camera buffer_handle_t

时间: 2025-06-27 14:12:32 浏览: 18
<think>好的,我现在需要回答用户关于Android中camera和buffer_handle_t的关系或用法的问题,特别是在HAL或图形编程中的使用。首先,我需要回忆一下Android系统中的相机数据流处理机制。 用户提到了buffer_handle_t,这应该是Gralloc分配的缓冲区句柄,用于图形内存管理。在Android HAL层,相机子系统通常会生成图像数据,这些数据需要传输到其他组件进行处理或显示。Gralloc HAL负责分配这些缓冲区,并返回buffer_handle_t来标识它们。 接下来,用户可能想知道相机如何获取和使用这些缓冲区。例如,当相机捕获一帧图像时,它需要从BufferQueue获取一个缓冲区,填充数据后交还给消费者端,比如SurfaceView或SurfaceTexture。这里可能涉及到ANativeWindow,因为生产者(相机)通过ANativeWindow连接到BufferQueue,并通过dequeueBuffer获取可用的buffer_handle_t,填充数据后通过queueBuffer提交。 还需要考虑buffer_handle_t的结构,它可能包含元数据如宽高、格式、步幅等,这些对于正确解析图像数据很重要。另外,usage标志位也很关键,因为它们指定了缓冲区的用途,比如CPU可读、GPU可写等,这会影响内存分配的方式。 用户提供的引用中,引用[4]提到当通过Canvas锁定Surface时,会连接到BufferQueue的生产者端,这可能影响其他生产者如相机或GLES的使用。因此,在同时使用Canvas和相机时需要注意这一点,避免冲突。 另外,引用[3]提到ANativeWindow是C/C++中的Surface等价物,相机可能通过ANativeWindow来操作BufferQueue,获取buffer_handle_t。因此,相机HAL可能使用ANativeWindow的API来管理缓冲区。 总结一下,buffer_handle_t在相机流程中用于传递图像数据,通过Gralloc分配,由生产者(相机)通过BufferQueue获取和提交,消费者端处理这些缓冲区。需要结合HAL接口和图形内存管理来详细说明用法,包括如何分配、传递和处理这些缓冲区,以及相关的注意事项,比如usage标志和并发访问的问题。</think>在Android相机和图形编程中,`buffer_handle_t`是Gralloc内存分配器返回的缓冲区句柄,用于跨进程或跨组件传递图像数据。以下是其关键应用场景及与相机模块的关系解析: --- ### 1. **相机数据流的缓冲区管理** - **BufferQueue机制**: Android相机通过`BufferQueue`实现生产者-消费者模型。相机作为**生产者**,通过`ANativeWindow`接口从`BufferQueue`获取可用缓冲区(通过`dequeueBuffer()`),填充图像数据后通过`queueBuffer()`提交[^3][^4]。 - 示例代码片段: ```cpp // 从Surface获取ANativeWindow ANativeWindow* window = ANativeWindow_fromSurface(env, surface); // 请求缓冲区 ANativeWindow_Buffer buffer; ANativeWindow_lock(window, &buffer, nullptr); // 填充数据到buffer_handle_t对应的内存 // ... ANativeWindow_unlockAndPost(window); ``` - **`buffer_handle_t`的作用**: 每个从`BufferQueue`获取的缓冲区对应一个`buffer_handle_t`,其指向通过Gralloc分配的共享内存,包含图像元数据(如宽高`width/height`、像素格式`format`、步幅`stride`)。 --- ### 2. **Gralloc与HAL的交互** - **内存分配规则**: 相机HAL通过`GrallocModule`分配缓冲区时需指定`usage`标志(如`GRALLOC_USAGE_SW_READ_OFTEN`表示CPU可读),这直接影响内存的物理布局和访问权限[^1]。 - 例如,相机预览可能需要: ```cpp buffer_handle_t buffer; gralloc_module_t->alloc(..., CAMERA_STREAM, &buffer); ``` - **跨进程传递**: `buffer_handle_t`通过Binder序列化(如`GraphicBuffer`对象)传递,消费者(如SurfaceFlinger或应用)通过`GraphicBufferMapper`锁定和解锁缓冲区以访问数据。 --- ### 3. **关键应用场景** - **相机预览与录像**: 相机HAL将捕获的帧写入`buffer_handle_t`,消费者(如`SurfaceTexture`)从`BufferQueue`获取并渲染。时间戳(`timestamp`)由相机HAL设置,确保视频同步[^2]。 - **零拷贝处理**: 使用`buffer_handle_t`可直接将相机输出传递给GPU(如OpenGL ES纹理)或硬件编码器,避免内存复制。例如: ```cpp // 将buffer_handle_t绑定为EGLImage EGLImageKHR image = eglCreateImageKHR(..., buffer_handle_t); glEGLImageTargetTexture2DOES(GL_TEXTURE_2D, image); ``` --- ### 4. **注意事项** - **并发冲突**: 若通过Canvas锁定Surface进行软件渲染,将独占`BufferQueue`的生产者端,导致相机或GLES无法连接。因此需避免混合使用Canvas与硬件渲染。 - **格式兼容性**: 相机输出格式(如`HAL_PIXEL_FORMAT_YCrCb_420_SP`)需与消费者(如编解码器)支持的格式匹配,否则需要格式转换。 ---
阅读全文

相关推荐

#include "camera_pins.h" #include <WiFi.h> #include "esp_camera.h" #include <SD_MMC.h> // SD卡库 #include <shibie_inferencing.h> #include "edge-impulse-sdk/dsp/image/image.hpp" // 摄像头配置 #define PWDN_GPIO_NUM 32 #define RESET_GPIO_NUM -1 #define XCLK_GPIO_NUM 0 #define SIOD_GPIO_NUM 26 #define SIOC_GPIO_NUM 27 #define Y9_GPIO_NUM 35 #define Y8_GPIO_NUM 34 #define Y7_GPIO_NUM 39 #define Y6_GPIO_NUM 36 #define Y5_GPIO_NUM 21 #define Y4_GPIO_NUM 19 #define Y3_GPIO_NUM 18 #define Y2_GPIO_NUM 5 #define VSYNC_GPIO_NUM 25 #define HREF_GPIO_NUM 23 #define PCLK_GPIO_NUM 22 // Edge Impulse模型参数 #define EI_CAMERA_RAW_FRAME_BUFFER_COLS 320 #define EI_CAMERA_RAW_FRAME_BUFFER_ROWS 240 #define EI_CAMERA_FRAME_BYTE_SIZE 3 // WiFi配置 const char* ssid = "88888888"; const char* password = "11111111"; WiFiServer server(80); // 全局变量 static bool is_initialised = false; uint8_t* snapshot_buf = nullptr; // 摄像头初始化函数 bool ei_camera_init(void) { if (is_initialised) return true; camera_config_t config; config.ledc_channel = LEDC_CHANNEL_0; config.ledc_timer = LEDC_TIMER_0; config.pin_d0 = Y2_GPIO_NUM; config.pin_d1 = Y3_GPIO_NUM; config.pin_d2 = Y4_GPIO_NUM; config.pin_d3 = Y5_GPIO_NUM; config.pin_d4 = Y6_GPIO_NUM; config.pin_d5 = Y7_GPIO_NUM; config.pin_d6 = Y8_GPIO_NUM; config.pin_d7 = Y9_GPIO_NUM; config.pin_xclk = XCLK_GPIO_NUM; config.pin_pclk = PCLK_GPIO_NUM; config.pin_vsync = VSYNC_GPIO_NUM; config.pin_href = HREF_GPIO_NUM; config.pin_sscb_sda = SIOD_GPIO_NUM; config.pin_sscb_scl = SIOC_GPIO_NUM; config.pin_pwdn = PWDN_GPIO_NUM; config.pin_reset = RESET_GPIO_NUM; config.xclk_freq_hz = 20000000; config.pixel_format = PIXFORMAT_JPEG; config.frame_size = FRAMESIZE_QVGA; config.jpeg_quality = 12; config.fb_count = 1; esp_err_t err = esp_camera_init(&config); if (err != ESP_OK) { Serial.printf("Camera init failed: 0x%x\n", err); return false; } is_initialised = true; return true; } // 图像捕获函数 bool ei_camera_capture(uint32_t img_width, uint32_t img_height, uint8_t* out_buf) { if (!is_initialised) { Serial.println("Camera not initialized"); return false; } camera_fb_t* fb = esp_camera_fb_get(); if (!fb) { Serial.println("Camera capture failed"); return false; } bool converted = fmt2rgb888(fb->buf, fb->len, PIXFORMAT_JPEG, snapshot_buf); esp_camera_fb_return(fb); if (!converted) { Serial.println("RGB conversion failed"); return false; } if ((img_width != EI_CAMERA_RAW_FRAME_BUFFER_COLS) || (img_height != EI_CAMERA_RAW_FRAME_BUFFER_ROWS)) { ei::image::processing::crop_and_interpolate_rgb888( out_buf, EI_CAMERA_RAW_FRAME_BUFFER_COLS, EI_CAMERA_RAW_FRAME_BUFFER_ROWS, out_buf, img_width, img_height ); } return true; } // Edge Impulse数据获取回调 static int ei_camera_get_data(size_t offset, size_t length, float* out_ptr) { size_t pixel_ix = offset * 3; size_t pixels_left = length; size_t out_ptr_ix = 0; while (pixels_left != 0) { out_ptr[out_ptr_ix] = (snapshot_buf[pixel_ix + 2] << 16) + (snapshot_buf[pixel_ix + 1] << 8) + snapshot_buf[pixel_ix]; out_ptr_ix++; pixel_ix += 3; pixels_left--; } return 0; } // 执行Edge Impulse推理 String run_inference() { // 分配图像缓冲区 snapshot_buf = (uint8_t*)ps_malloc(EI_CAMERA_RAW_FRAME_BUFFER_COLS * EI_CAMERA_RAW_FRAME_BUFFER_ROWS * EI_CAMERA_FRAME_BYTE_SIZE); if (!snapshot_buf) { return "{\"error\":\"Memory allocation failed\"}"; } // 捕获图像 if (!ei_camera_capture(EI_CLASSIFIER_INPUT_WIDTH, EI_CLASSIFIER_INPUT_HEIGHT, snapshot_buf)) { free(snapshot_buf); return "{\"error\":\"Image capture failed\"}"; } // 准备信号 ei::signal_t signal; signal.total_length = EI_CLASSIFIER_INPUT_WIDTH * EI_CLASSIFIER_INPUT_HEIGHT; signal.get_data = &ei_camera_get_data; // 执行推理 ei_impulse_result_t result = {0}; EI_IMPULSE_ERROR err = run_classifier(&signal, &result, false); free(snapshot_buf); if (err != EI_IMPULSE_OK) { return "{\"error\":\"Classification failed: " + String(err) + "\"}"; } // 生成JSON响应 String json = "{\"predictions\":["; for (size_t i = 0; i < EI_CLASSIFIER_LABEL_COUNT; i++) { json += "{\"label\":\"" + String(ei_classifier_inferencing_categories[i]) + "\","; json += "\"value\":" + String(result.classification[i].value, 5) + "}"; if (i < EI_CLASSIFIER_LABEL_COUNT - 1) json += ","; } json += "],\"timing\":{"; json += "\"dsp\":" + String(result.timing.dsp) + ","; json += "\"classification\":" + String(result.timing.classification) + ","; json += "\"anomaly\":" + String(result.timing.anomaly) + "}}"; return json; } // 处理HTTP请求 void handle_client(WiFiClient& client) { String request = client.readStringUntil('\n'); request.trim(); if (request.indexOf("GET /photo") != -1) { camera_fb_t* fb = esp_camera_fb_get(); if (!fb) { client.println("HTTP/1.1 500 Internal Server Error"); client.println("Content-Type: text/plain"); client.println(); client.println("Camera capture failed"); return; } client.println("HTTP/1.1 200 OK"); client.println("Content-Type: image/jpeg"); client.println("Content-Length: " + String(fb->len)); client.println("Access-Control-Allow-Origin: *"); client.println(); client.write(fb->buf, fb->len); esp_camera_fb_return(fb); } else if (request.indexOf("GET /classify") != -1) { String json = run_inference(); client.println("HTTP/1.1 200 OK"); client.println("Content-Type: application/json"); client.println("Access-Control-Allow-Origin: *"); client.println("Connection: close"); client.println(); client.println(json); } else { client.println("HTTP/1.1 200 OK"); client.println("Content-Type: text/html"); client.println(); client.println("<html><body>"); client.println("ESP32-CAM Edge Impulse"); client.println("View Camera"); client.println("Run Classification"); client.println("</body></html>"); } } void setup() { Serial.begin(115200); // 初始化摄像头 if (!ei_camera_init()) { Serial.println("Failed to initialize camera"); while(1) delay(1000); } // 连接WiFi WiFi.begin(ssid, password); Serial.print("Connecting to WiFi"); while (WiFi.status() != WL_CONNECTED) { delay(500); Serial.print("."); } Serial.println("\nConnected! IP address: " + WiFi.localIP().toString()); server.begin(); Serial.println("HTTP server started"); } void loop() { WiFiClient client = server.available(); if (client) { while (client.connected()) { if (client.available()) { handle_client(client); break; } delay(1); } client.stop(); } delay(10); }浏览器上可以看实时图像,串口监视可以看图像识别结果

请解释下这段代码namespace cros { // This class interfaces with the Google3 auto-framing library: // http://google3/chromeos/camera/lib/auto_framing/auto_framing_cros.h class AutoFramingClient : public AutoFramingCrOS::Client { public: struct Options { Size input_size; double frame_rate = 0.0; uint32_t target_aspect_ratio_x = 0; uint32_t target_aspect_ratio_y = 0; }; // Set up the pipeline. bool SetUp(const Options& options); // Process one frame. |buffer| is only used during this function call. bool ProcessFrame(int64_t timestamp, buffer_handle_t buffer); // Return the stored ROI if a new detection is available, or nullopt if not. // After this call the stored ROI is cleared, waiting for another new // detection to fill it. std::optional<Rect<uint32_t>> TakeNewRegionOfInterest(); // Gets the crop window calculated by the full auto-framing pipeline. Rect<uint32_t> GetCropWindow(); // Tear down the pipeline and clear states. void TearDown(); // Implementations of AutoFramingCrOS::Client. void OnFrameProcessed(int64_t timestamp) override; void OnNewRegionOfInterest( int64_t timestamp, int x_min, int y_min, int x_max, int y_max) override; void OnNewCropWindow( int64_t timestamp, int x_min, int y_min, int x_max, int y_max) override; void OnNewAnnotatedFrame(int64_t timestamp, const uint8_t* data, int stride) override; private: base::Lock lock_; std::unique_ptr<AutoFramingCrOS> auto_framing_ GUARDED_BY(lock_); std::unique_ptr<CameraBufferPool> buffer_pool_ GUARDED_BY(lock_); std::map<int64_t, CameraBufferPool::Buffer> inflight_buffers_ GUARDED_BY(lock_); std::optional<Rect<uint32_t>> region_of_interest_ GUARDED_BY(lock_); Rect<uint32_t> crop_window_ GUARDED_BY(lock_); }; } // namespace

