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Fully working OPI5 and Azaion AI object recognition
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#include <QDebug>
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#include <QThread>
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#include <opencv2/imgproc.hpp>
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#include <opencv2/highgui.hpp>
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#include <iomanip>
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#include "aiengineinferenceopi5.h"
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AiEngineInferenceOpi5::AiEngineInferenceOpi5(QString modelPath, QObject *parent)
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: AiEngineInference{modelPath, parent}
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{
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qDebug() << "AiEngineInferenceOpi5() test mModelPath=" << mModelPath;
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memset(&mRrknnAppCtx, 0, sizeof(rknn_app_context_t));
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init_post_process();
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int ret = init_yolov8_model(modelPath.toLocal8Bit(), &mRrknnAppCtx);
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if (ret != 0) {
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qDebug() << "init_yolov8_model() failure! ret: " << ret << "modelPath = " << modelPath;
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return;
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}
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}
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AiEngineInferenceOpi5::~AiEngineInferenceOpi5()
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{
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deinit_post_process();
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release_yolov8_model(&mRrknnAppCtx);
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}
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image_buffer_t convertCV2FrameToImageBuffer(const cv::Mat& bgrFrame)
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{
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// Convert BGR to RGB
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cv::Mat rgbFrame;
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cv::cvtColor(bgrFrame, rgbFrame, cv::COLOR_BGR2RGB);
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image_buffer_t imgBuffer;
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memset(&imgBuffer, 0, sizeof(image_buffer_t));
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imgBuffer.width = rgbFrame.cols;
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imgBuffer.height = rgbFrame.rows;
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imgBuffer.width_stride = rgbFrame.step;
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imgBuffer.height_stride = rgbFrame.rows;
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imgBuffer.format = IMAGE_FORMAT_RGB888;
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imgBuffer.size = rgbFrame.total() * rgbFrame.elemSize();
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imgBuffer.virt_addr = new unsigned char[imgBuffer.size];
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std::memcpy(imgBuffer.virt_addr, rgbFrame.data, imgBuffer.size);
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return imgBuffer;
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}
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void freeImageBuffer(image_buffer_t& imgBuffer)
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{
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if (imgBuffer.virt_addr) {
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delete[] imgBuffer.virt_addr;
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imgBuffer.virt_addr = nullptr;
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}
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}
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cv::Mat resizeAndCenterImage(const cv::Mat& src, int targetWidth, int targetHeight)
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{
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// Calculate the scaling factor and size
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int originalWidth = src.cols;
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int originalHeight = src.rows;
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double aspectRatio = static_cast<double>(originalWidth) / originalHeight;
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int newWidth, newHeight;
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if (originalWidth > originalHeight) {
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newWidth = targetWidth;
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newHeight = static_cast<int>(targetWidth / aspectRatio);
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}
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else {
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newHeight = targetHeight;
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newWidth = static_cast<int>(targetHeight * aspectRatio);
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}
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// Resize the image
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cv::Mat resizedImage;
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cv::resize(src, resizedImage, cv::Size(newWidth, newHeight));
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// Create a black image of target size
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cv::Mat outputImage = cv::Mat::zeros(targetHeight, targetWidth, src.type());
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// Calculate position to center the image
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int top = (targetHeight - newHeight) / 2;
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int left = (targetWidth - newWidth) / 2;
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// Copy resized image into the center of the black image
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resizedImage.copyTo(outputImage(cv::Rect(left, top, newWidth, newHeight)));
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return outputImage;
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}
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void drawObjects(cv::Mat& image, const object_detect_result_list& result_list) {
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for (int i = 0; i < result_list.count; i++) {
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const object_detect_result& result = result_list.results[i];
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int left = result.box.left;
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int top = result.box.top;
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int right = result.box.right;
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int bottom = result.box.bottom;
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cv::rectangle(image, cv::Point(left, top), cv::Point(right, bottom), cv::Scalar(255, 0, 0), 2);
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fprintf(stderr, "TUOMAS OMA. ID=%d String=%s\n", result.cls_id, coco_cls_to_name(result.cls_id));
