Question/Issue:
Hi,
I am facing issues with the edge impulse devloped object detection model, which I am running on esp32 cam module. I have trained the model with 2 animal’s, labled as “Tiger and Elephant”.
Now as I have generate the Arduino library and putted it inside the IDE. In the library itself, there is a example folder from which I took the “esp_camera example”. I am also putting the example below, kindly check. For further details about the errors please check “Summery” section below.
//Edge Impulse Arduino examples
// These sketches are tested with 2.0.4 ESP32 Arduino Core
// https://github.com/espressif/arduino-esp32/releases/tag/2.0.4
/* Includes ---------------------------------------------------------------- */
#include <EliTrg_detect_inferencing.h>
#include "edge-impulse-sdk/dsp/image/image.hpp"
#include "esp_camera.h"
// Select camera model - find more camera models in camera_pins.h file here
// https://github.com/espressif/arduino-esp32/blob/master/libraries/ESP32/examples/Camera/CameraWebServer/camera_pins.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
/* Constant defines -------------------------------------------------------- */
#define EI_CAMERA_RAW_FRAME_BUFFER_COLS 320
#define EI_CAMERA_RAW_FRAME_BUFFER_ROWS 240
#define EI_CAMERA_FRAME_BYTE_SIZE 3
/* Private variables ------------------------------------------------------- */
static bool debug_nn = false; // Set this to true to see e.g. features generated from the raw signal
static bool is_initialised = false;
uint8_t *snapshot_buf; //points to the output of the capture
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 20MHz or 10MHz for OV2640 double FPS (Experimental)
.xclk_freq_hz = 20000000,
.ledc_timer = LEDC_TIMER_0,
.ledc_channel = LEDC_CHANNEL_0,
.pixel_format = PIXFORMAT_JPEG, //YUV422,GRAYSCALE,RGB565,JPEG
.frame_size = FRAMESIZE_QVGA, //QQVGA-UXGA Do not use sizes above QVGA when not JPEG
.jpeg_quality = 12, //0-63 lower number means higher quality
.fb_count = 1, //if more than one, i2s runs in continuous mode. Use only with JPEG
.fb_location = CAMERA_FB_IN_PSRAM,
.grab_mode = CAMERA_GRAB_WHEN_EMPTY,
};
/* Function definitions ------------------------------------------------------- */
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) ;
/**
* @brief Arduino setup function
*/
void setup()
{
// put your setup code here, to run once:
Serial.begin(115200);
//comment out the below line to start inference immediately after upload
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);
}
/**
* @brief Get data and run inferencing
*
* @param[in] debug Get debug info if true
*/
void loop()
{
// instead of wait_ms, we'll wait on the signal, this allows threads to cancel us...
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);
// check if allocation was successful
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;
}
// Run the classifier
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;
}
// print the predictions
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
ei_printf("Object detection bounding boxes:\r\n");
for (uint32_t i = 0; i < result.bounding_boxes_count; i++) {
ei_impulse_result_bounding_box_t bb = result.bounding_boxes[i];
if (bb.value == 0) {
continue;
}
ei_printf(" %s (%f) [ x: %u, y: %u, width: %u, height: %u ]\r\n",
bb.label,
bb.value,
bb.x,
bb.y,
bb.width,
bb.height);
}
// Print the prediction results (classification)
#else
ei_printf("Predictions:\r\n");
for (uint16_t i = 0; i < EI_CLASSIFIER_LABEL_COUNT; i++) {
ei_printf(" %s: ", ei_classifier_inferencing_categories[i]);
ei_printf("%.5f\r\n", result.classification[i].value);
}
#endif
// Print anomaly result (if it exists)
#if EI_CLASSIFIER_HAS_ANOMALY
ei_printf("Anomaly prediction: %.3f\r\n", result.anomaly);
#endif
#if EI_CLASSIFIER_HAS_VISUAL_ANOMALY
ei_printf("Visual anomalies:\r\n");
for (uint32_t i = 0; i < result.visual_ad_count; i++) {
ei_impulse_result_bounding_box_t bb = result.visual_ad_grid_cells[i];
if (bb.value == 0) {
continue;
}
ei_printf(" %s (%f) [ x: %u, y: %u, width: %u, height: %u ]\r\n",
bb.label,
bb.value,
bb.x,
bb.y,
bb.width,
bb.height);
}
#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
//initialize the camera
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();
// initial sensors are flipped vertically and colors are a bit saturated
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;
}
/**
* @brief Stop streaming of sensor data
*/
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;
}
/**
* @brief Capture, rescale and crop image
*
* @param[in] img_width width of output image
* @param[in] img_height height of output image
* @param[in] out_buf pointer to store output image, NULL may be used
* if ei_camera_frame_buffer is to be used for capture and resize/cropping.
*
* @retval false if not initialised, image captured, rescaled or cropped failed
*
*/
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) {
// Swap BGR to RGB here
// due to https://github.com/espressif/esp32-camera/issues/379
out_ptr[out_ptr_ix] = (snapshot_buf[pixel_ix + 2] << 16) + (snapshot_buf[pixel_ix + 1] << 8) + snapshot_buf[pixel_ix];
// go to the next pixel
out_ptr_ix++;
pixel_ix+=3;
pixels_left--;
}
// and done!
return 0;
}
#if !defined(EI_CLASSIFIER_SENSOR) || EI_CLASSIFIER_SENSOR != EI_CLASSIFIER_SENSOR_CAMERA
#error "Invalid model for current sensor"
#endif
Project ID:
657062
Context/Use case:
I am trying to build a project to integrate PIR, sleep mode with AI on ESP32 CAM module, to reduce battery usage and extend the battery life.
Summary:
Now about the issue, I am continuously getting the below given errors on the serial monitor.
17:09:33.284 -> Predictions (DSP: 14 ms., Classification: 2291 ms., Anomaly: 0 ms.):
17:09:33.284 -> Object detection bounding boxes:17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 192, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 192, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 32, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 192, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 192, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 192, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 192, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 32, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 32, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 192, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 192, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 192, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 192, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 32, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 32, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 192, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 192, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 128, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 128, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 12, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:33.687 -> ERR: Failed to allocate persistent buffer of size 12, does not fit in tensor arena and reached EI_MAX_OVERFLOW_BUFFER_COUNT
17:09:35.702 -> Predictions (DSP: 14 ms., Classification: 2291 ms., Anomaly: 0 ms.):
17:09:35.702 -> Object detection bounding boxes:
As you can see in the log above the issue is with “tensor arena”, so I checked the files and tried changing what all is understandable to me, But nothing seems to work. I even tried directly defining it in the main code, given above, but that also didn’t worked.
Expected Results:
Print the lables of the objects detected in the serial monitor
Actual Results:
Errors in memory allocation with tensor arena.
Environment:
- Platform: [ESP 32 CAM module (CAMERA_MODEL_AI_THINKER).
- Build Environment Details: Arduino IDE 2.3.6
- OS Version: Windows 10 and 11
Logs/Attachments:
I have given all the required details in the above section.
Additional Information:
Kindly guide me with this as I have tried with all the knowldege I have. This is the first time I am using edge impules so if I am doing any minor mistake, kindly let me know.
Thank you.