#include <WiFi.h> #include "esp_camera.h" #include <shibie_inferencing.h> #include "edge-impulse-sdk/dsp/image/image.hpp" #include "freertos/semphr.h" // 互斥锁头文件 #include "esp_task_wdt.h" #include "freertos/task.h" #include "esp_http_server.h" // 摄像头引脚配置(根据实际硬件调整) // 摄像头引脚配置 (ESP32-CAM标准配置) #define PWDN_GPIO_NUM 32 #define RESET_GPIO_NUM -1 #define XCLK_GPIO_NUM 0 #define SIOD_GPIO_NUM 26 #define SIOC_GPIO_NUM 27 #define Y9_GPIO_NUM 35 #define Y8_GPIO_NUM 34 #define Y7_GPIO_NUM 39 #define Y6_GPIO_NUM 36 #define Y5_GPIO_NUM 21 #define Y4_GPIO_NUM 19 #define Y3_GPIO_NUM 18 #define Y2_GPIO_NUM 5 #define VSYNC_GPIO_NUM 25 #define HREF_GPIO_NUM 23 #define PCLK_GPIO_NUM 22 // Edge Impulse配置 #define EI_CAMERA_RAW_FRAME_BUFFER_COLS 320 #define EI_CAMERA_RAW_FRAME_BUFFER_ROWS 240 #define EI_CAMERA_FRAME_BYTE_SIZE 3 // WiFi配置 const char* ssid = "your_SSID"; const char* password = "your_PASSWORD"; httpd_handle_t server = NULL; // HTTP服务器句柄 SemaphoreHandle_t xMutex; // 摄像头访问互斥锁 // 摄像头配置优化 camera_config_t camera_config = { .pin_pwdn = PWDN_GPIO_NUM, .pin_reset = RESET_GPIO_NUM, .pin_xclk = XCLK_GPIO_NUM, .pin_sscb_sda = SIOD_GPIO_NUM, .pin_sscb_scl = SIOC_GPIO_NUM, .pin_d7 = Y9_GPIO_NUM, .pin_d6 = Y8_GPIO_NUM, .pin_d5 = Y7_GPIO_NUM, .pin_d4 = Y6_GPIO_NUM, .pin_d3 = Y5_GPIO_NUM, .pin_d2 = Y4_GPIO_NUM, .pin_d1 = Y3_GPIO_NUM, .pin_d0 = Y2_GPIO_NUM, .pin_vsync = VSYNC_GPIO_NUM, .pin_href = HREF_GPIO_NUM, .pin_pclk = PCLK_GPIO_NUM, .xclk_freq_hz = 10000000, // 10MHz降低功耗 .pixel_format = PIXFORMAT_JPEG, .frame_size = FRAMESIZE_QVGA, // 320x240 .jpeg_quality = 12, // 0-63 (越低质量越高) .fb_count = 1, // 单缓冲 .fb_location = CAMERA_FB_IN_PSRAM, .grab_mode = CAMERA_GRAB_LATEST // 获取最新帧 }; // 函数声明 static bool ei_camera_capture(uint32_t w, uint32_t h, uint8_t *out_buf); static int ei_camera_get_data(size_t offset, size_t length, float *out_ptr); static esp_err_t inference_handler(httpd_req_t *req); bool init_camera(); void start_webserver(); // 摄像头捕获函数 (带互斥锁保护) static bool ei_camera_capture(uint32_t w, uint32_t h, uint8_t *out_buf) { camera_fb_t *fb = NULL; bool result = false; // 获取互斥锁 (带100ms超时) if (xSemaphoreTake(xMutex, pdMS_TO_TICKS(100)) == pdTRUE) { fb = esp_camera_fb_get(); xSemaphoreGive(xMutex); if (!fb || fb->format != PIXFORMAT_JPEG) { Serial.println("Camera capture failed"); if(fb) esp_camera_fb_return(fb); return false; } // JPEG转RGB888 if(fmt2rgb888(fb->buf, fb->len, PIXFORMAT_JPEG, out_buf)) { result = true; } // 释放帧缓冲 if (xSemaphoreTake(xMutex, pdMS_TO_TICKS(100)) == pdTRUE) { esp_camera_fb_return(fb); xSemaphoreGive(xMutex); } } else { Serial.println("Camera mutex timeout"); } return result; } // Edge Impulse数据获取回调 static int ei_camera_get_data(size_t offset, size_t length, float *out_ptr) { // 使用PSRAM分配对齐内存 (16字节对齐提升性能) uint8_t *rgb888_buf = (uint8_t*)heap_caps_aligned_alloc( 16, EI_CAMERA_RAW_FRAME_BUFFER_COLS * EI_CAMERA_RAW_FRAME_BUFFER_ROWS * EI_CAMERA_FRAME_BYTE_SIZE, MALLOC_CAP_SPIRAM | MALLOC_CAP_8BIT ); if (!rgb888_buf) { Serial.println("Failed to allocate RGB buffer"); return -1; } // 捕获图像 if (!ei_camera_capture(EI_CAMERA_RAW_FRAME_BUFFER_COLS, EI_CAMERA_RAW_FRAME_BUFFER_ROWS, rgb888_buf)) { heap_caps_free(rgb888_buf); return -1; } // 提取RGB像素值 (转换为模型需要的格式) size_t pixel_ix = offset * 3; size_t out_ptr_ix = 0; while (length--) { out_ptr[out_ptr_ix++] = (rgb888_buf[pixel_ix] << 16) + (rgb888_buf[pixel_ix + 1] << 8) + rgb888_buf[pixel_ix + 2]; pixel_ix += 3; } heap_caps_free(rgb888_buf); // 关键:释放内存防止泄漏 return 0; } // 初始化摄像头 bool init_camera() { esp_err_t err = esp_camera_init(&camera_config); if (err != ESP_OK) { Serial.printf("Camera init failed: 0x%x\n", err); return false; } sensor_t *s = esp_camera_sensor_get(); s->set_vflip(s, 1); // 垂直翻转图像 return true; } // HTTP推理请求处理 static esp_err_t inference_handler(httpd_req_t *req) { ei_impulse_result_t result = {0}; char json_response[512] = {0}; // 创建信号结构体 ei::signal_t signal; signal.total_length = EI_CLASSIFIER_INPUT_WIDTH * EI_CLASSIFIER_INPUT_HEIGHT; signal.get_data = &ei_camera_get_data; // 执行推理 EI_IMPULSE_ERROR err = run_classifier(&signal, &result, false); if (err != EI_IMPULSE_OK) { const char *err_msg = "Inference failed"; snprintf(json_response, sizeof(json_response), "{\"error\":\"%s\", \"code\":%d}", err_msg, err); } else { // 构建JSON响应 snprintf(json_response, sizeof(json_response), "{\"predictions\":[" "{\"label\":\"%s\",\"value\":%.3f}," "{\"label\":\"%s\",\"value\":%.3f}," "{\"label\":\"%s\",\"value\":%.3f}]}", result.classification[0].label, result.classification[0].value, result.classification[1].label, result.classification[1].value, result.classification[2].label, result.classification[2].value); } httpd_resp_set_type(req, "application/json"); httpd_resp_send(req, json_response, strlen(json_response)); return ESP_OK; } // 启动HTTP服务器 void start_webserver() { httpd_config_t config = HTTPD_DEFAULT_CONFIG(); config.server_port = 80; config.ctrl_port = 32767; // 避免端口冲突 config.max_open_sockets = 3; // 限制连接数节省内存 // 注册推理端点 httpd_uri_t inference_uri = { .uri = "/inference", .method = HTTP_GET, .handler = inference_handler, .user_ctx = NULL }; // 启动服务器 if (httpd_start(&server, &config) == ESP_OK) { httpd_register_uri_handler(server, &inference_uri); Serial.println("HTTP server started on port 80"); } else { Serial.println("HTTP server start failed"); } } // 内存监控任务 void memory_monitor_task(void *param) { while(1) { Serial.printf("PSRAM: %dKB Free | Min Heap: %dKB\n", heap_caps_get_free_size(MALLOC_CAP_SPIRAM)/1024, esp_get_minimum_free_heap_size()/1024); vTaskDelay(pdMS_TO_TICKS(5000)); } } void setup() { Serial.begin(115200); delay(1000); // 创建互斥锁 xMutex = xSemaphoreCreateMutex(); if (xMutex == NULL) { Serial.println("Failed to create mutex"); while(1); } // 初始化PSRAM if (!psramInit()) { Serial.println("PSRAM init failed!"); while(1); } else { heap_caps_malloc_extmem_enable(128); // 128字节最小分配单元 Serial.println("PSRAM initialized"); } // 初始化摄像头 if (!init_camera()) { Serial.println("Camera init failed"); while(1); } // 连接WiFi WiFi.begin(ssid, password); WiFi.setSleep(false); // 禁用WiFi睡眠 Serial.print("Connecting to WiFi"); int attempts = 0; while (WiFi.status() != WL_CONNECTED && attempts < 20) { delay(500); Serial.print("."); attempts++; } if (WiFi.status() == WL_CONNECTED) { Serial.println("\nWiFi connected. IP: " + WiFi.localIP().toString()); } else { Serial.println("\nWiFi connection failed"); while(1); } // 启动HTTP服务器 start_webserver(); // 创建内存监控任务 xTaskCreatePinnedToCore( memory_monitor_task, "MemoryMonitor", 4096, NULL, 1, NULL, APP_CPU_NUM ); // 验证模型分辨率 #if EI_CLASSIFIER_INPUT_WIDTH != 320 || EI_CLASSIFIER_INPUT_HEIGHT != 240 #error "模型分辨率必须为320x240!" #endif } void loop() { // 主循环保持空闲 delay(1000); } #if !defined(EI_CLASSIFIER_SENSOR) || EI_CLASSIFIER_SENSOR != EI_CLASSIFIER_SENSOR_CAMERA #error "Invalid model for current sensor" #endif采用方法二修改给我完整代码

#include <assert.h> #include <fcntl.h> #include <getopt.h> #include <opencv2/core/hal/interface.h> #include <opencv2/imgproc.hpp> #include <opencv2/imgproc/imgproc_c.h> #include #include <signal.h> #include <stdbool.h> #include <stdio.h> #include <stdlib.h> #include <time.h> #include <unistd.h> // #include "common/sample_common.h" #include "rkmedia_api.h" #include "rockx.h" #include <opencv2/core.hpp> // #include <opencv2/imgoroc.hpp> #include <opencv2/highgui.hpp> #include <opencv2/opencv.hpp> #define CAMERA_PATH "rkispp_scale0" #define CAMERA_ID 0 #define CAMERA_CHN 0 #define VENC_CHN 0 #define WIDTH 1920 #define HEIGHT 1080 using namespace cv; void nv12ToBgr(uint8_t * nv12_buf, int width, int height, uint8_t * bgr_buf) { Mat nv12_mat(height + height/2, width, CV_8UC1, nv12_buf); Mat bgr_mat(height, width, CV_8UC3, bgr_buf); cvtColor(nv12_mat,bgr_mat,COLOR_YUV2BGR_NV12); } int main(int argc, char **argv) { int ret; VI_CHN_ATTR_S vi_chn_attr; vi_chn_attr.pcVideoNode = CAMERA_PATH; // Path vi_chn_attr.u32Width = 1920; // Width vi_chn_attr.u32Height = 1080; // Height vi_chn_attr.enPixFmt = IMAGE_TYPE_NV12; // ImageType vi_chn_attr.enBufType = VI_CHN_BUF_TYPE_MMAP; // BufType vi_chn_attr.u32BufCnt = 3; // Cnt vi_chn_attr.enWorkMode = VI_WORK_MODE_NORMAL; // Mode ret = RK_MPI_VI_SetChnAttr(CAMERA_ID, CAMERA_CHN, &vi_chn_attr); if (ret) { printf("Vi Set Attr Failed.....\n"); return 0; } else { printf("Vi Set Attr Success.....\n"); } ret = RK_MPI_VI_EnableChn(CAMERA_ID, CAMERA_CHN); if (ret) { printf("Vi Enable Attr Failed.....\n"); return 0; } else { printf("Vi Enable Attr Success.....\n"); } ret = RK_MPI_VI_StartStream(CAMERA_ID, CAMERA_CHN); if(ret) { printf("Start Vi Failed.....\n"); } else { printf("Start Vi Success.....\n"); } rockx_config_t * rockx_face_det_config = rockx_create_config(); rockx_add_config(rockx_face_det_config,ROCKX_CONFIG_DATA_PATH, "/userdata/rockx_data/"); rockx_handle_t face_detect_handle; rockx_ret_t face_ret; rockx_module_t face_det_module = ROCKX_MODULE_FACE_DETECTION_V2; printf("rock_reate 1 \n"); face_ret = rockx_create(&face_detect_handle, face_det_module, rockx_face_det_config, 0); if (face_ret != ROCKX_RET_SUCCESS) { printf("rockx_create failed....\n"); } else { printf("rockx_create success....\n"); } rockx_image_t rv1126_image_frame={0}; rv1126_image_frame.width =1920; rv1126_image_frame.height = 1080; rv1126_image_frame.pixel_format = ROCKX_PIXEL_FORMAT_YUV420SP_NV12; MEDIA_BUFFER mb; uint8_t *bgr = new uint8_t[WIDTH * HEIGHT *3]; char save_pic_name[50]; while (1) { mb = RK_MPI_SYS_GetMediaBuffer(RK_ID_VI, CAMERA_CHN, -1); if(!mb) { printf("RK_MPI_SYS_GetMediaBuffer break....\n"); break; } void *data =RK_MPI_MB_GetPtr(mb); uint8_t *data_uint8=(uint8_t *)data; rv1126_image_frame.data = data_uint8; rv1126_image_frame.size = RK_MPI_MB_GetSize(mb); rockx_object_array_t face_detect_array={0}; printf(" detect \n"); rockx_face_detect(face_detect_handle, &rv1126_image_frame,&face_detect_array,NULL); printf(" detect 2 \n"); if(face_ret != ROCKX_RET_SUCCESS) { printf("rockx_face_detect failed...\n"); } else { //printf("rockx_face_detect Success...\n"); } if(face_detect_array.count > 0) { printf("Snap face Success...\n"); Mat original_nv12_mat = Mat(HEIGHT,WIDTH,CV_8UC1,rv1126_image_frame.data); nv12ToBgr(original_nv12_mat.data,WIDTH,HEIGHT,bgr); Mat output_bgr_mat = Mat(HEIGHT,WIDTH,CV_8UC3,bgr); srand(time(NULL)); sprintf(save_pic_name,"face_%d.jpg",rand()); imwrite(save_pic_name,output_bgr_mat); } RK_MPI_MB_ReleaseBuffer(mb); } return 0; }这个代码在 rockx_face_detect(face_detect_handle, &rv1126_image_frame,&face_detect_array,NULL);出现段错误,怎么回事,是哪个参数的配置错了

void CameraDeviceSession::updateBufferCaches(const hidl_vec<BufferCache>& cachesToRemove) { 1. lock_acquire: 调用 Autolock 将获取锁 this->mInflightLock.mMutex。[显示详情] 1107 Mutex::Autolock _l(mInflightLock); 2. 对 cachesToRemove 的另一元素迭代。 5. 对 cachesToRemove 的另一元素迭代。 1108 for (auto& cache : cachesToRemove) { 1109 auto cbsIt = mCirculatingBuffers.find(cache.streamId); 3. 条件 cbsIt == std::__1::map<int, std::__1::unordered_map<unsigned long long, native_handle const *, std::__1::hash<unsigned long long>, std::__1::equal_to<unsigned long long>, std::__1::allocator<std::__1::pair<unsigned long long const, native_handle const *> > >, std::__1::less<int>, std::__1::allocator<std::__1::pair<int const, std::__1::unordered_map<unsigned long long, native_handle const *, std::__1::hash<unsigned long long>, std::__1::equal_to<unsigned long long>, std::__1::allocator<std::__1::pair<unsigned long long const, native_handle const *> > > > > >::iterator const(this->mCirculatingBuffers.end()),使用了 true 分支。 6. 条件 cbsIt == std::__1::map<int, std::__1::unordered_map<unsigned long long, native_handle const *, std::__1::hash<unsigned long long>, std::__1::equal_to<unsigned long long>, std::__1::allocator<std::__1::pair<unsigned long long const, native_handle const *> > >, std::__1::less<int>, std::__1::allocator<std::__1::pair<int const, std::__1::unordered_map<unsigned long long, native_handle const *, std::__1::hash<unsigned long long>, std::__1::equal_to<unsigned long long>, std::__1::allocator<std::__1::pair<unsigned long long const, native_handle const *> > > > > >::iterator const(this->mCirculatingBuffers.end()),使用了 false 分支。 1110 if (cbsIt == mCirculatingBuffers.end()) { 1111 // The stream could have been removed 4. 继续循环 1112 continue; 1113 } 1114 CirculatingBuffers& cbs = cbsIt->second; 1115 auto it = cbs.find(cache.bufferId); 7. 条件 it != std::__1::unordered_map<unsigned long long, native_handle const *, std::__1::hash<unsigned long long>, std::__1::equal_to<unsigned long long>, std::__1::allocator<std::__1::pair<unsigned long long const, native_handle const *> > >::iterator const(cbs->end()),使用了 true 分支。 1116 if (it != cbs.end()) { CID 171518: (#1 of 1): 持有锁时等待 (SLEEP) 8. sleep: 对 freeBuffer 的调用可能在持有锁 this->mInflightLock.mMutex 的情况下睡眠。[显示详情] 1117 sHandleImporter.freeBuffer(it->second); 1118 cbs.erase(it); 1119 } else { 1120 ALOGE("%s: stream %d buffer %" PRIu64 " is not cached", 1121 __FUNCTION__, cache.streamId, cache.bufferId); 1122 } 1123 } 1124

Status CameraDeviceSession::processOneCaptureRequest_3_4(const V3_4::CaptureRequest& request) { Status status = initStatus(); 1. 条件 status != OK,使用了 false 分支。 if (status != Status::OK) { ALOGE("%s: camera init failed or disconnected", __FUNCTION__); return status; } // If callback is 3.2, make sure there are no physical settings. 2. 条件 !this->mHasCallback_3_4,使用了 true 分支。 if (!mHasCallback_3_4) { 3. 条件 request.physicalCameraSettings.size() > 0,使用了 false 分支。 if (request.physicalCameraSettings.size() > 0) { ALOGE("%s: trying to call processCaptureRequest_3_4 with physical camera id " "and V3.2 callback", __FUNCTION__); return Status::INTERNAL_ERROR; } } camera3_capture_request_t halRequest; halRequest.frame_number = request.v3_2.frameNumber; bool converted = true; V3_2::CameraMetadata settingsFmq; // settings from FMQ 4. 条件 request.v3_2.fmqSettingsSize > 0,使用了 true 分支。 if (request.v3_2.fmqSettingsSize > 0) { // non-blocking read; client must write metadata before calling // processOneCaptureRequest settingsFmq.resize(request.v3_2.fmqSettingsSize); bool read = mRequestMetadataQueue->read(settingsFmq.data(), request.v3_2.fmqSettingsSize); 5. 条件 read,使用了 true 分支。 if (read) { converted = V3_2::implementation::convertFromHidl(settingsFmq, &halRequest.settings); 6. 导致 if 语句结束 } else { ALOGE("%s: capture request settings metadata couldn't be read from fmq!", __FUNCTION__); converted = false; } 7. 导致 if 语句结束 } else { converted = V3_2::implementation::convertFromHidl(request.v3_2.settings, &halRequest.settings); } 8. 条件 !converted,使用了 false 分支。 if (!converted) { ALOGE("%s: capture request settings metadata is corrupt!", __FUNCTION__); return Status::ILLEGAL_ARGUMENT; } CID 144764: (#1 of 1): 数据竞态条件 (MISSING_LOCK) 9. missing_lock: 在未持有锁 android::Mutex.mMutex 的情况下访问 this->mFirstRequest。在其他地方,android::hardware::camera::device::V3_2::implementation::CameraDeviceSession.mFirstRequest 在持有 Mutex.mMutex 的情况下被写入 5/5 次。 if (mFirstRequest && halRequest.settings == nullptr) { ALOGE("%s: capture request settings must not be null for first request!", __FUNCTION__); return Status::ILLEGAL_ARGUMENT; } hidl_vec<buffer_handle_t*> allBufPtrs; hidl_vec<int> allFences; bool hasInputBuf = (request.v3_2.inputBuffer.streamId != -1 && request.v3_2.inputBuffer.bufferId != 0); size_t numOutputBufs = request.v3_2.outputBuffers.size(); size_t numBufs = numOutputBufs + (hasInputBuf ? 1 : 0); if (numOutputBufs == 0) { ALOGE("%s: capture request must have at least one output buffer!", __FUNCTION__); return Status::ILLEGAL_ARGUMENT; } status = importRequest(request.v3_2, allBufPtrs, allFences); if (status != Status::OK) { return status; }

