#include // Includes common necessary includes for development using depthai library #include "depthai/depthai.hpp" // MobilenetSSD label texts static const std::vector labelMap = {"background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow", "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor"}; int main(int argc, char** argv) { using namespace std; // Default blob path provided by Hunter private data download // Applicable for easier example usage only std::string nnPath(BLOB_PATH); // If path to blob specified, use that if(argc > 1) { nnPath = std::string(argv[1]); } // Print which blob we are using printf("Using blob at path: %s\n", nnPath.c_str()); // Create pipeline dai::Pipeline pipeline; // Define sources and outputs auto camRgb = pipeline.create(); auto videoEncoder = pipeline.create(); auto nn = pipeline.create(); auto xoutRgb = pipeline.create(); auto videoOut = pipeline.create(); auto nnOut = pipeline.create(); xoutRgb->setStreamName("rgb"); videoOut->setStreamName("h265"); nnOut->setStreamName("nn"); // Properties camRgb->setBoardSocket(dai::CameraBoardSocket::CAM_A); camRgb->setResolution(dai::ColorCameraProperties::SensorResolution::THE_1080_P); camRgb->setPreviewSize(300, 300); camRgb->setInterleaved(false); videoEncoder->setDefaultProfilePreset(30, dai::VideoEncoderProperties::Profile::H265_MAIN); nn->setConfidenceThreshold(0.5); nn->setBlobPath(nnPath); nn->setNumInferenceThreads(2); nn->input.setBlocking(false); // Linking camRgb->video.link(videoEncoder->input); camRgb->preview.link(xoutRgb->input); camRgb->preview.link(nn->input); videoEncoder->bitstream.link(videoOut->input); nn->out.link(nnOut->input); // Connect to device and start pipeline dai::Device device(pipeline); // Queues int queueSize = 8; auto qRgb = device.getOutputQueue("rgb", queueSize); auto qDet = device.getOutputQueue("nn", queueSize); auto qRgbEnc = device.getOutputQueue("h265", 30, true); cv::Mat frame; std::vector detections; // Add bounding boxes and text to the frame and show it to the user auto displayFrame = [](std::string name, cv::Mat frame, std::vector& detections) { auto color = cv::Scalar(255, 0, 0); // nn data, being the bounding box locations, are in <0..1> range - they need to be normalized with frame width/height for(auto& detection : detections) { int x1 = detection.xmin * frame.cols; int y1 = detection.ymin * frame.rows; int x2 = detection.xmax * frame.cols; int y2 = detection.ymax * frame.rows; uint32_t labelIndex = detection.label; std::string labelStr = to_string(labelIndex); if(labelIndex < labelMap.size()) { labelStr = labelMap[labelIndex]; } cv::putText(frame, labelStr, cv::Point(x1 + 10, y1 + 20), cv::FONT_HERSHEY_TRIPLEX, 0.5, color); std::stringstream confStr; confStr << std::fixed << std::setprecision(2) << detection.confidence * 100; cv::putText(frame, confStr.str(), cv::Point(x1 + 10, y1 + 40), cv::FONT_HERSHEY_TRIPLEX, 0.5, color); cv::rectangle(frame, cv::Rect(cv::Point(x1, y1), cv::Point(x2, y2)), color, cv::FONT_HERSHEY_SIMPLEX); } // Show the frame cv::imshow(name, frame); }; auto videoFile = std::ofstream("video.h264", std::ios::binary); while(true) { auto inRgb = qRgb->tryGet(); auto inDet = qDet->tryGet(); auto out = qRgbEnc->get(); videoFile.write((char*)out->getData().data(), out->getData().size()); if(inRgb) { frame = inRgb->getCvFrame(); } if(inDet) { detections = inDet->detections; } if(!frame.empty()) { displayFrame("rgb", frame, detections); } int key = cv::waitKey(1); if(key == 'q' || key == 'Q') { break; } } cout << "To view the encoded data, convert the stream file (.h265) into a video file (.mp4), using a command below:" << endl; cout << "ffmpeg -framerate 30 -i video.h264 -c copy video.mp4" << endl; return 0; }