typedef struct {
#if EI_CLASSIFIER_OBJECT_DETECTION == 1
ei_impulse_result_bounding_box_t *bounding_boxes;
uint32_t bounding_boxes_count;
#else
ei_impulse_result_classification_t classification[EI_CLASSIFIER_LABEL_COUNT];
#endif
float anomaly;
ei_impulse_result_timing_t timing;
} ei_impulse_result_t;
Brief: Holds the output of inference, anomaly results, and timing information.
Location: edge-impulse-sdk/classifier/ei_classifier_types.h
Description:
ei_impulse_result_t holds the output of run_classifier(). If object detection is enabled (e.g. EI_CLASSIFIER_OBJECT_DETECTION == 1), then the output results is a pointer to an array of bounding boxes of size bounding_boxes_count, as given by ei_impulse_result_bounding_box_t. Otherwise, results are stored as an array of classification scores, as given by ei_impulse_result_classification_t.
If anomaly detection is enabled (e.g. EI_CLASSIFIER_HAS_ANOMALY == 1), then the anomaly score will be stored as a floating point value in anomaly.
Timing information is stored in an ei_impulse_result_timing_t struct.
Members:
bounding_boxes[]- Array of bounding boxes, if object detection is enabled.classification[]- Array of classification scores (if object detection is not enabled)anomaly- A higher anomaly score indicates greater likelihood of an anomalous sample (e.g. it is farther away from its cluster).timing- Information about the time it took to execute sampling, preprocessing (DSP), and inference.
Example:
https://github.com/edgeimpulse/example-standalone-inferencing/blob/master/source/main.cpp