#include "camera_pins.h" #include <WiFi.h> #include "esp_camera.h" #include <Wire.h> #include <Adafruit_GFX.h> #include <Adafruit_SSD1306.h> // Edge Impulse模型库(需手动添加到项目目录) #include "shibie_inferencing.h" #include "edge-impulse-sdk/dsp/image/image.hpp" #include "esp_task_wdt.h" #include "freertos/semphr.h" #include <SD_MMC.h> // SD卡库(使用SPI或SDMMC接口) #include <SPIFFS.h> #include <SD.h> // SPI接口SD卡库(新增) #include <Time.h> // 时间函数库(新增) #include "esp_task_wdt.h" #include "freertos/semphr.h" // 功能开关 #define ENABLE_INFERENCE 1 #define ENABLE_HTTP_SERVER 1 #define ENABLE_OLED_DISPLAY 1 #define ENABLE_SD_CARD 1 // 启用SD卡功能 #define SUPPORT_OBJECT_DETECTION 0 // 摄像头配置 #define CAMERA_MODEL_AI_THINKER #define XCLK_FREQ_HZ 2000000 // 降低时钟频率 #define FRAME_SIZE FRAMESIZE_QVGA // 320x240分辨率 #define JPEG_QUALITY 12 #define MAX_CAPTURE_RETRIES 3 // 图像尺寸 #define EI_CAMERA_COLS 320 #define EI_CAMERA_ROWS 240 #define MODEL_INPUT_WIDTH EI_CLASSIFIER_INPUT_WIDTH #define MODEL_INPUT_HEIGHT EI_CLASSIFIER_INPUT_HEIGHT // OLED配置 #define OLED_WIDTH 128 #define OLED_HEIGHT 64 #define OLED_RESET -1 #define OLED_SDA 21 #define OLED_SCL 22 Adafruit_SSD1306 display(OLED_WIDTH, OLED_HEIGHT, &Wire, OLED_RESET); // WiFi配置 const char* ssid = "88888888"; const char* password = "11111111"; // SD卡配置(SPI接口) #define SD_MOUNT_POINT "/sdcard" #define SD_PIN_CS 15 // 改为常用的SPI CS引脚(原5可能冲突) // 全局变量 WiFiServer server(80); static bool is_initialised = false; static bool wifi_connected = false; static bool sd_ready = false; uint8_t* model_buf = NULL; camera_fb_t* fb = NULL; SemaphoreHandle_t camera_mutex = NULL; SemaphoreHandle_t sd_mutex = NULL; // 摄像头配置 static camera_config_t camera_config = { .pin_pwdn = PWDN_GPIO_NUM, .pin_reset = RESET_GPIO_NUM, .pin_xclk = XCLK_GPIO_NUM, .pin_sscb_sda = SIOD_GPIO_NUM, .pin_sscb_scl = SIOC_GPIO_NUM, .pin_d7 = Y9_GPIO_NUM, .pin_d6 = Y8_GPIO_NUM, .pin_d5 = Y7_GPIO_NUM, .pin_d4 = Y6_GPIO_NUM, .pin_d3 = Y5_GPIO_NUM, .pin_d2 = Y4_GPIO_NUM, .pin_d1 = Y3_GPIO_NUM, .pin_d0 = Y2_GPIO_NUM, .pin_vsync = VSYNC_GPIO_NUM, .pin_href = HREF_GPIO_NUM, .pin_pclk = PCLK_GPIO_NUM, .xclk_freq_hz = XCLK_FREQ_HZ, .ledc_timer = LEDC_TIMER_0, .ledc_channel = LEDC_CHANNEL_0, .pixel_format = PIXFORMAT_JPEG, .frame_size = FRAME_SIZE, .jpeg_quality = JPEG_QUALITY, .fb_count = 1, .fb_location = CAMERA_FB_IN_PSRAM, .grab_mode = CAMERA_GRAB_WHEN_EMPTY, }; /* -------------------------- 时间初始化 -------------------------- */ // 初始化时间(使用NTP同步) void init_time() { configTime(8 * 3600, 0, "pool.ntp.org", "time.nist.gov"); // 北京时间(UTC+8) Serial.println("等待时间同步..."); time_t now = time(nullptr); int retry_count = 0; // 等待时间同步,超时则跳过 while (now < 1609459200 && retry_count < 10) { // 等待同步到2021年之后 delay(1000); Serial.print("."); now = time(nullptr); retry_count++; } if (now >= 1609459200) { Serial.println("\n时间同步完成"); struct tm* tm_info = localtime(&now); char time_str[26]; strftime(time_str, 26, "%Y-%m-%d %H:%M:%S", tm_info); Serial.print("当前时间: "); Serial.println(time_str); } else { Serial.println("\n时间同步超时,使用默认时间"); } } /* -------------------------- SD卡操作 -------------------------- */ #ifdef ENABLE_SD_CARD bool sd_init() { sd_mutex = xSemaphoreCreateMutex(); if (!sd_mutex) { Serial.println("SD卡互斥锁创建失败"); return false; } Serial.println("初始化SD卡..."); // 尝试SDMMC模式(仅适用于支持SDMMC的板子) if (!SD_MMC.begin("/sdcard", true)) { // 1线模式 Serial.println("SDMMC模式失败,尝试SPI模式..."); // SPI模式初始化(低速模式提高兼容性) if (!SD.begin(SD_PIN_CS, SPI, 1000000)) { // 1MHz低速率 Serial.println("SPI模式初始化失败,检查:"); Serial.println("1. 引脚连接是否正确(CS=" + String(SD_PIN_CS) + ", SCK=18, MOSI=23, MISO=19)"); Serial.println("2. SD卡是否为FAT32格式"); Serial.println("3. 尝试更换SD卡"); return false; } } // 验证SD卡读写功能 File testFile = SD.open("/test.txt", FILE_WRITE); if (testFile) { testFile.println("SD卡测试成功"); testFile.close(); // 读取测试 testFile = SD.open("/test.txt", FILE_READ); if (testFile) { String content = testFile.readString(); testFile.close(); SD.remove("/test.txt"); // 删除测试文件 Serial.println("SD卡读写验证成功: " + content); } } else { Serial.println("SD卡写入测试失败"); return false; } // 创建目录 if (!SD.exists("/logs")) SD.mkdir("/logs"); if (!SD.exists("/images")) SD.mkdir("/images"); sd_ready = true; Serial.println("SD卡初始化成功"); return true; } // 写入日志到SD卡 void sd_log(const char* message) { if (!sd_ready) return; if (xSemaphoreTake(sd_mutex, 1000 / portTICK_PERIOD_MS) != pdTRUE) return; time_t now = time(nullptr); struct tm* tm = localtime(&now); char filename[32]; sprintf(filename, "/logs/%04d%02d%02d.txt", tm->tm_year + 1900, tm->tm_mon + 1, tm->tm_mday); File file = SD.open(filename, FILE_APPEND); if (file) { char timestamp[32]; sprintf(timestamp, "[%02d:%02d:%02d] ", tm->tm_hour, tm->tm_min, tm->tm_sec); file.print(timestamp); file.println(message); file.close(); } xSemaphoreGive(sd_mutex); } // 保存图像到SD卡 bool sd_save_image(const uint8_t* data, size_t size) { if (!sd_ready || !data || size == 0) return false; if (xSemaphoreTake(sd_mutex, 1000 / portTICK_PERIOD_MS) != pdTRUE) return false; time_t now = time(nullptr); struct tm* tm = localtime(&now); char filename[64]; sprintf(filename, "/images/img_%04d%02d%02d_%02d%02d%02d.jpg", tm->tm_year + 1900, tm->tm_mon + 1, tm->tm_mday, tm->tm_hour, tm->tm_min, tm->tm_sec); File file = SD.open(filename, FILE_WRITE); if (!file) { xSemaphoreGive(sd_mutex); return false; } bool success = (file.write(data, size) == size); file.close(); xSemaphoreGive(sd_mutex); if (success) { Serial.printf("图像保存到: %s\n", filename); sd_log((String("图像保存: ") + filename).c_str()); } return success; } // 从SD卡读取图像 size_t sd_read_image(const char* filename, uint8_t* buffer, size_t max_size) { if (!sd_ready || !buffer || max_size == 0) return 0; if (xSemaphoreTake(sd_mutex, 1000 / portTICK_PERIOD_MS) != pdTRUE) return 0; File file = SD.open(filename, FILE_READ); if (!file) { xSemaphoreGive(sd_mutex); return 0; } size_t size = file.size(); if (size > max_size) size = max_size; size_t read = file.read(buffer, size); file.close(); xSemaphoreGive(sd_mutex); return read; } #endif /* -------------------------- 图像处理函数 -------------------------- */ bool convert_jpeg_to_rgb888_from_sd(const char* jpeg_path, uint8_t* rgb_data, size_t rgb_size) { if (!sd_ready || !rgb_data) return false; File file = SD.open(jpeg_path, FILE_READ); if (!file) return false; size_t jpeg_size = file.size(); if (jpeg_size == 0 || jpeg_size > 1024*200) { file.close(); return false; } uint8_t* jpeg_buf = (uint8_t*)ps_malloc(jpeg_size); if (!jpeg_buf) { file.close(); return false; } size_t read = file.read(jpeg_buf, jpeg_size); file.close(); if (read != jpeg_size) { free(jpeg_buf); return false; } bool success = fmt2rgb888(jpeg_buf, jpeg_size, PIXFORMAT_JPEG, rgb_data); free(jpeg_buf); return success; } // 备用缩放函数(当默认缩放失败时使用) bool backup_resize_rgb888(const uint8_t* src, uint32_t src_width, uint32_t src_height, uint8_t* dst, uint32_t dst_width, uint32_t dst_height) { if (!src || !dst || src_width == 0 || src_height == 0 || dst_width == 0 || dst_height == 0) { return false; } if (((uintptr_t)dst) % 4 != 0) { Serial.println("错误:输出缓冲区未4字节对齐"); return false; } float x_ratio = (float)src_width / (float)dst_width; float y_ratio = (float)src_height / (float)dst_height; for (uint32_t y = 0; y < dst_height; y++) { for (uint32_t x = 0; x < dst_width; x++) { float src_x = x * x_ratio; float src_y = y * y_ratio; uint32_t x1 = (uint32_t)src_x; uint32_t y1 = (uint32_t)src_y; uint32_t x2 = (x1 < src_width - 1) ? x1 + 1 : x1; uint32_t y2 = (y1 < src_height - 1) ? y1 + 1 : y1; float fx = src_x - x1; float fy = src_y - y1; for (uint8_t c = 0; c < 3; c++) { uint8_t v11 = src[(y1 * src_width + x1) * 3 + c]; uint8_t v12 = src[(y2 * src_width + x1) * 3 + c]; uint8_t v21 = src[(y1 * src_width + x2) * 3 + c]; uint8_t v22 = src[(y2 * src_width + x2) * 3 + c]; uint8_t v1 = (uint8_t)((1 - fx) * v11 + fx * v21); uint8_t v2 = (uint8_t)((1 - fx) * v12 + fx * v22); dst[(y * dst_width + x) * 3 + c] = (uint8_t)((1 - fy) * v1 + fy * v2); } } } return true; } /* -------------------------- 工具函数 -------------------------- */ void oled_print(const char* line1, const char* line2 = "", const char* line3 = "") { #ifdef ENABLE_OLED_DISPLAY display.clearDisplay(); display.setTextSize(1); display.setTextColor(SSD1306_WHITE); display.setCursor(0, 0); display.println(line1); if (strlen(line2) > 0) { display.setCursor(0, 16); display.println(line2); } if (strlen(line3) > 0) { display.setCursor(0, 32); display.println(line3); } display.display(); #endif } /* -------------------------- 摄像头操作 -------------------------- */ bool camera_init() { if (is_initialised) return true; Serial.println("\n===== 摄像头初始化 ====="); camera_mutex = xSemaphoreCreateMutex(); #ifdef ENABLE_SD_CARD // 初始化SD卡(允许失败,不影响主功能) if (!sd_init()) { Serial.println("SD卡初始化失败,继续启动系统"); } #endif gpio_uninstall_isr_service(); esp_err_t err; int init_retry = 0; while (init_retry < 3) { err = esp_camera_init(&camera_config); if (err == ESP_OK) break; Serial.printf("摄像头初始化失败(重试%d): %s\n", init_retry+1, esp_err_to_name(err)); #ifdef ENABLE_SD_CARD if (sd_ready) { sd_log((String("摄像头初始化失败: ") + esp_err_to_name(err)).c_str()); } #endif if (err == ESP_ERR_INVALID_STATE) { gpio_uninstall_isr_service(); } init_retry++; vTaskDelay(1000 / portTICK_PERIOD_MS); } if (err != ESP_OK) { Serial.println("摄像头初始化彻底失败"); #ifdef ENABLE_SD_CARD if (sd_ready) { sd_log("摄像头初始化彻底失败"); } #endif return false; } sensor_t* s = esp_camera_sensor_get(); if (s) { s->set_vflip(s, 1); s->set_hmirror(s, 1); s->set_awb_gain(s, 1); } size_t model_size = MODEL_INPUT_WIDTH * MODEL_INPUT_HEIGHT * 3; model_size = (model_size + 3) & ~3; // 4字节对齐 model_buf = (uint8_t*)aligned_alloc(4, model_size); if (!model_buf) { Serial.println("模型缓冲区分配失败"); camera_deinit(); return false; } Serial.printf("模型缓冲区: %zu bytes\n", model_size); is_initialised = true; Serial.println("摄像头初始化成功"); #ifdef ENABLE_SD_CARD if (sd_ready) { sd_log("摄像头初始化成功"); } #endif return true; } void camera_deinit() { if (!is_initialised) return; esp_camera_deinit(); if (model_buf) free(model_buf); model_buf = NULL; is_initialised = false; } bool camera_capture_to_sd() { if (!is_initialised) return false; if (xSemaphoreTake(camera_mutex, 2000 / portTICK_PERIOD_MS) != pdTRUE) { return false; } bool success = false; fb = esp_camera_fb_get(); if (fb && fb->len > 1024) { #ifdef ENABLE_SD_CARD if (sd_ready) { success = sd_save_image(fb->buf, fb->len); } #endif esp_camera_fb_return(fb); fb = NULL; } xSemaphoreGive(camera_mutex); return success; } bool process_image_from_sd(uint8_t* model_buf, size_t model_size) { if (!sd_ready || !model_buf) return false; File dir = SD.open("/images"); if (!dir) return false; File latest_file; time_t latest_time = 0; while (File file = dir.openNextFile()) { if (!file.isDirectory() && strstr(file.name(), ".jpg")) { time_t t = file.getLastWrite(); if (t > latest_time) { latest_time = t; if (latest_file) latest_file.close(); latest_file = file; } else { file.close(); } } } dir.close(); if (!latest_file) return false; const char* img_path = latest_file.path(); latest_file.close(); size_t rgb_size = EI_CAMERA_COLS * EI_CAMERA_ROWS * 3; uint8_t* rgb_buf = (uint8_t*)ps_malloc(rgb_size); if (!rgb_buf) return false; bool success = false; if (convert_jpeg_to_rgb888_from_sd(img_path, rgb_buf, rgb_size)) { success = ei::image::processing::crop_and_interpolate_rgb888( rgb_buf, EI_CAMERA_COLS, EI_CAMERA_ROWS, model_buf, MODEL_INPUT_WIDTH, MODEL_INPUT_HEIGHT ); if (!success) { success = backup_resize_rgb888( rgb_buf, EI_CAMERA_COLS, EI_CAMERA_ROWS, model_buf, MODEL_INPUT_WIDTH, MODEL_INPUT_HEIGHT ); } } free(rgb_buf); return success; } /* -------------------------- 推理核心 -------------------------- */ #ifdef ENABLE_INFERENCE void run_inference() { if (!is_initialised || !model_buf) { oled_print("未就绪", "设备异常"); return; } Serial.println("\n===== 开始推理 ====="); oled_print("识别中..."); if (!camera_capture_to_sd()) { oled_print("处理失败", "图像捕获失败"); #ifdef ENABLE_SD_CARD if (sd_ready) { sd_log("图像捕获失败"); } #endif return; } if (!process_image_from_sd(model_buf, MODEL_INPUT_WIDTH * MODEL_INPUT_HEIGHT * 3)) { oled_print("处理失败", "图像转换失败"); #ifdef ENABLE_SD_CARD if (sd_ready) { sd_log("图像转换失败"); } #endif return; } ei::signal_t signal; signal.total_length = MODEL_INPUT_WIDTH * MODEL_INPUT_HEIGHT; signal.get_data = [](size_t offset, size_t length, float* out) { size_t pixel_ix = offset * 3; if (pixel_ix + 3*length > MODEL_INPUT_WIDTH * MODEL_INPUT_HEIGHT * 3) { Serial.println("错误:模型输入数据越界"); return -1; } for (size_t i = 0; i < length; i++) { uint8_t r = model_buf[pixel_ix]; uint8_t g = model_buf[pixel_ix + 1]; uint8_t b = model_buf[pixel_ix + 2]; out[i] = (r - 127.5f) / 127.5f; out[i + length] = (g - 127.5f) / 127.5f; out[i + length * 2] = (b - 127.5f) / 127.5f; pixel_ix += 3; } return 0; }; ei_impulse_result_t result; memset(&result, 0, sizeof(result)); EI_IMPULSE_ERROR err = run_classifier(&signal, &result, false); if (err != EI_IMPULSE_OK) { Serial.printf("推理失败: %d\n", err); oled_print("推理错误", String(err).c_str()); #ifdef ENABLE_SD_CARD if (sd_ready) { sd_log((String("推理失败: ") + String(err)).c_str()); } #endif return; } float max_prob = 0; const char* max_label = "未知"; for (uint16_t i = 0; i < EI_CLASSIFIER_LABEL_COUNT; i++) { if (result.classification[i].value > max_prob) { max_prob = result.classification[i].value; max_label = ei_classifier_inferencing_categories[i]; } } Serial.printf("识别结果: %s (%.1f%%)\n", max_label, max_prob*100); oled_print("识别为:", max_label, (String(max_prob*100, 1) + "%").c_str()); #ifdef ENABLE_SD_CARD if (sd_ready) { sd_log((String("识别结果: ") + max_label + " (" + String(max_prob*100) + "%)").c_str()); } #endif } #endif /* -------------------------- HTTP服务 -------------------------- */ #ifdef ENABLE_HTTP_SERVER void handle_client(WiFiClient& client) { String req = client.readStringUntil('\n'); req.trim(); Serial.println("HTTP请求: " + req); if (req.startsWith("GET /photo")) { client.println("HTTP/1.1 200 OK"); client.println("Content-Type: image/jpeg"); client.println("Connection: close"); client.println(); #ifdef ENABLE_SD_CARD if (sd_ready) { File dir = SD.open("/images"); File latest_file; while (File file = dir.openNextFile()) { if (!file.isDirectory() && strstr(file.name(), ".jpg")) { if (!latest_file || file.getLastWrite() > latest_file.getLastWrite()) { if (latest_file) latest_file.close(); latest_file = file; } else { file.close(); } } } dir.close(); if (latest_file) { size_t fileSize = latest_file.size(); const size_t bufferSize = 1024; uint8_t buffer[bufferSize]; while (fileSize > 0) { size_t read = latest_file.read(buffer, min(bufferSize, fileSize)); client.write(buffer, read); fileSize -= read; } latest_file.close(); } else { client.print("无图像文件"); } } else { client.print("SD卡未就绪"); } #else client.print("SD卡功能未启用"); #endif } else if (req.startsWith("GET /infer")) { client.println("HTTP/1.1 200 OK"); client.println("Content-Type: text/plain"); client.println("Connection: close"); client.println(); run_inference(); client.println("推理已触发"); } else if (req.startsWith("GET /")) { client.println("HTTP/1.1 200 OK"); client.println("Content-Type: text/html"); client.println("Connection: close"); client.println(); client.println("<html><body>"); client.println("ESP32 识别系统"); client.println("查看最新照片
"); client.println("运行识别
"); client.println("</body></html>"); } else { client.println("HTTP/1.1 404 Not Found"); client.println("Content-Type: text/plain"); client.println("Connection: close"); client.println(); client.println("404 Not Found"); } delay(1); client.stop(); } #endif /* -------------------------- WiFi连接 -------------------------- */ void connect_wifi() { if (wifi_connected) return; Serial.println("\n===== WiFi连接 ====="); oled_print("连接WiFi...", ssid); WiFi.begin(ssid, password); int attempt = 0; while (WiFi.status() != WL_CONNECTED && attempt < 20) { delay(500); Serial.print("."); attempt++; } if (WiFi.status() == WL_CONNECTED) { wifi_connected = true; Serial.println("\nWiFi连接成功"); Serial.print("IP地址: "); Serial.println(WiFi.localIP()); oled_print("WiFi已连接", WiFi.localIP().toString().c_str()); #ifdef ENABLE_HTTP_SERVER server.begin(); Serial.println("HTTP服务启动"); #endif #ifdef ENABLE_SD_CARD if (sd_ready) { sd_log((String("WiFi连接成功 - IP: ") + WiFi.localIP().toString()).c_str()); } #endif } else { Serial.println("\nWiFi连接失败"); oled_print("WiFi连接失败", "请检查配置"); #ifdef ENABLE_SD_CARD if (sd_ready) { sd_log("WiFi连接失败"); } #endif } } /* -------------------------- 初始化和主循环 -------------------------- */ void setup() { Serial.begin(115200); Serial.println("Edge Impulse 识别系统启动中"); // 初始化OLED #ifdef ENABLE_OLED_DISPLAY Wire.begin(OLED_SDA, OLED_SCL); if (!display.begin(SSD1306_SWITCHCAPVCC, 0x3C)) { Serial.println(F("SSD1306 OLED显示屏初始化失败")); } else { display.clearDisplay(); display.setTextSize(1); display.setTextColor(SSD1306_WHITE); display.setCursor(0, 0); display.println("Edge Impulse"); display.println("识别系统启动中"); display.display(); } #endif // 初始化时间 init_time(); // 初始化摄像头 if (!camera_init()) { oled_print("错误", "摄像头初始化失败"); delay(5000); } // 连接WiFi connect_wifi(); // 启动看门狗 esp_task_wdt_init(10, false); } void loop() { // 喂狗 esp_task_wdt_reset(); // 检查WiFi连接 if (!wifi_connected || WiFi.status() != WL_CONNECTED) { wifi_connected = false; connect_wifi(); } // 处理HTTP请求 #ifdef ENABLE_HTTP_SERVER if (wifi_connected) { WiFiClient client = server.available(); if (client) { handle_client(client); } } #endif // 主循环逻辑 static unsigned long last_inference_time = 0; if (millis() - last_inference_time > 10000) { // 每10秒运行一次推理 last_inference_time = millis(); #ifdef ENABLE_INFERENCE run_inference(); #endif } delay(100); }

