edge lab LIVE! starts Tuesday in Munich. Grab a workshop seat and take home the board you build on. Code FRIEND-HACKSTER saves 20%. () Learn more!
Whitney Knitter
Published © GPL3+

Importing Edge Impulse C++ Library into Vitis Workspace

This project walks through how to import a C++ library of an Edge Impulse ML model to develop accelerated applications for AMD FPGAs.

AdvancedWork in progress2 hours1,132
Importing Edge Impulse C++ Library into Vitis Workspace

Things used in this project

Software apps and online services

AMD Vitis Unified Software Platform
Edge Impulse Studio
Edge Impulse Studio
OpenCV
OpenCV

Story

Read more

Code

main.cpp

C/C++
#define OCL_CHECK(error, call)                                                                   \
    call;                                                                                        \
    if (error != CL_SUCCESS) {                                                                   \
        printf("%s:%d Error calling " #call ", error code is: %d\n", __FILE__, __LINE__, error); \
        exit(EXIT_FAILURE);                                                                      \
    }

#include "vadd.h"
#include <stdio.h>
#include <fstream>
#include <iostream>
#include <stdlib.h>
#include "opencv2/opencv.hpp"
#include "edge-impulse-sdk/classifier/ei_run_classifier.h"

static const int DATA_SIZE = 4096;

static const std::string error_message =
    "Error: Result mismatch:\n"
    "i = %d CPU result = %d Device result = %d\n";

// Callback function declaration
static int get_signal_data(size_t offset, size_t length, float *out_ptr);

// Raw features copied from test sample (Edge Impulse > Model testing)
static float input_buf[] = {
    /* Paste your raw features here! */ 
};

int main(int argc, char **argv) {
    
    signal_t signal;            // Wrapper for raw input buffer
    ei_impulse_result_t result; // Used to store inference output
    EI_IMPULSE_ERROR res;       // Return code from inference

    // Calculate the length of the buffer
    size_t buf_len = sizeof(input_buf) / sizeof(input_buf[0]);

    // Make sure that the length of the buffer matches expected input length
    if (buf_len != EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE) {
        printf("ERROR: The size of the input buffer is not correct.\r\n");
        printf("Expected %d items, but got %d\r\n", 
                EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE, 
                (int)buf_len);
        return 1;
    }

    // Assign callback function to fill buffer used for preprocessing/inference
    signal.total_length = EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE;
    signal.get_data = &get_signal_data;

    // Perform DSP pre-processing and inference
    res = run_classifier(&signal, &result, false);

    // Print return code and how long it took to perform inference
    printf("run_classifier returned: %d\r\n", res);
    printf("Timing: DSP %d ms, inference %d ms, anomaly %d ms\r\n", 
            result.timing.dsp, 
            result.timing.classification, 
            result.timing.anomaly);

    // Print the prediction results (object detection)
#if EI_CLASSIFIER_OBJECT_DETECTION == 1
    printf("Object detection bounding boxes:\r\n");
    for (uint32_t i = 0; i < EI_CLASSIFIER_OBJECT_DETECTION_COUNT; i++) {
        ei_impulse_result_bounding_box_t bb = result.bounding_boxes[i];
        if (bb.value == 0) {
            continue;
        }
        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
    printf("Predictions:\r\n");
    for (uint16_t i = 0; i < EI_CLASSIFIER_LABEL_COUNT; i++) {
        printf("  %s: ", ei_classifier_inferencing_categories[i]);
        printf("%.5f\r\n", result.classification[i].value);
    }
#endif

    // Print anomaly result (if it exists)
#if EI_CLASSIFIER_HAS_ANOMALY == 1
    printf("Anomaly prediction: %.3f\r\n", result.anomaly);
#endif

    return 0;
}




// Callback: fill a section of the out_ptr buffer when requested
static int get_signal_data(size_t offset, size_t length, float *out_ptr) {
    for (size_t i = 0; i < length; i++) {
        out_ptr[i] = (input_buf + offset)[i];
    }

    return EIDSP_OK;
}

Credits

Whitney Knitter
181 projects • 2070 followers
All thoughts/opinions are my own and do not reflect those of any company/entity I currently/previously associate with.

Comments

Related channels and tags
  • AI & Machine Learning
  • AI & Machine Learning
  • AMD
  • Edge Impulse
  • FPGAs
  • FPGAs
  • OpenCV