.h"
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}
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#include <freertos/FreeRTOS.h>
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#include <freertos/task.h>
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#include <freertos/queue.h>
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#include <list>
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#include <stdlib.h>
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#include <string.h>
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#include <stdint.h>
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#include <math.h>
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#include <vector>
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typedef struct {
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int r;
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int g;
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int b;
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} rgb_result_t;
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// 识别区域结构体
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typedef struct {
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int x;
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int y;
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int w;
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int h;
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} region_t;
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static TaskHandle_t color_task_handle = NULL;
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static SemaphoreHandle_t color_mutex = NULL;
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static rgb_result_t color_result = {0, 0, 0};
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static region_t detect_region = {0, 0, 40, 40};
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static void color_recognition_task(void *arg) {
45+
while (1) {
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camera_fb_t *camera_frame = esp_camera_fb_get();
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if (camera_frame == NULL) {
48+
vTaskDelay(pdMS_TO_TICKS(50));
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continue;
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}
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int img_width = camera_frame->width;
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int img_height = camera_frame->height;
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region_t region;
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xSemaphoreTake(color_mutex, portMAX_DELAY);
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region = detect_region;
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xSemaphoreGive(color_mutex);
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int start_x = region.x;
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int start_y = region.y;
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int region_w = region.w;
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int region_h = region.h;
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// 限制区域合法
65+
if (start_x < 0) start_x = 0;
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if (start_y < 0) start_y = 0;
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if (start_x + region_w > img_width) region_w = img_width - start_x;
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if (start_y + region_h > img_height) region_h = img_height - start_y;
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uint16_t *pixels = (uint16_t *)camera_frame->buf;
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uint8_t max_r = 0, max_g = 0, max_b = 0;
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for (int y = start_y; y < start_y + region_h; ++y) {
75+
for (int x = start_x; x < start_x + region_w; ++x) {
76+
int index = y * img_width + x;
77+
uint16_t pixel = pixels[index];
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79+
uint8_t r = ((pixel >> 11) & 0x1F) << 3;
80+
uint8_t g = ((pixel >> 5) & 0x3F) << 2;
81+
uint8_t b = (pixel & 0x1F) << 3;
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if (r > max_r) max_r = r;
84+
if (g > max_g) max_g = g;
85+
if (b > max_b) max_b = b;
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}
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}
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rgb_result_t temp_result = {max_r, max_g, max_b};
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xSemaphoreTake(color_mutex, portMAX_DELAY);
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color_result = temp_result;
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xSemaphoreGive(color_mutex);
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esp_camera_fb_return(camera_frame);
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vTaskDelay(pdMS_TO_TICKS(100));
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}
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}
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mp_obj_t esp_color_rgb_init(void) {
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if (color_mutex == NULL) {
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color_mutex = xSemaphoreCreateMutex();
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}
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if (color_task_handle == NULL) {
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xTaskCreate(color_recognition_task, "color_recognition_task", 6 * 1024, NULL, 2, &color_task_handle);
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}
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return mp_const_none;
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}
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mp_obj_t esp_color_rgb(void) {
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mp_obj_t r, g, b;
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xSemaphoreTake(color_mutex, portMAX_DELAY);
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r = mp_obj_new_int(color_result.r);
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g = mp_obj_new_int(color_result.g);
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b = mp_obj_new_int(color_result.b);
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xSemaphoreGive(color_mutex);
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mp_obj_t rgb_list[] = {r, g, b};
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return mp_obj_new_list(3, rgb_list);
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}
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// 设置区域接口：传入 x, y, w, h
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mp_obj_t esp_color_set_region(mp_obj_t x_obj, mp_obj_t y_obj, mp_obj_t w_obj, mp_obj_t h_obj) {
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int x = mp_obj_get_int(x_obj);
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int y = mp_obj_get_int(y_obj);
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int w = mp_obj_get_int(w_obj);
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int h = mp_obj_get_int(h_obj);
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xSemaphoreTake(color_mutex, portMAX_DELAY);
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detect_region.x = x;
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detect_region.y = y;
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detect_region.w = w;
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detect_region.h = h;
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xSemaphoreGive(color_mutex);
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return mp_const_none;
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}
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mp_obj_t esp_color_rgb_deinit(void) {
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if (color_task_handle != NULL) {
142+
vTaskDelete(color_task_handle);
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color_task_handle = NULL;
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}
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if (color_mutex != NULL) {
146+
vSemaphoreDelete(color_mutex);
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color_mutex = NULL;
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}
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return mp_const_none;
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}

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