# -- coding: utf-8 -- import threading import time import sys import inspect import ctypes import random import os from ctypes import * sys.path.append(os.getenv('MVCAM_COMMON_RUNENV') + "/Samples/Python/MvImport") from CameraParams_header import * from MvCameraControl_class import * # 强制关闭线程 def Async_raise(tid, exctype): tid = ctypes.c_long(tid) if not inspect.isclass(exctype): exctype = type(exctype) res = ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, ctypes.py_object(exctype)) if res == 0: raise ValueError("invalid thread id") elif res != 1: ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, None) raise SystemError("PyThreadState_SetAsyncExc failed") # 停止线程 def Stop_thread(thread): Async_raise(thread.ident, SystemExit) # 转为16进制字符串 def To_hex_str(num): chaDic = {10: 'a', 11: 'b', 12: 'c', 13: 'd', 14: 'e', 15: 'f'} hexStr = "" if num < 0: num = num + 2 ** 32 while num >= 16: digit = num % 16 hexStr = chaDic.get(digit, str(digit)) + hexStr num //= 16 hexStr = chaDic.get(num, str(num)) + hexStr return hexStr # 是否是Mono图像 def Is_mono_data(enGvspPixelType): if PixelType_Gvsp_Mono8 == enGvspPixelType or PixelType_Gvsp_Mono10 == enGvspPixelType \ or PixelType_Gvsp_Mono10_Packed == enGvspPixelType or PixelType_Gvsp_Mono12 == enGvspPixelType \ or PixelType_Gvsp_Mono12_Packed == enGvspPixelType: return True else: return False # 是否是彩色图像 def Is_color_data(enGvspPixelType): if PixelType_Gvsp_BayerGR8 == enGvspPixelType or PixelType_Gvsp_BayerRG8 == enGvspPixelType \ or PixelType_Gvsp_BayerGB8 == enGvspPixelType or PixelType_Gvsp_BayerBG8 == enGvspPixelType \ or PixelType_Gvsp_BayerGR10 == enGvspPixelType or PixelType_Gvsp_BayerRG10 == enGvspPixelType \ or PixelType_Gvsp_BayerGB10 == enGvspPixelType or PixelType_Gvsp_BayerBG10 == enGvspPixelType \ or PixelType_Gvsp_BayerGR12 == enGvspPixelType or PixelType_Gvsp_BayerRG12 == enGvspPixelType \ or PixelType_Gvsp_BayerGB12 == enGvspPixelType or PixelType_Gvsp_BayerBG12 == enGvspPixelType \ or PixelType_Gvsp_BayerGR10_Packed == enGvspPixelType or PixelType_Gvsp_BayerRG10_Packed == enGvspPixelType \ or PixelType_Gvsp_BayerGB10_Packed == enGvspPixelType or PixelType_Gvsp_BayerBG10_Packed == enGvspPixelType \ or PixelType_Gvsp_BayerGR12_Packed == enGvspPixelType or PixelType_Gvsp_BayerRG12_Packed == enGvspPixelType \ or PixelType_Gvsp_BayerGB12_Packed == enGvspPixelType or PixelType_Gvsp_BayerBG12_Packed == enGvspPixelType \ or PixelType_Gvsp_YUV422_Packed == enGvspPixelType or PixelType_Gvsp_YUV422_YUYV_Packed == enGvspPixelType: return True else: return False # 相机操作类 class CameraOperation: def __init__(self, obj_cam, st_device_list, n_connect_num=0, b_open_device=False, b_start_grabbing=False, h_thread_handle=None, b_thread_closed=False, st_frame_info=None, b_exit=False, b_save_bmp=False, b_save_jpg=False, buf_save_image=None, n_save_image_size=0, n_win_gui_id=0, frame_rate=0, exposure_time=0, gain=0): self.obj_cam = obj_cam self.st_device_list = st_device_list self.n_connect_num = n_connect_num self.b_open_device = b_open_device self.b_start_grabbing = b_start_grabbing self.b_thread_closed = b_thread_closed self.st_frame_info = st_frame_info self.b_exit = b_exit self.b_save_bmp = b_save_bmp self.b_save_jpg = b_save_jpg self.buf_save_image = buf_save_image self.n_save_image_size = n_save_image_size self.h_thread_handle = h_thread_handle self.b_thread_closed self.frame_rate = frame_rate self.exposure_time = exposure_time self.gain = gain self.buf_lock = threading.Lock() # 取图和存图的buffer锁 # 打开相机 def Open_device(self): if not self.b_open_device: if self.n_connect_num < 0: return MV_E_CALLORDER # ch:选择设备并创建句柄 | en:Select device and create handle nConnectionNum = int(self.n_connect_num) stDeviceList = cast(self.st_device_list.pDeviceInfo[int(nConnectionNum)], POINTER(MV_CC_DEVICE_INFO)).contents self.obj_cam = MvCamera() ret = self.obj_cam.MV_CC_CreateHandle(stDeviceList) if ret != 0: self.obj_cam.MV_CC_DestroyHandle() return ret ret = self.obj_cam.MV_CC_OpenDevice() if ret != 0: return ret print("open device successfully!") self.b_open_device = True self.b_thread_closed = False # ch:探测网络最佳包大小(只对GigE相机有效) | en:Detection network optimal package size(It only works for the GigE camera) if stDeviceList.nTLayerType == MV_GIGE_DEVICE or stDeviceList.nTLayerType == MV_GENTL_GIGE_DEVICE: nPacketSize = self.obj_cam.MV_CC_GetOptimalPacketSize() if int(nPacketSize) > 0: ret = self.obj_cam.MV_CC_SetIntValue("GevSCPSPacketSize", nPacketSize) if ret != 0: print("warning: set packet size fail! ret[0x%x]" % ret) else: print("warning: set packet size fail! ret[0x%x]" % nPacketSize) stBool = c_bool(False) ret = self.obj_cam.MV_CC_GetBoolValue("AcquisitionFrameRateEnable", stBool) if ret != 0: print("get acquisition frame rate enable fail! ret[0x%x]" % ret) # ch:设置触发模式为off | en:Set trigger mode as off ret = self.obj_cam.MV_CC_SetEnumValue("TriggerMode", MV_TRIGGER_MODE_OFF) if ret != 0: print("set trigger mode fail! ret[0x%x]" % ret) return MV_OK # 开始取图 def Start_grabbing(self, winHandle): if not self.b_start_grabbing and self.b_open_device: self.b_exit = False ret = self.obj_cam.MV_CC_StartGrabbing() if ret != 0: return ret self.b_start_grabbing = True print("start grabbing successfully!") try: thread_id = random.randint(1, 10000) self.h_thread_handle = threading.Thread(target=CameraOperation.Work_thread, args=(self, winHandle)) self.h_thread_handle.start() self.b_thread_closed = True finally: pass return MV_OK return MV_E_CALLORDER # 停止取图 def Stop_grabbing(self): if self.b_start_grabbing and self.b_open_device: # 退出线程 if self.b_thread_closed: Stop_thread(self.h_thread_handle) self.b_thread_closed = False ret = self.obj_cam.MV_CC_StopGrabbing() if ret != 0: return ret print("stop grabbing successfully!") self.b_start_grabbing = False self.b_exit = True return MV_OK else: return MV_E_CALLORDER # 关闭相机 def Close_device(self): if self.b_open_device: # 退出线程 if self.b_thread_closed: Stop_thread(self.h_thread_handle) self.b_thread_closed = False ret = self.obj_cam.MV_CC_CloseDevice() if ret != 0: return ret # ch:销毁句柄 | Destroy handle self.obj_cam.MV_CC_DestroyHandle() self.b_open_device = False self.b_start_grabbing = False self.b_exit = True print("close device successfully!") return MV_OK # 设置触发模式 def Set_trigger_mode(self, is_trigger_mode): if not self.b_open_device: return MV_E_CALLORDER if not is_trigger_mode: ret = self.obj_cam.MV_CC_SetEnumValue("TriggerMode", 0) if ret != 0: return ret else: ret = self.obj_cam.MV_CC_SetEnumValue("TriggerMode", 1) if ret != 0: return ret ret = self.obj_cam.MV_CC_SetEnumValue("TriggerSource", 7) if ret != 0: return ret return MV_OK # 软触发一次 def Trigger_once(self): if self.b_open_device: return self.obj_cam.MV_CC_SetCommandValue("TriggerSoftware") # 获取参数 def Get_parameter(self): if self.b_open_device: stFloatParam_FrameRate = MVCC_FLOATVALUE() memset(byref(stFloatParam_FrameRate), 0, sizeof(MVCC_FLOATVALUE)) stFloatParam_exposureTime = MVCC_FLOATVALUE() memset(byref(stFloatParam_exposureTime), 0, sizeof(MVCC_FLOATVALUE)) stFloatParam_gain = MVCC_FLOATVALUE() memset(byref(stFloatParam_gain), 0, sizeof(MVCC_FLOATVALUE)) ret = self.obj_cam.MV_CC_GetFloatValue("AcquisitionFrameRate", stFloatParam_FrameRate) if ret != 0: return ret self.frame_rate = stFloatParam_FrameRate.fCurValue ret = self.obj_cam.MV_CC_GetFloatValue("ExposureTime", stFloatParam_exposureTime) if ret != 0: return ret self.exposure_time = stFloatParam_exposureTime.fCurValue ret = self.obj_cam.MV_CC_GetFloatValue("Gain", stFloatParam_gain) if ret != 0: return ret self.gain = stFloatParam_gain.fCurValue return MV_OK # 设置参数 def Set_parameter(self, frameRate, exposureTime, gain): if '' == frameRate or '' == exposureTime or '' == gain: print('show info', 'please type in the text box !') return MV_E_PARAMETER if self.b_open_device: ret = self.obj_cam.MV_CC_SetEnumValue("ExposureAuto", 0) time.sleep(0.2) ret = self.obj_cam.MV_CC_SetFloatValue("ExposureTime", float(exposureTime)) if ret != 0: print('show error', 'set exposure time fail! ret = ' + To_hex_str(ret)) return ret ret = self.obj_cam.MV_CC_SetFloatValue("Gain", float(gain)) if ret != 0: print('show error', 'set gain fail! ret = ' + To_hex_str(ret)) return ret ret = self.obj_cam.MV_CC_SetFloatValue("AcquisitionFrameRate", float(frameRate)) if ret != 0: print('show error', 'set acquistion frame rate fail! ret = ' + To_hex_str(ret)) return ret print('show info', 'set parameter success!') return MV_OK # 取图线程函数 def Work_thread(self, winHandle): stOutFrame = MV_FRAME_OUT() memset(byref(stOutFrame), 0, sizeof(stOutFrame)) while True: ret = self.obj_cam.MV_CC_GetImageBuffer(stOutFrame, 1000) if 0 == ret: # 拷贝图像和图像信息 if self.buf_save_image is None: self.buf_save_image = (c_ubyte * stOutFrame.stFrameInfo.nFrameLen)() self.st_frame_info = stOutFrame.stFrameInfo # 获取缓存锁 self.buf_lock.acquire() cdll.msvcrt.memcpy(byref(self.buf_save_image), stOutFrame.pBufAddr, self.st_frame_info.nFrameLen) self.buf_lock.release() print("get one frame: Width[%d], Height[%d], nFrameNum[%d]" % (self.st_frame_info.nWidth, self.st_frame_info.nHeight, self.st_frame_info.nFrameNum)) # 释放缓存 self.obj_cam.MV_CC_FreeImageBuffer(stOutFrame) else: print("no data, ret = " + To_hex_str(ret)) continue # 使用Display接口显示图像 stDisplayParam = MV_DISPLAY_FRAME_INFO() memset(byref(stDisplayParam), 0, sizeof(stDisplayParam)) stDisplayParam.hWnd = int(winHandle) stDisplayParam.nWidth = self.st_frame_info.nWidth stDisplayParam.nHeight = self.st_frame_info.nHeight stDisplayParam.enPixelType = self.st_frame_info.enPixelType stDisplayParam.pData = self.buf_save_image stDisplayParam.nDataLen = self.st_frame_info.nFrameLen self.obj_cam.MV_CC_DisplayOneFrame(stDisplayParam) # 是否退出 if self.b_exit: if self.buf_save_image is not None: del self.buf_save_image break # 存jpg图像 def Save_jpg(self): if self.buf_save_image is None: return # 获取缓存锁 self.buf_lock.acquire() file_path = str(self.st_frame_info.nFrameNum) + ".jpg" c_file_path = file_path.encode('ascii') stSaveParam = MV_SAVE_IMAGE_TO_FILE_PARAM_EX() stSaveParam.enPixelType = self.st_frame_info.enPixelType # ch:相机对应的像素格式 | en:Camera pixel type stSaveParam.nWidth = self.st_frame_info.nWidth # ch:相机对应的宽 | en:Width stSaveParam.nHeight = self.st_frame_info.nHeight # ch:相机对应的高 | en:Height stSaveParam.nDataLen = self.st_frame_info.nFrameLen stSaveParam.pData = cast(self.buf_save_image, POINTER(c_ubyte)) stSaveParam.enImageType = MV_Image_Jpeg # ch:需要保存的图像类型 | en:Image format to save stSaveParam.nQuality = 80 stSaveParam.pcImagePath = ctypes.create_string_buffer(c_file_path) stSaveParam.iMethodValue = 1 ret = self.obj_cam.MV_CC_SaveImageToFileEx(stSaveParam) self.buf_lock.release() return ret # 存BMP图像 def Save_Bmp(self): if 0 == self.buf_save_image: return # 获取缓存锁 self.buf_lock.acquire() file_path = str(self.st_frame_info.nFrameNum) + ".bmp" c_file_path = file_path.encode('ascii') stSaveParam = MV_SAVE_IMAGE_TO_FILE_PARAM_EX() stSaveParam.enPixelType = self.st_frame_info.enPixelType # ch:相机对应的像素格式 | en:Camera pixel type stSaveParam.nWidth = self.st_frame_info.nWidth # ch:相机对应的宽 | en:Width stSaveParam.nHeight = self.st_frame_info.nHeight # ch:相机对应的高 | en:Height stSaveParam.nDataLen = self.st_frame_info.nFrameLen stSaveParam.pData = cast(self.buf_save_image, POINTER(c_ubyte)) stSaveParam.enImageType = MV_Image_Bmp # ch:需要保存的图像类型 | en:Image format to save stSaveParam.pcImagePath = ctypes.create_string_buffer(c_file_path) stSaveParam.iMethodValue = 1 ret = self.obj_cam.MV_CC_SaveImageToFileEx(stSaveParam) self.buf_lock.release() return ret 这是CamOperation_class.py的程序使用你的第一个方法进行修改放出完整代码

static int media_get_socket(void* handle) { MediaIOPriv* priv = handle; if (!priv || priv->socket <= 0) return -EINVAL; return priv->socket; } /**************************************************************************** * Public Functions ****************************************************************************/ int media_process_command(const char* target, const char* cmd, const char* arg, char* res, int res_len) { return media_proxy(MEDIA_ID_GRAPH, NULL, target, cmd, arg, 0, res, res_len); } void media_graph_dump(const char* options) { media_proxy(MEDIA_ID_GRAPH, NULL, NULL, "dump", options, 0, NULL, 0); } void* media_player_open(const char* params) { return media_open(MEDIA_ID_PLAYER, params); } int media_player_close(void* handle, int pending_stop) { return media_close(handle, pending_stop); } int media_player_set_event_callback(void* handle, void* cookie, media_event_callback event_cb) { return media_set_event_cb(handle, cookie, event_cb); } int media_player_prepare(void* handle, const char* url, const char* options) { return media_prepare(handle, url, options); } int media_player_reset(void* handle) { if (!handle) return -EINVAL; media_close_socket(handle); return media_proxy_once(handle, NULL, "reset", NULL, 0, NULL, 0); } ssize_t media_player_write_data(void* handle, const void* data, size_t len) { return media_process_data(handle, true, (void*)data, len); } int media_player_get_sockaddr(void* handle, struct sockaddr_storage* addr) { return media_get_sockaddr(handle, addr); } void media_player_close_socket(void* handle) { media_close_socket(handle); } int media_player_get_socket(void* handle) { return media_get_socket(handle); } int media_player_start(void* handle) { if (!handle) return -EINVAL; return media_proxy_once(handle, NULL, "start", NULL, 0, NULL, 0); } int media_player_stop(void* handle) { if (!handle) return -EINVAL; media_close_socket(handle); return media_proxy_once(handle, NULL, "stop", NULL, 0, NULL, 0); } int media_player_pause(void* handle) { return media_proxy_once(handle, NULL, "pause", NULL, 0, NULL, 0); } int media_player_seek(void* handle, unsigned int msec) { char tmp[32]; snprintf(tmp, sizeof(tmp), "%u", msec); return media_proxy_once(handle, NULL, "seek", tmp, 0, NULL, 0); } int media_player_set_looping(void* handle, int loop) { char tmp[32]; snprintf(tmp, sizeof(tmp), "%d", loop); return media_proxy_once(handle, NULL, "set_loop", tmp, 0, NULL, 0); } int media_player_is_playing(void* handle) { char tmp[32]; int ret; ret = media_proxy_once(handle, NULL, "get_playing", NULL, 0, tmp, sizeof(tmp)); return ret < 0 ? ret : !!atoi(tmp); } int media_player_get_position(void* handle, unsigned int* msec) { char tmp[32]; int ret; if (!msec) return -EINVAL; ret = media_proxy_once(handle, NULL, "get_position", NULL, 0, tmp, sizeof(tmp)); if (ret >= 0) *msec = strtoul(tmp, NULL, 0); return ret; } int media_player_get_duration(void* handle, unsigned int* msec) { char tmp[32]; int ret; if (!msec) return -EINVAL; ret = media_proxy_once(handle, NULL, "get_duration", NULL, 0, tmp, sizeof(tmp)); if (ret >= 0) *msec = strtoul(tmp, NULL, 0); return ret; } int media_player_get_latency(void* handle, unsigned int* latency) { char tmp[32]; int ret; if (!latency) return -EINVAL; ret = media_proxy_once(handle, NULL, "get_latency", NULL, 0, tmp, sizeof(tmp)); if (ret >= 0) *latency = strtoul(tmp, NULL, 0); return ret; } int media_player_set_volume(void* handle, float volume) { char tmp[32]; snprintf(tmp, sizeof(tmp), "%f", volume); return media_proxy_once(handle, NULL, "volume", tmp, 0, NULL, 0); } int media_player_get_volume(void* handle, float* volume) { char tmp[32]; int ret; if (!volume) return -EINVAL; ret = media_proxy_once(handle, NULL, "get_volume", NULL, 0, tmp, sizeof(tmp)); if (ret >= 0) { sscanf(tmp, "vol:%f", volume); ret = 0; } return ret; } int media_player_set_property(void* handle, const char* target, const char* key, const char* value) { return media_proxy_once(handle, target, key, value, 0, NULL, 0); } int media_player_get_property(void* handle, const char* target, const char* key, char* value, int value_len) { return media_proxy_once(handle, target, key, NULL, 0, value, value_len); } void* media_recorder_open(const char* params) { return media_open(MEDIA_ID_RECORDER, params); } int media_recorder_close(void* handle) { return media_close(handle, 0); } int media_recorder_set_event_callback(void* handle, void* cookie, media_event_callback event_cb) { return media_set_event_cb(handle, cookie, event_cb); } int media_recorder_prepare(void* handle, const char* url, const char* options) { return media_prepare(handle, url, options); } int media_recorder_reset(void* handle) { if (!handle) return -EINVAL; media_close_socket(handle); return media_proxy_once(handle, NULL, "reset", NULL, 0, NULL, 0); } ssize_t media_recorder_read_data(void* handle, void* data, size_t len) { return media_process_data(handle, false, data, len); } int media_recorder_get_sockaddr(void* handle, struct sockaddr_storage* addr) { return media_get_sockaddr(handle, addr); } int media_recorder_get_socket(void* handle) { return media_get_socket(handle); } void media_recorder_close_socket(void* handle) { media_close_socket(handle); } int media_recorder_start(void* handle) { return media_proxy_once(handle, NULL, "start", NULL, 0, NULL, 0); } int media_recorder_pause(void* handle) { return media_proxy_once(handle, NULL, "pause", NULL, 0, NULL, 0); } int media_recorder_stop(void* handle) { if (!handle) return -EINVAL; media_close_socket(handle); return media_proxy_once(handle, NULL, "stop", NULL, 0, NULL, 0); } int media_recorder_set_property(void* handle, const char* target, const char* key, const char* value) { return media_proxy_once(handle, target, key, value, 0, NULL, 0); } int media_recorder_get_property(void* handle, const char* target, const char* key, char* value, int value_len) { return media_proxy_once(handle, target, key, NULL, 0, value, value_len); } int media_recorder_take_picture(char* params, char* filename, size_t number) { int ret = 0; MediaIOPriv* priv; if (!number || number > INT_MAX) return -EINVAL; priv = calloc(1, sizeof(MediaIOPriv)); if (!priv) return -ENOMEM; sem_init(&priv->sem, 0, 0); priv->cookie = media_recorder_start_picture(params, filename, number, media_recorder_take_picture_cb, priv); if (!priv->cookie) { free(priv); return -EINVAL; } sem_wait(&priv->sem); sem_destroy(&priv->sem); ret = priv->result; free(priv); return ret; } void* media_recorder_start_picture(char* params, char* filename, size_t number, media_event_callback event_cb, void* cookie) { char option[32]; void* handle = NULL; int ret; if (!number || number > INT_MAX) return NULL; handle = media_recorder_open(params); if (!handle) return NULL; ret = media_recorder_set_event_callback(handle, cookie, event_cb); if (ret < 0) goto error; snprintf(option, sizeof(option), "total_number=%zu", number); ret = media_recorder_prepare(handle, filename, option); if (ret < 0) goto error; ret = media_recorder_start(handle); if (ret < 0) goto error; return handle; error: media_recorder_close(handle); return NULL; } int media_recorder_finish_picture(void* handle) { return media_recorder_close(handle); }