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// Text
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char c_text[256];
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sprintf(c_text, "%s %.1f%%", coco_cls_to_name(result.cls_id), result.prop * 100);
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cv::Point textOrg(left, top - 5);
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cv::putText(image, std::string(c_text), textOrg, cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 255), 1);
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}
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}
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void AiEngineInferenceOpi5::performInferenceSlot(cv::Mat frame)
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{
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qDebug() << "performInferenceSlot() in thread: " << QThread::currentThreadId();
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mActive = true;
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cv::Mat scaledFrame = resizeAndCenterImage(frame, 640, 640);
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image_buffer_t imgBuffer = convertCV2FrameToImageBuffer(scaledFrame);
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object_detect_result_list od_results;
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int ret = inference_yolov8_model(&mRrknnAppCtx, &imgBuffer, &od_results);
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if (ret != 0) {
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qDebug() << "inference_yolov8_model() failure! ret: " << ret;
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}
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for (int i = 0; i < od_results.count; i++) {
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object_detect_result *det_result = &(od_results.results[i]);
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fprintf(stderr, "TUOMAS RKNN. ID=%d String=%s\n", det_result->cls_id, coco_cls_to_name(det_result->cls_id));
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}
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/*
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char text[256];
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for (int i = 0; i < od_results.count; i++) {
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object_detect_result *det_result = &(od_results.results[i]);
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printf("%s @ (%d %d %d %d) %.3f\n", coco_cls_to_name(det_result->cls_id),
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det_result->box.left, det_result->box.top,
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det_result->box.right, det_result->box.bottom,
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det_result->prop);
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int x1 = det_result->box.left;
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int y1 = det_result->box.top;
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int x2 = det_result->box.right;
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int y2 = det_result->box.bottom;
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draw_rectangle(&imgBuffer, x1, y1, x2 - x1, y2 - y1, COLOR_BLUE, 3);
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sprintf(text, "%s %.1f%%", coco_cls_to_name(det_result->cls_id), det_result->prop * 100);
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draw_text(&imgBuffer, text, x1, y1 - 20, COLOR_RED, 10);
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}
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*/
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// Testing
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//write_image(filename.c_str(), &imgBuffer);
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drawObjects(scaledFrame, od_results);
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freeImageBuffer(imgBuffer);
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/*
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static int imageNum = 0;
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std::stringstream ss;
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ss << std::setw(4) << std::setfill('0') << imageNum++;
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std::string formatted_number = ss.str();
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std::string filename = "/tmp/out-" + formatted_number + ".png";
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cv::imwrite(filename, scaledFrame);
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*/
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AiEngineInferenceResult result;
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result.frame = scaledFrame.clone();
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result.objects = od_results.count;
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emit resultsReady(result);
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mActive = false;
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}
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@@ -0,0 +1,22 @@
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#pragma once
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#include <QObject>
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#include "aiengineinference.h"
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#include "yolov8.h"
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#include "image_utils.h"
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#include "file_utils.h"
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#include "image_drawing.h"
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class AiEngineInferenceOpi5 : public AiEngineInference
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{
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Q_OBJECT
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public:
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explicit AiEngineInferenceOpi5(QString modelPath, QObject *parent = nullptr);
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~AiEngineInferenceOpi5();
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public slots:
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void performInferenceSlot(cv::Mat frame) override;
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private:
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rknn_app_context_t mRrknnAppCtx;
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};
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@@ -23,7 +23,13 @@
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#include <set>
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#include <vector>
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#define LABEL_NALE_TXT_PATH "./model/coco_80_labels_list.txt"
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#ifdef OPI5_BUILD
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#define LABEL_NALE_TXT_PATH "azaion_10_labels_list.txt"
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#else
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#define LABEL_NALE_TXT_PATH "coco_80_labels_list.txt"
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#endif
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static char *labels[OBJ_CLASS_NUM];
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