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Morning everybody
I am working on an object detection since 2 weeks.i have started the project by a testing object using edge impulse to creat the library based on this object but when i compile the code i have an error
That's the code:
#include <final_inferencing.h> #include "edge-impulse-sdk/dsp/image/image.hpp" #include "esp_camera.h" //#define CAMERA_MODEL_ESP_EYE // Has PSRAM #define CAMERA_MODEL_AI_THINKER // Has PSRAM #if defined(CAMERA_MODEL_ESP_EYE) #define PWDN_GPIO_NUM -1 #define RESET_GPIO_NUM -1 #define XCLK_GPIO_NUM 4 #define SIOD_GPIO_NUM 18 #define SIOC_GPIO_NUM 23 #define Y9_GPIO_NUM 36 #define Y8_GPIO_NUM 37 #define Y7_GPIO_NUM 38 #define Y6_GPIO_NUM 39 #define Y5_GPIO_NUM 35 #define Y4_GPIO_NUM 14 #define Y3_GPIO_NUM 13 #define Y2_GPIO_NUM 34 #define VSYNC_GPIO_NUM 5 #define HREF_GPIO_NUM 27 #define PCLK_GPIO_NUM 25 #elif defined(CAMERA_MODEL_AI_THINKER) #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 #else #error "Camera model not selected" #endif #define EI_CAMERA_RAW_FRAME_BUFFER_COLS 320 #define EI_CAMERA_RAW_FRAME_BUFFER_ROWS 240 #define EI_CAMERA_FRAME_BYTE_SIZE 3 static bool debug_nn = false; static bool is_initialised = false; uint8_t *snapshot_buf; 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 = 20000000, .ledc_timer = LEDC_TIMER_0, .ledc_channel = LEDC_CHANNEL_0, .pixel_format = PIXFORMAT_JPEG, .frame_size = FRAMESIZE_QVGA, .jpeg_quality = 12, .fb_count = 1, .fb_location = CAMERA_FB_IN_PSRAM, .grab_mode = CAMERA_GRAB_WHEN_EMPTY, }; bool ei_camera_init(void); void ei_camera_deinit(void); bool ei_camera_capture(uint32_t img_width, uint32_t img_height, uint8_t *out_buf) ; void setup() { Serial.begin(115200); while (!Serial); Serial.println("Edge Impulse Inferencing Demo"); if (ei_camera_init() == false) { ei_printf("Failed to initialize Camera!\r\n"); } else { ei_printf("Camera initialized\r\n"); } ei_printf("\nStarting continious inference in 2 seconds...\n"); ei_sleep(2000); } void loop() { if (ei_sleep(5) != EI_IMPULSE_OK) { return; } snapshot_buf = (uint8_t*)malloc(EI_CAMERA_RAW_FRAME_BUFFER_COLS * EI_CAMERA_RAW_FRAME_BUFFER_ROWS * EI_CAMERA_FRAME_BYTE_SIZE); if(snapshot_buf == nullptr) { ei_printf("ERR: Failed to allocate snapshot buffer!\n"); return; } ei::signal_t signal; signal.total_length = EI_CLASSIFIER_INPUT_WIDTH * EI_CLASSIFIER_INPUT_HEIGHT; signal.get_data = &ei_camera_get_data; if (ei_camera_capture((size_t)EI_CLASSIFIER_INPUT_WIDTH, (size_t)EI_CLASSIFIER_INPUT_HEIGHT, snapshot_buf) == false) { ei_printf("Failed to capture image\r\n"); free(snapshot_buf); return; } ei_impulse_result_t result = { 0 }; EI_IMPULSE_ERROR err = run_classifier(&signal, &result, debug_nn); if (err != EI_IMPULSE_OK) { ei_printf("ERR: Failed to run classifier (%d)\n", err); return; } ei_printf("Predictions (DSP: %d ms., Classification: %d ms., Anomaly: %d ms.): \n", result.timing.dsp, result.timing.classification, result.timing.anomaly); #if EI_CLASSIFIER_OBJECT_DETECTION == 1 bool bb_found = result.bounding_boxes[0].value > 0; for (size_t ix = 0; ix < result.bounding_boxes_count; ix++) { auto bb = result.bounding_boxes[ix]; if (bb.value == 0) { continue; } ei_printf(" %s (%f) [ x: %u, y: %u, width: %u, height: %u ]\n", bb.label, bb.value, bb.x, bb.y, bb.width, bb.height); } if (!bb_found) { ei_printf(" No objects found\n"); } #else for (size_t ix = 0; ix < EI_CLASSIFIER_LABEL_COUNT; ix++) { ei_printf(" %s: %.5f\n", result.classification[ix].label, result.classification[ix].value); } #endif #if EI_CLASSIFIER_HAS_ANOMALY == 1 ei_printf(" anomaly score: %.3f\n", result.anomaly); #endif free(snapshot_buf); } /** * @brief Setup image sensor & start streaming * * @retval false if initialisation failed */ bool ei_camera_init(void) { if (is_initialised) return true; #if defined(CAMERA_MODEL_ESP_EYE) pinMode(13, INPUT_PULLUP); pinMode(14, INPUT_PULLUP); #endif esp_err_t err = esp_camera_init(&camera_config); if (err != ESP_OK) { Serial.printf("Camera init failed with error 0x%x\n", err); return false; } sensor_t * s = esp_camera_sensor_get(); if (s->id.PID == OV3660_PID) { s->set_vflip(s, 1); // flip it back s->set_brightness(s, 1); // up the brightness just a bit s->set_saturation(s, 0); // lower the saturation } #if defined(CAMERA_MODEL_M5STACK_WIDE) s->set_vflip(s, 1); s->set_hmirror(s, 1); #elif defined(CAMERA_MODEL_ESP_EYE) s->set_vflip(s, 1); s->set_hmirror(s, 1); s->set_awb_gain(s, 1); #endif is_initialised = true; return true; } void ei_camera_deinit(void) { //deinitialize the camera esp_err_t err = esp_camera_deinit(); if (err != ESP_OK) { ei_printf("Camera deinit failed\n"); return; } is_initialised = false; return; } bool ei_camera_capture(uint32_t img_width, uint32_t img_height, uint8_t *out_buf) { bool do_resize = false; if (!is_initialised) { ei_printf("ERR: Camera is not initialized\r\n"); return false; } camera_fb_t *fb = esp_camera_fb_get(); if (!fb) { ei_printf("Camera capture failed\n"); return false; } bool converted = fmt2rgb888(fb->buf, fb->len, PIXFORMAT_JPEG, snapshot_buf); esp_camera_fb_return(fb); if(!converted){ ei_printf("Conversion failed\n"); return false; } if ((img_width != EI_CAMERA_RAW_FRAME_BUFFER_COLS) || (img_height != EI_CAMERA_RAW_FRAME_BUFFER_ROWS)) { do_resize = true; } if (do_resize) { 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; } static int ei_camera_get_data(size_t offset, size_t length, float *out_ptr) { // we already have a RGB888 buffer, so recalculate offset into pixel index 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; } #if !defined(EI_CLASSIFIER_SENSOR) || EI_CLASSIFIER_SENSOR != EI_CLASSIFIER_SENSOR_CAMERA #error "Invalid model for current sensor" #endif end that is the error: fork/exec C:\Users\NGALEU JNR\AppData\Local\Arduino15\packages\esp32\tools\xtensa-esp32-elf-gcc\esp-2021r2-patch5-8.4.0/bin/xtensa-esp32-elf-g++.exe: Nom de fichier ou extension trop long. Erreur de compilation pour la carte AI Thinker ESP32-CAM
please i need help to fix it
thanks

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Hi @sanal143, Welcome to the MakerGram community .

Does your training data contain noise data similar to the data you are inferencing? and May I know, what kind of hardware you are using to run the model. Thanks

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