#include "camera_pins.h" #include <WiFi.h> #include "esp_camera.h" #include <Wire.h> #include <Adafruit_GFX.h> #include <Adafruit_SSD1306.h> // Edge Impulse模型库(需手动添加到项目目录) #include "shibie_inferencing.h" #include "edge-impulse-sdk/dsp/image/image.hpp" #include "esp_task_wdt.h" // 功能开关 #define ENABLE_INFERENCE        1 #define ENABLE_HTTP_SERVER      1 #define ENABLE_OLED_DISPLAY     1 #define SUPPORT_OBJECT_DETECTION 0 // 摄像头配置 #define CAMERA_MODEL_AI_THINKER #define XCLK_FREQ_HZ            8000000   // 8MHz时钟,更稳定 #define FRAME_SIZE              FRAMESIZE_QVGA  // 320x240 #define JPEG_QUALITY            10         // 低压缩比,高质量 #define MAX_CAPTURE_RETRIES     3          // 捕获重试次数 // 图像尺寸 #define EI_CAMERA_COLS          320 #define EI_CAMERA_ROWS          240 #define MODEL_INPUT_WIDTH       EI_CLASSIFIER_INPUT_WIDTH #define MODEL_INPUT_HEIGHT      EI_CLASSIFIER_INPUT_HEIGHT // OLED配置 #define OLED_WIDTH              128 #define OLED_HEIGHT             64 #define OLED_RESET              -1 #define OLED_SDA                21 #define OLED_SCL                22 Adafruit_SSD1306 display(OLED_WIDTH, OLED_HEIGHT, &Wire, OLED_RESET); // WiFi配置 const char* ssid     = "88888888"; const char* password = "11111111"; // 全局变量 WiFiServer server(80); static bool is_initialised = false; static bool wifi_connected = false; uint8_t* snapshot_buf = NULL;  // 原始RGB缓冲区 uint8_t* model_buf = NULL;     // 模型输入缓冲区 camera_fb_t* fb = NULL; // 摄像头配置 static camera_config_t camera_config = {     .pin_pwdn     = PWDN_GPIO_NUM,     .pin_reset    = RESET_GPIO_NUM,     .pin_xclk     = XCLK_GPIO_NUM,     .pin_sscb_sda = SIOD_GPIO_NUM,     .pin_sscb_scl = SIOC_GPIO_NUM,     .pin_d7       = Y9_GPIO_NUM,     .pin_d6       = Y8_GPIO_NUM,     .pin_d5       = Y7_GPIO_NUM,     .pin_d4       = Y6_GPIO_NUM,     .pin_d3       = Y5_GPIO_NUM,     .pin_d2       = Y4_GPIO_NUM,     .pin_d1       = Y3_GPIO_NUM,     .pin_d0       = Y2_GPIO_NUM,     .pin_vsync    = VSYNC_GPIO_NUM,     .pin_href     = HREF_GPIO_NUM,     .pin_pclk     = PCLK_GPIO_NUM,     .xclk_freq_hz = XCLK_FREQ_HZ,     .ledc_timer   = LEDC_TIMER_0,     .ledc_channel = LEDC_CHANNEL_0,     .pixel_format = PIXFORMAT_JPEG,     .frame_size   = FRAME_SIZE,     .jpeg_quality = JPEG_QUALITY,     .fb_count     = 2,  // 双缓冲     .fb_location  = CAMERA_FB_IN_PSRAM,     .grab_mode    = CAMERA_GRAB_WHEN_EMPTY, }; // 正确的JPEG转RGB888函数(使用ESP32官方函数) bool convert_jpeg_to_rgb888(const uint8_t* jpeg_data, size_t jpeg_size, uint8_t* rgb_data, size_t rgb_size) {     // 使用ESP32摄像头库自带的fmt2rgb888函数(官方推荐)     return fmt2rgb888(jpeg_data, jpeg_size, PIXFORMAT_JPEG, rgb_data); } // 备用缩放函数(双线性插值,解决SDK缩放失败问题) bool backup_resize_rgb888(const uint8_t* src, uint32_t src_width, uint32_t src_height,                          uint8_t* dst, uint32_t dst_width, uint32_t dst_height) {     if (!src || !dst || src_width == 0 || src_height == 0 || dst_width == 0 || dst_height == 0) {         return false;     }     float x_ratio = (float)src_width / (float)dst_width;     float y_ratio = (float)src_height / (float)dst_height;     for (uint32_t y = 0; y < dst_height; y++) {         for (uint32_t x = 0; x < dst_width; x++) {             float src_x = x * x_ratio;             float src_y = y * y_ratio;                         uint32_t x1 = (uint32_t)src_x;             uint32_t y1 = (uint32_t)src_y;             uint32_t x2 = (x1 < src_width - 1) ? x1 + 1 : x1;             uint32_t y2 = (y1 < src_height - 1) ? y1 + 1 : y1;                         float fx = src_x - x1;             float fy = src_y - y1;                         for (uint8_t c = 0; c < 3; c++) {                 uint8_t v11 = src[(y1 * src_width + x1) * 3 + c];                 uint8_t v12 = src[(y2 * src_width + x1) * 3 + c];                 uint8_t v21 = src[(y1 * src_width + x2) * 3 + c];                 uint8_t v22 = src[(y2 * src_width + x2) * 3 + c];                                 uint8_t v1 = (uint8_t)((1 - fx) * v11 + fx * v21);                 uint8_t v2 = (uint8_t)((1 - fx) * v12 + fx * v22);                                 dst[(y * dst_width + x) * 3 + c] = (uint8_t)((1 - fy) * v1 + fy * v2);             }         }     }         return true; } /* -------------------------- 工具函数 -------------------------- */ void oled_print(const char* line1, const char* line2 = "", const char* line3 = "") { #ifdef ENABLE_OLED_DISPLAY     display.clearDisplay();     display.setTextSize(1);     display.setTextColor(SSD1306_WHITE);     display.setCursor(0, 0);     display.println(line1);     if (strlen(line2) > 0) {         display.setCursor(0, 16);         display.println(line2);     }     if (strlen(line3) > 0) {         display.setCursor(0, 32);         display.println(line3);     }     display.display(); #endif } /* -------------------------- 摄像头操作 -------------------------- */ bool camera_init() {     if (is_initialised) return true;     // 初始化摄像头(带重试)     esp_err_t err;     int init_retry = 0;     while (init_retry < 3) {         err = esp_camera_init(&camera_config);         if (err == ESP_OK) break;         Serial.printf("摄像头初始化失败(重试%d): %s\n", init_retry+1, esp_err_to_name(err));         init_retry++;         vTaskDelay(1000 / portTICK_PERIOD_MS);     }     if (err != ESP_OK) {         Serial.println("摄像头初始化彻底失败");         return false;     }     // 优化传感器参数     sensor_t* s = esp_camera_sensor_get();     if (s) {         s->set_vflip(s, 1);         // 翻转图像         s->set_hmirror(s, 1);       // 镜像图像         s->set_awb_gain(s, 1);      // 自动白平衡         s->set_exposure_ctrl(s, 1); // 自动曝光         s->set_gain_ctrl(s, 1);     // 自动增益         s->set_brightness(s, 0);    // 亮度适中         s->set_contrast(s, 0);      // 对比度适中     }     // 分配内存缓冲区(4字节对齐)     size_t snapshot_size = EI_CAMERA_COLS * EI_CAMERA_ROWS * 3;     size_t model_size = MODEL_INPUT_WIDTH * MODEL_INPUT_HEIGHT * 3;         snapshot_buf = (uint8_t*)aligned_alloc(4, snapshot_size);     model_buf = (uint8_t*)aligned_alloc(4, model_size);         // 对齐分配失败时降级为普通分配     if (!snapshot_buf) snapshot_buf = (uint8_t*)malloc(snapshot_size);     if (!model_buf) model_buf = (uint8_t*)malloc(model_size);         if (!snapshot_buf || !model_buf) {         Serial.println("内存缓冲区分配失败");         camera_deinit();         return false;     }     Serial.printf("分配内存: snapshot=%zu bytes, model=%zu bytes\n", snapshot_size, model_size);     is_initialised = true;     Serial.println("摄像头初始化成功");     return true; } void camera_deinit() {     if (is_initialised) {         esp_camera_deinit();         if (snapshot_buf) free(snapshot_buf);         if (model_buf) free(model_buf);         snapshot_buf = NULL;         model_buf = NULL;         is_initialised = false;     } } // 优化后的图像捕获函数(修复JPEG转RGB错误) bool camera_capture(uint32_t img_width, uint32_t img_height, uint8_t* out_buf) {     if (!is_initialised) {         Serial.println("摄像头未初始化");         return false;     }     for (int retry = 0; retry < MAX_CAPTURE_RETRIES; retry++) {         // 获取JPEG帧         fb = esp_camera_fb_get();         if (!fb) {             Serial.printf("获取帧失败(重试%d)\n", retry+1);             vTaskDelay(200 / portTICK_PERIOD_MS);             continue;         }         // 过滤无效帧(1KB~200KB)         if (fb->len < 1024 || fb->len > 1024*200) {             Serial.printf("JPEG数据异常(%u字节),重试\n", fb->len);             esp_camera_fb_return(fb);             continue;         }         // 打印JPEG文件头(验证格式是否正确)         Serial.print("JPEG头: ");         for (int i = 0; i < 8 && i < fb->len; i++) {             Serial.printf("%02X ", fb->buf[i]); // 正常JPEG头应为FF D8 FF E0 ...         }         Serial.println();         // 转换JPEG到RGB888(使用正确的convert函数)         bool converted = convert_jpeg_to_rgb888(fb->buf, fb->len, snapshot_buf,                                               EI_CAMERA_COLS * EI_CAMERA_ROWS * 3);         esp_camera_fb_return(fb);         fb = NULL;         if (converted) {             // 打印RGB数据前8字节(验证是否有效)             Serial.print("RGB头: ");             for (int i = 0; i < 8; i++) {                 Serial.printf("%02X ", snapshot_buf[i]);             }             Serial.println();             // 尝试SDK缩放函数             bool resized = false;             Serial.println("尝试SDK缩放...");             resized = ei::image::processing::crop_and_interpolate_rgb888(                 snapshot_buf, EI_CAMERA_COLS, EI_CAMERA_ROWS,                 out_buf, img_width, img_height             );             if (!resized) {                 // SDK缩放失败时用备用函数                 Serial.println("SDK缩放失败,尝试备用缩放...");                 resized = backup_resize_rgb888(                     snapshot_buf, EI_CAMERA_COLS, EI_CAMERA_ROWS,                     out_buf, img_width, img_height                 );             }             if (resized) {                 Serial.println("缩放成功");                 return true;             }             // 缩放失败原因             Serial.println("缩放失败原因:数据格式异常");         } else {             Serial.printf("JPEG转RGB失败(重试%d)\n", retry+1);         }         vTaskDelay(200 / portTICK_PERIOD_MS);     }     Serial.println("图像处理最终失败");     return false; } /* -------------------------- 推理核心 -------------------------- */ #ifdef ENABLE_INFERENCE void run_inference() {     if (!is_initialised || !snapshot_buf || !model_buf) {         oled_print("未就绪", "摄像头异常");         return;     }     Serial.println("\n===== 开始推理 =====");     oled_print("识别中...");     if (!camera_capture(MODEL_INPUT_WIDTH, MODEL_INPUT_HEIGHT, model_buf)) {         oled_print("处理失败", "图像异常");         return;     }     // 准备模型输入信号     ei::signal_t signal;     signal.total_length = MODEL_INPUT_WIDTH * MODEL_INPUT_HEIGHT;     signal.get_data = [](size_t offset, size_t length, float* out) {         size_t pixel_ix = offset * 3;         for (size_t i = 0; i < length; i++) {             out[i] = (model_buf[pixel_ix] - 127.5f) / 127.5f;    // R             out[i + length] = (model_buf[pixel_ix + 1] - 127.5f) / 127.5f;  // G             out[i + length * 2] = (model_buf[pixel_ix + 2] - 127.5f) / 127.5f;  // B             pixel_ix += 3;         }         return 0;     };     // 运行推理     ei_impulse_result_t result;     EI_IMPULSE_ERROR err = run_classifier(&signal, &result, false);     if (err != EI_IMPULSE_OK) {         Serial.printf("推理失败: %d\n", err);         oled_print("推理错误", String(err).c_str());         return;     }     // 解析结果     float max_prob = 0;     const char* max_label = "未知";     for (uint16_t i = 0; i < EI_CLASSIFIER_LABEL_COUNT; i++) {         if (result.classification[i].value > max_prob) {             max_prob = result.classification[i].value;             max_label = ei_classifier_inferencing_categories[i];         }     }     // 显示结果     Serial.printf("识别结果: %s (%.1f%%)\n", max_label, max_prob*100);     oled_print("识别为:", max_label, (String(max_prob*100, 1) + "%").c_str());     Serial.println("===== 推理结束 ====="); } #endif /* -------------------------- HTTP服务 -------------------------- */ #ifdef ENABLE_HTTP_SERVER void handle_client(WiFiClient& client) {     String req = client.readStringUntil('\n');     req.trim();     Serial.println("HTTP请求: " + req);     if (req.startsWith("GET /photo")) {         client.println("HTTP/1.1 200 OK");         client.println("Content-Type: image/jpeg");         client.println("Connection: close");         client.println();         fb = esp_camera_fb_get();         if (fb && fb->len > 1024) {             client.write(fb->buf, fb->len);             esp_camera_fb_return(fb);         } else {             client.print("获取照片失败");             if (fb) esp_camera_fb_return(fb);         }         fb = NULL;     } else if (req.startsWith("GET /infer")) {         client.println("HTTP/1.1 200 OK");         client.println("Content-Type: text/plain");         client.println("Connection: close");         client.println();                 if (ENABLE_INFERENCE) {             run_inference();             client.println("推理已触发");         } else {             client.println("推理功能未启用");         }     } else {         client.println("HTTP/1.1 404 Not Found");         client.println("Content-Type: text/plain");         client.println();         client.println("支持: /photo, /infer");     }     client.stop(); } #endif /* -------------------------- 任务与初始化 -------------------------- */ void inference_task(void* param) {     while (1) {         if (wifi_connected && is_initialised) { #ifdef ENABLE_INFERENCE             run_inference(); #endif         } else {             String status = wifi_connected ? "等待摄像头" : "等待WiFi";             oled_print("准备中", status.c_str());         }         vTaskDelay(5000 / portTICK_PERIOD_MS);     } } void http_task(void* param) {     server.begin();     Serial.println("HTTP服务启动");     while (1) {         if (wifi_connected) {             WiFiClient client = server.available();             if (client) handle_client(client);         }         vTaskDelay(100 / portTICK_PERIOD_MS);     } } void wifi_monitor_task(void* param) {     while (1) {         if (WiFi.status() != WL_CONNECTED) {             if (wifi_connected) {                 wifi_connected = false;                 Serial.println("WiFi连接丢失");                 oled_print("错误", "WiFi断开");             }                         WiFi.reconnect();             Serial.println("尝试重连WiFi...");             oled_print("重连WiFi中");                         int retry = 0;             while (WiFi.status() != WL_CONNECTED && retry < 20) {                 vTaskDelay(500 / portTICK_PERIOD_MS);                 retry++;             }                         if (WiFi.status() == WL_CONNECTED) {                 wifi_connected = true;                 Serial.printf("WiFi重连成功: %s\n", WiFi.localIP().toString().c_str());                 oled_print("WiFi已恢复", WiFi.localIP().toString().c_str());             }         } else if (!wifi_connected) {             wifi_connected = true;             Serial.printf("WiFi已连接: %s\n", WiFi.localIP().toString().c_str());         }                 vTaskDelay(3000 / portTICK_PERIOD_MS);     } } void setup() {     Serial.begin(115200);     while (!Serial) vTaskDelay(100 / portTICK_PERIOD_MS);     Serial.println("Edge Impulse 识别系统启动中");     // 初始化OLED #ifdef ENABLE_OLED_DISPLAY     Wire.begin(OLED_SDA, OLED_SCL);     if (!display.begin(SSD1306_SWITCHCAPVCC, 0x3C)) {         Serial.println("OLED初始化失败(忽略)");     } else {         oled_print("系统启动中");     } #endif     // 初始化摄像头     if (!camera_init()) {         oled_print("错误", "摄像头初始化失败");         while (1) vTaskDelay(1000 / portTICK_PERIOD_MS);     }     // 连接WiFi     WiFi.begin(ssid, password);     WiFi.setSleep(false);     Serial.printf("连接WiFi: %s...\n", ssid);     oled_print("连接WiFi", ssid);     // 创建任务     xTaskCreatePinnedToCore(inference_task, "inference", 40960, NULL, 2, NULL, 0);     xTaskCreatePinnedToCore(http_task, "http", 20480, NULL, 1, NULL, 1);     xTaskCreatePinnedToCore(wifi_monitor_task, "wifi_monitor", 8192, NULL, 1, NULL, 1); } void loop() {     vTaskDelay(portMAX_DELAY); }修改

:/mnt/hgfs/UbuntuShared/3.4rockx_face_camera_vi$ arm-linux-gnueabihf-gdb ./rockx_face_camera_vi GNU gdb (GNU Toolchain for the A-profile Architecture 8.3-2019.03 (arm-rel-8.36)) 8.2.1.20190227-git Copyright (C) 2018 Free Software Foundation, Inc. License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html> This is free software: you are free to change and redistribute it. There is NO WARRANTY, to the extent permitted by law. Type "show copying" and "show warranty" for details. This GDB was configured as "--host=x86_64-pc-linux-gnu --target=arm-linux-gnueabihf". Type "show configuration" for configuration details. For bug reporting instructions, please see: <https://bugs.linaro.org/>. Find the GDB manual and other documentation resources online at: <http://www.gnu.org/software/gdb/documentation/>. For help, type "help". Type "apropos word" to search for commands related to "word"... Reading symbols from ./rockx_face_camera_vi...done. (gdb) target remote 192.168.100.75:1234 Remote debugging using 192.168.100.75:1234 Reading symbols from /opt/rv1126_rv1109_linux_sdk_v1.8.0_20210224/prebuilts/gcc/linux-x86/arm/gcc-arm-8.3-2019.03-x86_64-arm-linux-gnueabihf/arm-linux-gnueabihf/libc/lib/ld-linux-armhf.so.3...done. 0xa6ed0a00 in _start () from /opt/rv1126_rv1109_linux_sdk_v1.8.0_20210224/prebuilts/gcc/linux-x86/arm/gcc-arm-8.3-2019.03-x86_64-arm-linux-gnueabihf/arm-linux-gnueabihf/libc/lib/ld-linux-armhf.so.3 (gdb) break main Breakpoint 1 at 0x11ddc: file rockx_face_camera_vi.cpp, line 76. (gdb) continue Continuing. warning: Could not load shared library symbols for 47 libraries, e.g. /oem/usr/lib/libeasymedia.so.1. Use the "info sharedlibrary" command to see the complete listing. Do you need "set solib-search-path" or "set sysroot"? warning: Could not load shared library symbols for /usr/lib/libv4l/plugins/libv4l-mplane.so. Do you need "set solib-search-path" or "set sysroot"? [New Thread 1096.1913] Thread 1 "rockx_face_came" hit Breakpoint 1, main (argc=1, argv=0xaeb0ed24) at rockx_face_camera_vi.cpp:76 76 memset(&vi_chn_attr, 0, sizeof(VI_CHN_ATTR_S)); (gdb) next 77 vi_chn_attr.pcVideoNode = CAMERA_PATH; // Path (gdb) 78 vi_chn_attr.u32Width = 1920; // Width (gdb) next 79 vi_chn_attr.u32Height = 1080; // Height (gdb) next 80 vi_chn_attr.enPixFmt = IMAGE_TYPE_NV12; // ImageType (gdb) next 81 vi_chn_attr.enBufType = VI_CHN_BUF_TYPE_MMAP; // BufType (gdb) next 82 vi_chn_attr.u32BufCnt = 3; // Cnt (gdb) next 83 vi_chn_attr.enWorkMode = VI_WORK_MODE_NORMAL; // Mode (gdb) next 84 ret = RK_MPI_VI_SetChnAttr(CAMERA_ID, CAMERA_CHN, &vi_chn_attr); (gdb) next 85 if (ret) (gdb) next 87 printf("Vi Set Attr Failed.....\n"); (gdb) next 88 return 0; (gdb) next 92 printf("Vi Set Attr Success.....\n"); (gdb) next 95 ret = RK_MPI_VI_EnableChn(CAMERA_ID, CAMERA_CHN); (gdb) next [New Thread 1096.2089] [New Thread 1096.2090] 96 if (ret) (gdb) next 99 return 0; (gdb) next 103 printf("Vi Enable Attr Success.....\n"); (gdb) next 107 memset(&venc_chn_attr, 0, sizeof(VENC_CHN_ATTR_S)); (gdb) next 110 venc_chn_attr.stVencAttr.u32VirWidth = 1920; (gdb) next 111 venc_chn_attr.stVencAttr.u32VirHeight = 1080; (gdb) next 112 venc_chn_attr.stVencAttr.imageType = IMAGE_TYPE_NV12; (gdb) next 113 venc_chn_attr.stVencAttr.enType = RK_CODEC_TYPE_H264; (gdb) next [New Thread 1096.2167] 114 venc_chn_attr.stVencAttr.u32Profile = 66; (gdb) next 115 venc_chn_attr.stRcAttr.enRcMode = VENC_RC_MODE_H264CBR; (gdb) next 121 venc_chn_attr.stRcAttr.stH264Cbr.u32SrcFrameRateNum = 25; (gdb) next 122 ret = RK_MPI_VENC_CreateChn(VENC_CHN, &venc_chn_attr); (gdb) next 123 if (ret) (gdb) next 125 printf("ERROR: Create venc failed!\n"); (gdb) next 126 exit(0); (gdb) next 129 ret = RK_MPI_VI_StartStream(CAMERA_ID, CAMERA_CHN); (gdb) next 130 if (ret) (gdb) next 148 cerr<<"pthread create successed...."<<endl; (gdb) next 151 rockx_config_t *face_detect_config = rockx_create_config(); (gdb) next 152 ret=rockx_add_config(face_detect_config, ROCKX_CONFIG_DATA_PATH, "/userdata/rockx_data"); (gdb) next warning: Could not load shared library symbols for 6 libraries, e.g. /usr/lib32/librknn_runtime.so. Use the "info sharedlibrary" command to see the complete listing. Do you need "set solib-search-path" or "set sysroot"? [New Thread 1096.2250] 153 if (ret != ROCKX_RET_SUCCESS) (gdb) next 155 printf("Failed to add config: error code = %d\n", ret); (gdb) next 160 printf("Invalid parameter: check key or value\n"); (gdb) next 161 break; (gdb) next 163 printf("Memory allocation failed\n"); (gdb) next 164 break; (gdb) next 166 printf("类型不匹配 ...\n"); (gdb) next 175 printf("rockx_add_config successfully\n"); (gdb) next 178 rockx_handle_t face_detect_handle=NULL; (gdb) next 181 printf("第一处断点\n"); (gdb) next 183 rockx_module_t face_detect_module = ROCKX_MODULE_FACE_DETECTION_V2; (gdb) next 187 rockx_release_config(face_detect_config); // 释放配置 (gdb) next 188 printf("第三处断点\n"); (gdb) next 189 if (face_detect_ret != ROCKX_RET_SUCCESS) (gdb) next 191 printf("rockx_create face_detect failed...\n"); (gdb) next 192 return -1; (gdb) next 200 rv1126_rockx_image.width = WIDTH; (gdb) next 201 rv1126_rockx_image.height = HEIGHT; (gdb) next 202 rv1126_rockx_image.pixel_format = ROCKX_PIXEL_FORMAT_YUV420SP_NV12; (gdb) next 203 printf("Image params: width=%d, height=%d, format=%d\n", (gdb) next 206 rv1126_rockx_image.pixel_format); (gdb) next 203 printf("Image params: width=%d, height=%d, format=%d\n", (gdb) next 217 mb = RK_MPI_SYS_GetMediaBuffer(RK_ID_VI, CAMERA_CHN, -1); (gdb) next 218 if (!mb) (gdb) next 220 printf("Get Vi Stream break....\n"); (gdb) next 297 RK_MPI_VENC_DestroyChn(VENC_CHN); (gdb) next 298 RK_MPI_VI_DisableChn(CAMERA_ID, CAMERA_CHN); (gdb) next cv::String::String (this=0xaeb0ebe8, s=0x11cc3f "") at ./arm_opencv_source/include/opencv2/core/cvstd.hpp:599 599 if (!s) return; (gdb) next 601 if (!len) return; (gdb) next 603 } (gdb) next cv::String::~String (this=0xa2170b1c <__GI__IO_file_jumps>, __in_chrg=<optimized out>) at ./arm_opencv_source/include/opencv2/core/cvstd.hpp:646 646 String::~String() (gdb) next cv::String::~String (this=0x0, __in_chrg=<optimized out>) at ./arm_opencv_source/include/opencv2/core/cvstd.hpp:648 648 deallocate(); (gdb) next 649 } (gdb) next cv::String::operator= (this=0xa2170b1c <__GI__IO_file_jumps>, str=...) at ./arm_opencv_source/include/opencv2/core/cvstd.hpp:653 653 { (gdb)

#include "tanhoapi.h" #include #include<string.h> struct libusb_device_handle *devh; int transferred_bytes=0; TanhoAPI::TanhoAPI() { } bool TanhoAPI::TanhoCam_DriverInit(unsigned int CAMERA_TYPE) { return libusb_init(NULL); } void TanhoAPI::TanhoCam_OpenDriver(wchar_t *nID) { devh=libusb_open_device_with_vid_pid(NULL,0xaa55,0x8866); // libusb_device **devs; // ssize_t cnt = libusb_get_device_list(NULL, &devs); // int current = 0; // libusb_device* target = NULL; // for (int i = 0; i < cnt; i++) { // libusb_device_descriptor desc; // libusb_get_device_descriptor(devs[i], &desc); // if (desc.idVendor == 0xaa55 && desc.idProduct == 0x8866) { // if (current == nIndex) { // target = devs[i]; // break; // } // current++; // } // } // if (target) { // libusb_open(target, &devh); // } // libusb_free_device_list(devs, 1); } int TanhoAPI::TanhoCam_CloseDriver() { libusb_close(devh); libusb_exit(NULL); return 0; } unsigned char * TanhoAPI::TanhoCam_GetFrameData() { unsigned char imagedata[655360*3]; unsigned char buffer[16384]; if(devh) { int i=0; while (i<40*3) { libusb_bulk_transfer(devh,0x81, buffer, sizeof(buffer), &transferred_bytes,120 );//(设备句柄,端点地址 (IN方向), 数据缓冲区,缓冲区大小,实际传输字节数,超时时间) memcpy(imagedata+i*16384,buffer,16384); if(i>100) { i=0; for(int ftcnt=0;ftcnt<(655360+1024)*2;ftcnt++) { if((imagedata[ftcnt + 0] == 0x55) && (imagedata[ftcnt + 1] == 0xff)) { if((imagedata[ftcnt + 2] == 0xaa) && (imagedata[ftcnt + 3] == 0xcc) ) { memcpy(imagedata,imagedata+ftcnt+512,655360); break; } } } } i++; } } return imagedata; } int TanhoAPI::TanhoCam_ExecuteCmd(unsigned char data[32]) { return libusb_bulk_transfer(devh,0x01,data,sizeof(data),&transferred_bytes,120); } 有的啊

# -*- coding: utf-8 -*- import threading import time import sys import inspect import ctypes import os import cv2 import numpy as np import logging from MvCameraControl_class import * from datetime import datetime from ctypes import * from enum import Enum from ctypes import byref, cast, POINTER, c_ubyte from MvCameraControl_class import MvCamera from CameraParams_header import MV_FRAME_OUT_INFO_EX, PixelType_Gvsp_BGR8_Packed, MV_OK # 配置日志系统 def setup_logging(log_level=logging.INFO): """配置全局日志系统""" logging.basicConfig( level=log_level, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', handlers=[ logging.FileHandler("camera_operation.log"), logging.StreamHandler() ] ) logging.info("日志系统初始化完成") # 强制关闭线程 def async_raise(tid, exctype): """安全终止线程""" tid = ctypes.c_long(tid) if not inspect.isclass(exctype): exctype = type(exctype) res = ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, ctypes.py_object(exctype)) if res == 0: raise ValueError("invalid thread id") elif res != 1: ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, None) raise SystemError("PyThreadState_SetAsyncExc failed") def stop_thread(thread): """停止指定线程""" async_raise(thread.ident, SystemExit) # 触发模式常量定义(兼容不同SDK版本) try: from CameraParams_header import MV_TRIGGER_MODE_ON, MV_TRIGGER_MODE_OFF, MV_TRIGGER_SOURCE_SOFTWARE except ImportError: # 如果导入失败,使用默认值(兼容旧版本) logging.warning("CameraParams_header 导入触发模式常量失败,使用默认值") MV_TRIGGER_MODE_ON = 1 MV_TRIGGER_MODE_OFF = 0 MV_TRIGGER_SOURCE_SOFTWARE = 7 # 像素格式常量定义(兼容不同SDK版本) try: from CameraParams_header import * # 如果导入成功,使用SDK中的常量定义 PIXEL_FORMATS = { "MONO8": PixelType_Gvsp_Mono8, "MONO10": PixelType_Gvsp_Mono10, "MONO12": PixelType_Gvsp_Mono12, "BAYER_BG8": PixelType_Gvsp_BayerBG8, "BAYER_GB8": PixelType_Gvsp_BayerGB8, "BAYER_GR8": PixelType_Gvsp_BayerGR8, "BAYER_RG8": PixelType_Gvsp_BayerRG8, "RGB8": PixelType_Gvsp_RGB8_Packed, "YUV422": PixelType_Gvsp_YUV422_Packed, "YUV422_YUYV": PixelType_Gvsp_YUV422_YUYV_Packed } except ImportError: # 如果导入失败,使用默认值(兼容旧版本) logging.warning("CameraParams_header 导入失败,使用默认像素格式常量") PIXEL_FORMATS = { "MONO8": 0x01080001, "MONO10": 0x01100003, "MONO12": 0x01100005, "BAYER_BG8": 0x0108000B, "BAYER_GB8": 0x0108000A, "BAYER_GR8": 0x01080008, "BAYER_RG8": 0x01080009, "RGB8": 0x02180014, "YUV422": 0x02100032, "YUV422_YUYV": 0x0210001F } # 像素格式枚举 class PixelFormat(Enum): MONO8 = PIXEL_FORMATS["MONO8"] MONO10 = PIXEL_FORMATS["MONO10"] MONO12 = PIXEL_FORMATS["MONO12"] BAYER_BG8 = PIXEL_FORMATS["BAYER_BG8"] BAYER_GB8 = PIXEL_FORMATS["BAYER_GB8"] BAYER_GR8 = PIXEL_FORMATS["BAYER_GR8"] BAYER_RG8 = PIXEL_FORMATS["BAYER_RG8"] RGB8 = PIXEL_FORMATS["RGB8"] YUV422 = PIXEL_FORMATS["YUV422"] YUV422_YUYV = PIXEL_FORMATS["YUV422_YUYV"] def is_mono_data(enGvspPixelType): """判断是否为单色图像格式""" mono_formats = [ PIXEL_FORMATS["MONO8"], PIXEL_FORMATS["MONO10"], PIXEL_FORMATS["MONO12"], 0x010C0004, # Mono10 Packed 0x010C0006, # Mono12 Packed 0x01080002, # Mono8 Signed 0x0110000C # Mono16 ] return enGvspPixelType in mono_formats def is_color_data(enGvspPixelType): """判断是否为彩色图像格式""" color_formats = [ # Bayer格式 PIXEL_FORMATS["BAYER_BG8"], PIXEL_FORMATS["BAYER_GB8"], PIXEL_FORMATS["BAYER_GR8"], PIXEL_FORMATS["BAYER_RG8"], 0x01100011, # BayerBG10 0x01100010, # BayerGB10 0x0110000E, # BayerGR10 0x0110000F, # BayerRG10 0x01100017, # BayerBG12 0x01100016, # BayerGB12 0x01100014, # BayerGR12 0x01100015, # BayerRG12 # YUV格式 PIXEL_FORMATS["YUV422"], PIXEL_FORMATS["YUV422_YUYV"], # RGB格式 PIXEL_FORMATS["RGB8"], 0x0220001E, # RGB10_Packed 0x02300020, # RGB12_Packed 0x02400021, # RGB16_Packed 0x02180032 # BGR8_Packed ] return enGvspPixelType in color_formats def get_pixel_format_name(pixel_value): """根据像素值获取可读的名称""" for name, value in PIXEL_FORMATS.items(): if value == pixel_value: return name return f"未知格式: 0x{pixel_value:08X}" # 相机操作类 class CameraOperation: # 状态码定义 MV_OK = 0 MV_E_CALLORDER = -2147483647 MV_E_PARAMETER = -2147483646 MV_E_NO_DATA = -2147483645 MV_E_SAVE_IMAGE = -2147483644 MV_E_STATE = -2147483643 # 在 CamOperation_class.py 中修改 CameraOperation 类 def __init__(self, obj_cam, st_device_list, n_connect_num=0): """ 初始化相机操作对象 :param obj_cam: 相机对象 :param st_device_list: 设备列表 :param n_connect_num: 连接编号 """ self.obj_cam = obj_cam self.st_device_list = st_device_list self.n_connect_num = n_connect_num # 状态标志 - 确保所有属性初始化 self.b_open_device = False self.b_start_grabbing = False self.b_thread_running = False self.b_exit = False # 帧接收状态 - 关键修复:显式初始化 self.b_frame_received = False # 线程相关 self.h_thread_handle = None # 图像数据 self.st_frame_info = None self.buf_save_image = None self.n_save_image_size = 0 self.current_frame = None # 参数 self.frame_rate = 0.0 self.exposure_time = 0.0 self.gain = 0.0 # 线程安全锁 self.buf_lock = threading.Lock() # 图像缓冲区锁 self.frame_lock = threading.Lock() # 当前帧锁 self.param_lock = threading.Lock() # 参数锁 self.frame_count = 0 # 帧计数 self.last_frame_time = None # 最后帧时间 self.is_streaming = False # 取流状态 logging.info("相机操作对象初始化完成") # 添加 is_frame_available 方法 def is_frame_available(self): """检查是否有可用帧图像""" try: # 检查SDK是否返回有效帧 if hasattr(self, 'cam') and self.cam: return self.cam.is_frame_available() return False except Exception as e: logging.error(f"检查帧可用性失败: {str(e)}") return False def capture_frame(self): """捕获当前帧""" try: return self.cam.get_current_frame() except Exception as e: logging.error(f"捕获帧失败: {str(e)}") return None # 在获取图像的方法中更新 last_frame def get_current_frame(self): """获取当前帧图像""" try: # 假设这是获取图像的实际实现 frame = self.cam.get_image() # 伪代码,实际调用SDK方法 self.last_frame = frame # 更新最后捕获的帧 return frame except Exception as e: logging.error(f"获取图像失败: {str(e)}") return None # 在开始取流的方法中设置标志 def start_grabbing(self, hwnd=None): """开始取流""" ret = self.cam.start_grabbing(hwnd) if ret == MV_OK: self.is_grabbing = True return ret # 在停止取流的方法中重置标志 def Stop_grabbing(self): """停止取流""" ret = self.cam.stop_grabbing() if ret == MV_OK: self.is_grabbing = False self.last_frame = None # 清除最后帧 self.image_buffer = [] # 清空缓冲区 return ret def is_ready(self): """检查设备是否就绪""" return self.b_open_device and not self.b_exit def open_device(self): """打开相机设备""" if self.b_open_device: logging.warning("设备已打开,无需重复操作") return self.MV_OK if self.n_connect_num < 0: logging.error("无效的连接编号") return self.MV_E_CALLORDER try: # 选择设备并创建句柄 nConnectionNum = int(self.n_connect_num) stDeviceList = cast(self.st_device_list.pDeviceInfo[int(nConnectionNum)], POINTER(MV_CC_DEVICE_INFO)).contents self.obj_cam = MvCamera() # 创建相机句柄 ret = self.obj_cam.MV_CC_CreateHandle(stDeviceList) if ret != self.MV_OK: self.obj_cam.MV_CC_DestroyHandle() logging.error(f"创建句柄失败: {hex(ret)}") return ret # 打开设备 ret = self.obj_cam.MV_CC_OpenDevice() if ret != self.MV_OK: logging.error(f"打开设备失败: {hex(ret)}") return ret # 设备已成功打开 self.b_open_device = True self.b_exit = False logging.info("设备打开成功") # 探测网络最佳包大小(仅对GigE相机有效) if stDeviceList.nTLayerType in [MV_GIGE_DEVICE, MV_GENTL_GIGE_DEVICE]: nPacketSize = self.obj_cam.MV_CC_GetOptimalPacketSize() if int(nPacketSize) > 0: ret = self.obj_cam.MV_CC_SetIntValue("GevSCPSPacketSize", nPacketSize) if ret != self.MV_OK: logging.warning(f"设置包大小失败: {hex(ret)}") else: logging.warning(f"获取最佳包大小失败: {hex(nPacketSize)}") # 获取采集帧率使能状态 stBool = c_bool(False) ret = self.obj_cam.MV_CC_GetBoolValue("AcquisitionFrameRateEnable", stBool) if ret != self.MV_OK: logging.warning(f"获取帧率使能状态失败: {hex(ret)}") # 现在设备已打开,可以安全设置触发模式 ret = self.set_continue_mode() if ret != self.MV_OK: logging.warning(f"设置连续模式失败: {hex(ret)}") return self.MV_OK except Exception as e: logging.exception(f"打开设备异常: {str(e)}") # 尝试清理资源 try: if hasattr(self, 'obj_cam'): self.obj_cam.MV_CC_CloseDevice() self.obj_cam.MV_CC_DestroyHandle() except: pass self.b_open_device = False return self.MV_E_STATE def close_device(self): """关闭相机设备""" if not self.b_open_device: logging.warning("设备未打开,无需关闭") return self.MV_OK try: # 停止采集(如果正在采集) if self.b_start_grabbing: self.stop_grabbing() # 关闭设备 ret = self.obj_cam.MV_CC_CloseDevice() if ret != self.MV_OK: logging.error(f"关闭设备失败: {hex(ret)}") # 销毁句柄 ret = self.obj_cam.MV_CC_DestroyHandle() if ret != self.MV_OK: logging.error(f"销毁句柄失败: {hex(ret)}") self.b_open_device = False self.b_exit = True logging.info("设备关闭成功") return self.MV_OK except Exception as e: logging.exception(f"关闭设备异常: {str(e)}") return self.MV_E_STATE def start_grabbing(self, winHandle=None): """开始图像采集""" if not self.b_open_device: logging.error("设备未打开,无法开始采集") return self.MV_E_CALLORDER if self.b_start_grabbing: logging.warning("采集已在进行中") return self.MV_OK try: # 开始采集 ret = self.obj_cam.MV_CC_StartGrabbing() if ret != self.MV_OK: logging.error(f"开始采集失败: {hex(ret)}") return ret self.b_start_grabbing = True self.b_exit = False # 启动采集线程 self.h_thread_handle = threading.Thread( target=self.work_thread, args=(winHandle,), daemon=True ) self.h_thread_handle.start() self.b_thread_running = True logging.info("图像采集已开始") return self.MV_OK except Exception as e: logging.exception(f"开始采集异常: {str(e)}") return self.MV_E_STATE def stop_grabbing(self): """停止图像采集""" if not self.b_open_device: logging.error("设备未打开,无法停止采集") return self.MV_E_CALLORDER if not self.b_start_grabbing: logging.warning("采集未在进行中") return self.MV_OK try: # 设置退出标志 self.b_exit = True # 等待线程结束 if self.b_thread_running and self.h_thread_handle.is_alive(): self.h_thread_handle.join(timeout=2.0) if self.h_thread_handle.is_alive(): logging.warning("采集线程未正常退出,尝试强制终止") stop_thread(self.h_thread_handle) # 停止采集 ret = self.obj_cam.MV_CC_StopGrabbing() if ret != self.MV_OK: logging.error(f"停止采集失败: {hex(ret)}") return ret self.b_start_grabbing = False self.b_thread_running = False logging.info("图像采集已停止") return self.MV_OK except Exception as e: logging.exception(f"停止采集异常: {str(e)}") return self.MV_E_STATE def set_trigger_mode(self, enable=True, source=MV_TRIGGER_SOURCE_SOFTWARE): """ 设置触发模式 :param enable: 是否启用触发模式 :param source: 触发源 (默认软件触发) :return: 操作结果 """ if not self.b_open_device: logging.error("设备未打开,无法设置触发模式") return self.MV_E_CALLORDER try: mode = MV_TRIGGER_MODE_ON if enable else MV_TRIGGER_MODE_OFF ret = self.obj_cam.MV_CC_SetEnumValue("TriggerMode", mode) if ret != self.MV_OK: logging.error(f"设置触发模式失败: {hex(ret)}") return ret if enable: ret = self.obj_cam.MV_CC_SetEnumValue("TriggerSource", source) if ret != self.MV_OK: logging.error(f"设置触发源失败: {hex(ret)}") return ret logging.info(f"触发模式设置成功: {'启用' if enable else '禁用'}") return self.MV_OK except Exception as e: logging.exception(f"设置触发模式异常: {str(e)}") return self.MV_E_STATE def set_continue_mode(self): """设置连续采集模式""" # 添加设备状态检查 if not self.b_open_device: logging.error("设备未打开,无法设置连续模式") return self.MV_E_CALLORDER logging.info("尝试设置连续采集模式") try: # 禁用触发模式 ret = self.obj_cam.MV_CC_SetEnumValue("TriggerMode", MV_TRIGGER_MODE_OFF) if ret != self.MV_OK: logging.error(f"禁用触发模式失败: {hex(ret)}") return ret # 设置采集模式为连续 ret = self.obj_cam.MV_CC_SetEnumValue("AcquisitionMode", 2) # 2表示连续采集 if ret != self.MV_OK: logging.error(f"设置连续采集模式失败: {hex(ret)}") return ret logging.info("连续采集模式设置成功") return self.MV_OK except Exception as e: logging.exception(f"设置连续模式异常: {str(e)}") return self.MV_E_STATE def trigger_once(self): """执行一次软触发""" if not self.b_open_device: logging.error("设备未打开,无法触发") return self.MV_E_CALLORDER try: ret = self.obj_cam.MV_CC_SetCommandValue("TriggerSoftware") if ret != self.MV_OK: logging.error(f"软触发失败: {hex(ret)}") return ret logging.info("软触发成功") return self.MV_OK except Exception as e: logging.exception(f"软触发异常: {str(e)}") return self.MV_E_STATE def get_parameters(self): """获取相机参数""" if not self.b_open_device: logging.error("设备未打开,无法获取参数") return self.MV_E_CALLORDER try: # 使用锁保护参数访问 with self.param_lock: # 初始化返回值为整数错误码 return_code = self.MV_OK # 帧率 stFrameRate = MVCC_FLOATVALUE() memset(byref(stFrameRate), 0, sizeof(MVCC_FLOATVALUE)) ret = self.obj_cam.MV_CC_GetFloatValue("AcquisitionFrameRate", stFrameRate) if ret == self.MV_OK: self.frame_rate = stFrameRate.fCurValue logging.debug(f"获取帧率成功: {self.frame_rate}") else: logging.warning(f"获取帧率失败: {hex(ret)}") if return_code == self.MV_OK: # 保留第一个错误码 return_code = ret # 曝光时间 stExposure = MVCC_FLOATVALUE() memset(byref(stExposure), 0, sizeof(MVCC_FLOATVALUE)) ret = self.obj_cam.MV_CC_GetFloatValue("ExposureTime", stExposure) if ret == self.MV_OK: self.exposure_time = stExposure.fCurValue logging.debug(f"获取曝光时间成功: {self.exposure_time}") else: logging.warning(f"获取曝光时间失败: {hex(ret)}") if return_code == self.MV_OK: return_code = ret # 增益 stGain = MVCC_FLOATVALUE() memset(byref(stGain), 0, sizeof(MVCC_FLOATVALUE)) ret = self.obj_cam.MV_CC_GetFloatValue("Gain", stGain) if ret == self.MV_OK: self.gain = stGain.fCurValue logging.debug(f"获取增益成功: {self.gain}") else: logging.warning(f"获取增益失败: {hex(ret)}") if return_code == self.MV_OK: return_code = ret # 返回整数错误码 return return_code except Exception as e: logging.exception(f"获取参数异常: {str(e)}") return self.MV_E_STATE # 添加兼容拼写错误的方法 def get_parame(self): """兼容拼写错误的方法名:get_parame""" logging.warning("调用get_parame方法 - 可能是拼写错误,建议使用get_parameters()") return self.get_parameters() # 添加动态属性处理 def __getattr__(self, name): # 处理保存方法 if name == "Save_Image": logging.warning("动态处理Save_Image调用 - 映射到save_image") return self.save_image if name == "Save_Bmp": logging.warning("动态处理Save_Bmp调用 - 映射到save_bmp") return self.save_bmp # 处理其他可能的拼写错误 method_map = { "get_parame": self.get_parame, "get_parm": self.get_parameters, "get_parmeter": self.get_parameters, "get_parma": self.get_parameters, "GetParameter": self.get_parameters, "GetParam": self.get_parameters } if name in method_map: logging.warning(f"动态处理{name}调用 - 可能是拼写错误") return method_map[name] # 关键修复:处理b_frame_received属性 if name == "b_frame_received": logging.warning("动态访问b_frame_received属性 - 提供默认值") return False raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'") def set_param(self, frame_rate=None, exposure_time=None, gain=None): """ 设置相机参数 :param frame_rate: 帧率 (None表示不修改) :param exposure_time: 曝光时间 (None表示不修改) :param gain: 增益 (None表示不修改) :return: 操作结果 """ if not self.b_open_device: logging.error("设备未打开,无法设置参数") return self.MV_E_CALLORDER try: # 使用锁保护参数修改 with self.param_lock: # 禁用自动曝光 ret = self.obj_cam.MV_CC_SetEnumValue("ExposureAuto", 0) if ret != self.MV_OK: logging.warning(f"禁用自动曝光失败: {hex(ret)}") # 设置帧率 if frame_rate is not None: ret = self.obj_cam.MV_CC_SetFloatValue("AcquisitionFrameRate", float(frame_rate)) if ret != self.MV_OK: logging.error(f"设置帧率失败: {hex(ret)}") return ret self.frame_rate = float(frame_rate) # 设置曝光时间 if exposure_time is not None: ret = self.obj_cam.MV_CC_SetFloatValue("ExposureTime", float(exposure_time)) if ret != self.MV_OK: logging.error(f"设置曝光时间失败: {hex(ret)}") return ret self.exposure_time = float(exposure_time) # 设置增益 if gain is not None: ret = self.obj_cam.MV_CC_SetFloatValue("Gain", float(gain)) if ret != self.MV_OK: logging.error(f"设置增益失败: {hex(ret)}") return ret self.gain = float(gain) logging.info(f"参数设置成功: 帧率={self.frame_rate}, 曝光={self.exposure_time}, 增益={self.gain}") return self.MV_OK except Exception as e: logging.exception(f"设置参数异常: {str(e)}") return self.MV_E_STATE def work_thread(self, winHandle=None): """图像采集工作线程""" stOutFrame = MV_FRAME_OUT() memset(byref(stOutFrame), 0, sizeof(stOutFrame)) logging.info("采集线程启动") while not self.b_exit: try: # 获取图像缓冲区 ret = self.obj_cam.MV_CC_GetImageBuffer(stOutFrame, 1000) if ret != self.MV_OK: if ret != self.MV_E_NO_DATA: # 忽略无数据错误 logging.warning(f"获取图像缓冲区失败: {hex(ret)}") time.sleep(0.01) continue # 更新帧信息 self.st_frame_info = stOutFrame.stFrameInfo # 关键修复:标记帧已接收 self.b_frame_received = True # 记录像素格式信息 pixel_format = get_pixel_format_name(self.st_frame_info.enPixelType) logging.debug(f"获取到图像: {self.st_frame_info.nWidth}x{self.st_frame_info.nHeight}, " f"格式: {pixel_format}, 大小: {self.st_frame_info.nFrameLen}字节") # 分配/更新图像缓冲区 frame_size = stOutFrame.stFrameInfo.nFrameLen with self.buf_lock: if self.buf_save_image is None or self.n_save_image_size < frame_size: self.buf_save_image = (c_ubyte * frame_size)() self.n_save_image_size = frame_size # 复制图像数据 cdll.msvcrt.memcpy(byref(self.buf_save_image), stOutFrame.pBufAddr, frame_size) # 更新当前帧 self.update_current_frame() # 显示图像(如果指定了窗口句柄) if winHandle is not None: stDisplayParam = MV_DISPLAY_FRAME_INFO() memset(byref(stDisplayParam), 0, sizeof(stDisplayParam)) stDisplayParam.hWnd = int(winHandle) stDisplayParam.nWidth = self.st_frame_info.nWidth stDisplayParam.nHeight = self.st_frame_info.nHeight stDisplayParam.enPixelType = self.st_frame_info.enPixelType stDisplayParam.pData = self.buf_save_image stDisplayParam.nDataLen = frame_size self.obj_cam.MV_CC_DisplayOneFrame(stDisplayParam) # 释放图像缓冲区 self.obj_cam.MV_CC_FreeImageBuffer(stOutFrame) except Exception as e: logging.exception(f"采集线程异常: {str(e)}") time.sleep(0.1) # 清理资源 with self.buf_lock: if self.buf_save_image is not None: del self.buf_save_image self.buf_save_image = None self.n_save_image_size = 0 logging.info("采集线程退出") def update_current_frame(self): """将原始图像数据转换为OpenCV格式并存储""" if not self.st_frame_info or not self.buf_save_image: logging.warning("更新当前帧时缺少帧信息或缓冲区") return try: # 获取图像信息 width = self.st_frame_info.nWidth height = self.st_frame_info.nHeight pixel_type = self.st_frame_info.enPixelType # 复制缓冲区数据 with self.buf_lock: buffer_copy = bytearray(self.buf_save_image) # 转换为numpy数组 np_buffer = np.frombuffer(buffer_copy, dtype=np.uint8) # 根据像素类型处理图像 frame = None if is_mono_data(pixel_type): # 单色图像 frame = np_buffer.reshape(height, width) elif pixel_type == PIXEL_FORMATS["BAYER_BG8"]: # Bayer BG格式 frame = cv2.cvtColor(np_buffer.reshape(height, width), cv2.COLOR_BayerBG2RGB) elif pixel_type == PIXEL_FORMATS["BAYER_GB8"]: # Bayer GB格式 frame = cv2.cvtColor(np_buffer.reshape(height, width), cv2.COLOR_BayerGB2RGB) elif pixel_type == PIXEL_FORMATS["BAYER_GR8"]: # Bayer GR格式 frame = cv2.cvtColor(np_buffer.reshape(height, width), cv2.COLOR_BayerGR2RGB) elif pixel_type == PIXEL_FORMATS["BAYER_RG8"]: # Bayer RG格式 frame = cv2.cvtColor(np_buffer.reshape(height, width), cv2.COLOR_BayerRG2RGB) elif pixel_type == PIXEL_FORMATS["RGB8"]: # RGB格式 frame = np_buffer.reshape(height, width, 3) elif pixel_type in [PIXEL_FORMATS["YUV422"], PIXEL_FORMATS["YUV422_YUYV"]]: # YUV格式 frame = cv2.cvtColor(np_buffer.reshape(height, width, 2), cv2.COLOR_YUV2RGB_YUYV) else: # 尝试自动处理其他格式 if pixel_type in [PIXEL_FORMATS["MONO10"], PIXEL_FORMATS["MONO12"]]: # 10位或12位单色图像需要特殊处理 frame = self.process_high_bit_depth(np_buffer, width, height, pixel_type) else: logging.warning(f"不支持的像素格式: {get_pixel_format_name(pixel_type)}") return # 更新当前帧 - 使用线程安全锁 with self.frame_lock: self.current_frame = frame logging.debug(f"当前帧更新成功: {frame.shape if frame is not None else '无数据'}") except Exception as e: logging.exception(f"更新当前帧异常: {str(e)}") # 调试:保存原始数据用于分析 try: timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") debug_path = f"frame_debug_{timestamp}.bin" with open(debug_path, "wb") as f: f.write(buffer_copy) logging.info(f"已保存原始帧数据到: {debug_path}") except: logging.error("保存调试帧数据失败") def process_high_bit_depth(self, buffer, width, height, pixel_type): """处理高位深度图像格式""" try: # 10位或12位图像处理 if pixel_type == PIXEL_FORMATS["MONO10"]: # 将10位数据转换为16位 data_16bit = np.frombuffer(buffer, dtype=np.uint16) # 10位数据存储方式:每个像素占用2字节,但只有10位有效 data_16bit = (data_16bit >> 6) # 右移6位使10位数据对齐到低10位 frame = data_16bit.reshape(height, width).astype(np.uint16) elif pixel_type == PIXEL_FORMATS["MONO12"]: # 将12位数据转换为16位 data_16bit = np.frombuffer(buffer, dtype=np.uint16) # 12位数据存储方式:每个像素占用2字节,但只有12位有效 data_16bit = (data_16bit >> 4) # 右移4位使12位数据对齐到低12位 frame = data_16bit.reshape(height, width).astype(np.uint16) else: logging.warning(f"不支持的高位深度格式: {get_pixel_format_name(pixel_type)}") return None # 归一化到8位用于显示(如果需要) frame_8bit = cv2.convertScaleAbs(frame, alpha=(255.0/4095.0)) return frame_8bit except Exception as e: logging.exception(f"处理高位深度图像异常: {str(e)}") return None def get_current_frame(self): """获取当前帧的副本(线程安全)""" with self.frame_lock: if self.current_frame is None: return None # 返回副本以避免外部修改影响内部状态 return self.current_frame.copy() # 在 CameraOperation 类中添加/修改以下方法 def save_image(self, file_path, save_format="bmp", quality=95): """ 安全保存当前帧到文件 - 使用原始缓冲区数据 """ if not self.b_open_device or not self.b_start_grabbing: logging.error("设备未就绪,无法保存图像") return self.MV_E_CALLORDER # 使用缓冲区锁确保数据一致性 with self.buf_lock: if not self.buf_save_image or not self.st_frame_info: logging.error("无可用图像数据") return self.MV_E_NO_DATA # 获取图像信息 width = self.st_frame_info.nWidth height = self.st_frame_info.nHeight pixel_type = self.st_frame_info.enPixelType frame_size = self.st_frame_info.nFrameLen # 复制缓冲区数据 buffer_copy = bytearray(self.buf_save_image) try: # 确保目录存在 directory = os.path.dirname(file_path) if directory and not os.path.exists(directory): os.makedirs(directory, exist_ok=True) logging.info(f"创建目录: {directory}") # 根据像素类型处理图像 np_buffer = np.frombuffer(buffer_copy, dtype=np.uint8) # 根据像素格式转换图像 if is_mono_data(pixel_type): # 单色图像 frame = np_buffer.reshape(height, width) elif pixel_type == PIXEL_FORMATS["BAYER_BG8"]: # Bayer BG格式 frame = cv2.cvtColor(np_buffer.reshape(height, width), cv2.COLOR_BayerBG2BGR) elif pixel_type == PIXEL_FORMATS["BAYER_GB8"]: # Bayer GB格式 frame = cv2.cvtColor(np_buffer.reshape(height, width), cv2.COLOR_BayerGB2BGR) elif pixel_type == PIXEL_FORMATS["BAYER_GR8"]: # Bayer GR格式 frame = cv2.cvtColor(np_buffer.reshape(height, width), cv2.COLOR_BayerGR2BGR) elif pixel_type == PIXEL_FORMATS["BAYER_RG8"]: # Bayer RG格式 frame = cv2.cvtColor(np_buffer.reshape(height, width), cv2.COLOR_BayerRG2BGR) elif pixel_type == PIXEL_FORMATS["RGB8"]: # RGB格式 frame = np_buffer.reshape(height, width, 3) frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR) elif pixel_type in [PIXEL_FORMATS["YUV422"], PIXEL_FORMATS["YUV422_YUYV"]]: # YUV格式 frame = cv2.cvtColor(np_buffer.reshape(height, width, 2), cv2.COLOR_YUV2BGR_YUYV) else: # 尝试自动处理其他格式 if pixel_type in [PIXEL_FORMATS["MONO10"], PIXEL_FORMATS["MONO12"]]: # 10位或12位单色图像需要特殊处理 frame = self.process_high_bit_depth(np_buffer, width, height, pixel_type) else: logging.error(f"不支持的像素格式: {get_pixel_format_name(pixel_type)}") return self.MV_E_PARAMETER # 根据格式保存图像 save_format = save_format.lower() try: if save_format == "bmp": cv2.imwrite(file_path, frame) elif save_format in ["jpg", "jpeg"]: cv2.imwrite(file_path, frame, [cv2.IMWRITE_JPEG_QUALITY, quality]) elif save_format == "png": cv2.imwrite(file_path, frame, [cv2.IMWRITE_PNG_COMPRESSION, 9]) elif save_format in ["tiff", "tif"]: cv2.imwrite(file_path, frame, [cv2.IMWRITE_TIFF_COMPRESSION, 1]) else: logging.error(f"不支持的图像格式: {save_format}") return self.MV_E_PARAMETER # 验证保存结果 if not os.path.exists(file_path): logging.error(f"文件保存失败: {file_path}") return self.MV_E_SAVE_IMAGE file_size = os.path.getsize(file_path) if file_size < 1024: # 小于1KB视为无效 logging.error(f"文件大小异常: {file_path} ({file_size} 字节)") os.remove(file_path) # 删除无效文件 return self.MV_E_SAVE_IMAGE logging.info(f"图像已保存: {file_path} ({file_size} 字节)") return self.MV_OK except Exception as e: logging.exception(f"保存图像异常: {str(e)}") return self.MV_E_SAVE_IMAGE except Exception as e: logging.exception(f"图像处理异常: {str(e)}") return self.MV_E_SAVE_IMAGE # 在 CameraOperation 类中添加/修改以下方法 # 兼容旧方法的保存接口 def save_jpg(self, file_path=None, quality=95): """保存为JPEG格式""" if file_path is None: timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") file_path = f"capture_{timestamp}.jpg" return self.save_image(file_path, "jpg", quality) def save_bmp(self, file_path=None): """保存为BMP格式""" if file_path is None: timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") file_path = f"capture_{timestamp}.bmp" return self.save_image(file_path, "bmp") def save_png(self, file_path=None): """保存为PNG格式""" if file_path is None: timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") file_path = f"capture_{timestamp}.png" return self.save_image(file_path, "png") def save_tiff(self, file_path=None): """保存为TIFF格式""" if file_path is None: timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") file_path = f"capture_{timestamp}.tiff" return self.save_image(file_path, "tiff") # 新增方法:检查帧是否可用 def is_frame_available(self): """检查是否有有效帧可用""" with self.frame_lock: return self.current_frame is not None and self.current_frame.size > 0 # 新增方法:获取帧状态详细信息 def get_frame_status(self): """获取当前帧状态详细信息""" # 安全访问b_frame_received属性 frame_received = getattr(self, 'b_frame_received', False) status = { "camera_open": self.b_open_device, "grabbing_started": self.b_start_grabbing, "thread_running": self.b_thread_running, "frame_received": frame_received, # 使用安全访问 "frame_size": self.n_save_image_size if self.buf_save_image else 0, "current_frame": self.current_frame is not None } if self.st_frame_info: status.update({ "width": self.st_frame_info.nWidth, "height": self.st_frame_info.nHeight, "pixel_format": get_pixel_format_name(self.st_frame_info.enPixelType), "frame_num": self.st_frame_info.nFrameNum }) return status 这是camoperatto_class.py目前的完整代码在不改变原本已有功能的前提下,把你刚刚提出的改进方案完整展示出来

最新推荐

recommend-type

boh5_hmdp_for_learn_redis_by_fastapi_36224_1754229591966.zip

boh5_hmdp_for_learn_redis_by_fastapi_36224_1754229591966.zip
recommend-type

19年国赛服务器答案深度解析:网络搭建与应用

网络搭建与应用是一门涉及计算机网络规划、配置、管理和维护的技术学科。在19年的国家竞赛中,参与者需要展示他们对网络架构、网络设备、协议、安全等方面的知识,以及他们在真实世界问题解决中的实际应用能力。在网络搭建与应用19国赛服务器答案中,涉及的知识点可能包括但不限于以下几个方面: 1. 网络基础知识 - 了解网络的基本概念,包括网络的定义、分类(如LAN、WAN等)、网络的功能和网络协议栈(如TCP/IP模型)。 - 理解网络设备的功能和作用,例如交换机、路由器、防火墙等。 - 掌握网络通信的基本原理,包括数据链路层、网络层、传输层和应用层的协议和功能。 2. 网络设计与规划 - 学习如何根据不同的需求设计网络拓扑结构,例如星形、环形、总线型等。 - 掌握IP地址规划和子网划分的方法,如CIDR、VLSM等技术。 - 了解如何进行网络流量分析和带宽规划,以确保网络性能和稳定性。 3. 网络设备配置与管理 - 掌握交换机和路由器的配置命令,例如VLAN划分、路由协议配置、端口安全等。 - 理解网络设备的管理和维护策略,包括日志管理、性能监控和故障诊断。 4. 网络安全 - 学习网络安全的基本原则,包括数据加密、访问控制、入侵检测系统(IDS)和入侵防御系统(IPS)。 - 掌握常见的网络攻击手段及其防御措施,例如DDoS攻击、ARP欺骗、病毒和恶意软件的防御。 5. 服务器搭建与应用 - 了解不同类型的服务器和它们的应用场景,如Web服务器、数据库服务器、邮件服务器等。 - 学习服务器的安装、配置和管理方法,包括操作系统的安装、服务软件的部署、用户管理等。 6. 实践操作 - 通过搭建真实或虚拟的网络环境来实践理论知识,包括使用网络模拟软件(如GNS3、Packet Tracer等)进行网络设备配置和故障排除。 - 学习如何准备和参加网络相关的竞赛,包括时间管理和应对突发问题的策略。 在给定的压缩包子文件的文件名称列表中,“19年国赛服务器的答案”表明该文件包含具体的竞赛解答步骤和方法。文件可能涉及的是如何根据具体的网络搭建与应用的题目,一步一步地提供解题策略、配置命令和执行步骤等。具体内容可能包括: - 对竞赛题目需求的分析和理解。 - 对应的网络设计解决方案和实现步骤。 - 关键的配置命令和参数设置。 - 对于各种网络功能和安全性的测试方法。 - 可能遇到的问题及其解决方案。 综上所述,对于网络搭建与应用19国赛服务器答案的深入学习和掌握,能够帮助专业人士和学生扩展网络知识,提高解决复杂网络问题的能力,并为将来的IT行业工作奠定扎实的基础。通过针对竞赛题目的实际操作演练,还能增强个人的实践技能和创新思维能力。
recommend-type

【VS2010模块化秘籍】:提升项目管理效率的10个技巧

# 1. VS2010模块化编程概述 在现代软件开发中,模块化编程已经成为提高代码质量和促进团队协作的关键技术之一。本章将介绍在Visual Studio 2010(VS2010)环境中如何理解和实施模块化编程。 ## 1.1 什么是模块化编程? 模块化编程是一种组织程序结构的方法,将程序分解为独立且可管理的模块,每个模块实现一个特定的功能。在V
recommend-type

数据分析师发展前景

<think>嗯,用户现在想了解数据分析师的职业发展和未来前景。根据之前的对话,用户是土木本科想转行,之前我建议过数据分析作为可能的方向之一,现在他可能想更深入了解这个领域的潜力。 首先,我需要参考之前提供的引用内容。引用1提到了数据分析师的职业路径,从专员到专家,还有技能提升的重要性。引用2和3强调了行业需求增长和技能的必要性,引用4则讨论了成为行业专家的长期发展优势。这些都需要整合到回答中。 用户的问题集中在职业前景和趋势,所以我要覆盖市场需求、职业阶段、技能要求、行业趋势和转行建议。考虑到用户是转行者,需要突出土木背景如何与数据分析结合,比如提到的BIM、GIS或者工程数据分析,这样
recommend-type

Elasticsearch及IK分词器安装包资源汇总

标题中提到的知识点包括Elasticsearch安装包和IK分词器,这是进行搜索引擎搭建和数据文本分析的重要组件。Elasticsearch是一个基于Lucene构建的开源搜索引擎,具有水平可伸缩性、高可用性和易用性的特点。它提供了全文搜索功能,同时支持结构化搜索和分析,常被用于大数据分析场景中。 描述中涉及的版本信息表明了所附的安装包和分词器支持不同版本的Elasticsearch。Elasticsearch版本6.x和7.x分别对应了两个主要的版本线,而IK分词器是专门为Elasticsearch设计的中文分词插件。 IK分词器是一款支持中文分词的扩展插件,可以根据中文语境进行智能分词,包括正向匹配、正向最大匹配和逆向最大匹配等算法,对中文文本进行处理。分词器的版本通常会与Elasticsearch的版本相匹配,以保证兼容性和最佳性能。 提到的logstash是与Elasticsearch配合使用的数据处理管道工具,负责收集、处理和转发数据。logstash可以作为事件的中介来处理各种来源的数据,然后将其发送到Elasticsearch进行存储。本压缩包中的logstash-6.4.3.tar.gz对应的版本表明了它的兼容性,适用于Elasticsearch 6.x版本。 压缩包文件名称列表中的文件包含了不同软件的多个版本。其中,“elasticsearch-head-master.zip”是一个可以对Elasticsearch进行可视化管理的Chrome插件,它提供了包括集群管理、索引管理、数据操作和查询在内的功能。 另外,“mysql-connector-java-5.1.41.jar”是一个MySQL数据库的Java驱动程序,用于连接Java应用程序和MySQL数据库,但这似乎与Elasticsearch及IK分词器直接关联不大,可能是一个辅助组件,用于在某些集成场景下将数据从MySQL迁移到Elasticsearch。 从标签内容来看,Elasticsearch被归类于源码软件、大数据和搜索引擎类别。它是一个重要的大数据处理组件,特别是在全文搜索和文本分析领域。在大数据背景下,Elasticsearch凭借其卓越的搜索和分析能力,已经成为企业构建和维护搜索引擎的首选技术之一。 总结来说,本次提供的压缩包包含了多个关键组件,它们共同支持构建一个功能强大的搜索引擎和数据分析平台。Elasticsearch自身及其配套的IK分词器、logstash和可视化插件elasticsearch-head,均对大数据和搜索领域有着重要意义。尽管这些工具具有复杂性,但它们的组合使用使得数据的索引、搜索、可视化和分析变得简单、快速和强大。
recommend-type

从零开始:Axure插件开发入门指南,构建自定义Chrome工具

# 摘要 随着原型设计工具Axure RP的广泛应用,定制化插件开发变得日益重要。本文旨在为开发者提供一个完整的Axure插件开发指南,从基础概念到环境搭建,再到核心编程和界面定制,最终实现交互逻辑与发布维护。通过详细解析插件的API、JavaScript编程、数据管理、界面设计及发布流程,本文帮助开发者深入理解并掌握Axure插件开发的关键技术,确保开发过程的高效性和插件的稳定运行。 # 关键字 Axur
recommend-type

代码错误,修改代码

<think>好的,用户说代码有错误,需要修改。首先我得仔细看看之前的代码哪里有问题。题目是关于彩灯的操作和查询,每个彩灯有一个周期k_i,每次操作区间加1,查询时判断当前按动次数是否为k_i的倍数。 首先,用户提供的代码使用了树状数组(Fenwick Tree)来维护差分数组,实现区间加和单点查询。但可能存在一些问题。比如,树状数组的差分处理是否正确? 在区间更新时,原代码是add(l, 1)和add(r+1, -1),这应该是正确的差分方法。当查询单点x时,sum(x)得到的是从1到x的累计值,也就是该点的实际操作次数。这部分逻辑看起来没问题。 但可能的问题在于,当k_i的值很大时,
recommend-type

筹资风险分析模板:Excel高效风险评估工具

Excel模板筹资风险分析.zip是一个用于财务风险分析的工具包,它可能包含了一个名为“筹资风险分析.xlsx”的Excel文件,这个文件被压缩在ZIP格式的压缩包中。下面将详细说明这个Excel模板中可能包含的知识点: 1. 筹资风险概念: 筹资风险指的是企业在筹资过程中由于各种不确定因素的影响,使得企业实际获得的筹资成本高于预期成本,或者筹资方式、筹资渠道未能达到预期目的,从而对企业财务状况和经营成果产生不利影响的可能性。筹资风险可以来源于金融市场波动、债务利率上升、企业信用评级下降等因素。 2. Excel在财务分析中的应用: Excel作为一个强大的电子表格软件,广泛应用于各种财务数据分析和管理中。它具备数据处理、图表制作、公式计算等功能,非常适合用来制作财务模型、进行预算编制、风险分析等任务。筹资风险分析中,Excel可以帮助用户进行敏感性分析、情景模拟和概率分析等。 3. 筹资风险分析的关键要素: - 资本结构:分析企业的债务与权益比例,评估不同筹资方式对资本结构的影响。 - 债务成本:估算企业债务的利率和偿还期限,考虑利率风险和偿债压力。 - 股权成本:计算股权筹资的期望回报率,评估股权稀释的影响。 - 流动性风险:考虑筹资后的资金流动性,确保企业运营资金的充足性。 - 筹资成本:计算不同筹资方式的综合成本,比较各种筹资渠道的经济性。 4. Excel模板筹资风险分析.xlsx可能包含的功能: - 数据录入区:用于输入企业的财务数据和筹资相关的具体参数。 - 计算引擎:使用Excel公式和函数来计算筹资成本、预期回报率等关键指标。 - 情景分析表:通过调整不同的变量,模拟出不同的筹资情景,分析其对企业财务状况的影响。 - 敏感性分析:评估筹资参数变动对企业风险和回报的影响程度。 - 图表展示:将分析结果以图表的形式展现出来,比如使用条形图、折线图和饼图等,直观展示风险和回报的对比。 - 结论和建议:根据分析结果提供筹资策略的优化建议。 5. 筹资风险分析的实施步骤: - 明确分析目标:确定分析筹资风险的目的和需要关注的关键点。 - 收集数据:搜集相关的市场数据、企业财务报表、筹资计划等。 - 构建模型:在Excel中根据筹资风险分析的理论框架构建分析模型。 - 输入参数:将收集到的数据输入到Excel模型中。 - 运行分析:利用Excel的数据处理能力,执行必要的计算和分析。 - 解读结果:分析输出结果,并据此解读筹资风险水平。 - 制定策略:基于分析结果,提出筹资策略和风险控制措施。 6. 筹资风险分析的应用场景: 筹资风险分析不仅可以用于企业自身的筹资决策过程中,还可以在投资评估、财务咨询、风险管理和战略规划等领域发挥作用。在企业层面,它可以辅助管理层和财务部门制定更为稳健和有效的资金筹集计划;在咨询领域,可以为投资者提供分析企业的筹资活动和风险状况的专业意见;在学术研究中,筹资风险分析是研究企业资本结构和企业价值的重要工具。 7. 筹资风险分析的局限性: 尽管Excel模板筹资风险分析提供了有力的工具,但也存在局限性。模型依赖于准确的数据输入,如果假设或数据有误,将影响分析结果的可靠性。此外,市场环境的变化、政策的调整以及其他不可预测的因素都可能对筹资风险造成影响,这些在模型中可能难以全面考虑。 通过使用Excel模板筹资风险分析.zip内的筹资风险分析.xlsx文件,企业可以更有效地进行筹资风险管理,制定出更合理的筹资策略,从而降低财务风险,提高企业的整体价值。
recommend-type

【Z460_Z560 BIOS升级终极指南】:29CN41WW版本升级,性能提升,故障排除

# 摘要 本文探讨了BIOS升级的必要性、益处以及相关风险和解决策略。首先,概述了BIOS的基础概念和版本更新的重要性,接着详细解读了特定笔记本型号Z460/Z560的BIOS架构和升级步骤。文章进一步分析了BIOS升级对于笔记本性能提升的影响,并提供了详细的故障诊断和排除方法。最后,通过分享实际升级案例,总结了BIOS升级的最佳实践和专业建议。本文旨在帮助技术用户深入理解BIOS升级的过程及
recommend-type

lenet论文

<think>首先,用户查询是:“我想查找LeNet论文相关资料 请问LeNet论文原文及技术解析”。这看起来像是一个新查询,因为系统指令提到“请尽可能多的参考用户上一次的问题和你的回答”,但在这个上下文中,没有提供用户上一次的问题或我的回答。所以,我应该基于当前查询和提供的引用内容来回答。 系统指令包括: - 所有行内数学表达式必须使用$...$格式。 - 独立公式使用$$...$$格式并单独成段。 - LaTeX语法正确。 - 使用中文回答。 - 生成相关问题。 - 在回答中引用的段落末尾自然地添加引用标识,如[^1]。 - 回答结构清晰,帮助用户解决问题。 - 参考站内引用:有四个引用