-
Notifications
You must be signed in to change notification settings - Fork 2
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
Showing
17 changed files
with
507 additions
and
16 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,157 @@ | ||
| #include <chrono> | ||
| #include <iostream> | ||
|
|
||
| // Includes common necessary includes for development using depthai library | ||
| #include "depthai/depthai.hpp" | ||
|
|
||
| /* | ||
| The code is the same as for Tiny-yolo-V3 and V4, the only difference is the blob file and anchors that are not needed for V8. | ||
| The blob was compiled following this tutorial: https://github.com/TNTWEN/OpenVINO-YOLOV4 | ||
| */ | ||
|
|
||
| static const std::vector<std::string> labelMap = { | ||
| "person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat", | ||
| "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", | ||
| "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella", "handbag", | ||
| "tie", "suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat", "baseball glove", | ||
| "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup", "fork", "knife", "spoon", | ||
| "bowl", "banana", "apple", "sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza", | ||
| "donut", "cake", "chair", "sofa", "pottedplant", "bed", "diningtable", "toilet", "tvmonitor", | ||
| "laptop", "mouse", "remote", "keyboard", "cell phone", "microwave", "oven", "toaster", "sink", | ||
| "refrigerator", "book", "clock", "vase", "scissors", "teddy bear", "hair drier", "toothbrush"}; | ||
|
|
||
| static std::atomic<bool> syncNN{true}; | ||
|
|
||
| int main(int argc, char** argv) { | ||
| using namespace std; | ||
| using namespace std::chrono; | ||
| 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<dai::node::ColorCamera>(); | ||
| auto detectionNetwork = pipeline.create<dai::node::YoloDetectionNetwork>(); | ||
| auto xoutRgb = pipeline.create<dai::node::XLinkOut>(); | ||
| auto nnOut = pipeline.create<dai::node::XLinkOut>(); | ||
|
|
||
| xoutRgb->setStreamName("rgb"); | ||
| nnOut->setStreamName("detections"); | ||
|
|
||
| // Properties | ||
| camRgb->setPreviewSize(640, 352); | ||
| camRgb->setResolution(dai::ColorCameraProperties::SensorResolution::THE_1080_P); | ||
| camRgb->setInterleaved(false); | ||
| camRgb->setColorOrder(dai::ColorCameraProperties::ColorOrder::BGR); | ||
| camRgb->setFps(40); | ||
|
|
||
| // Network specific settings | ||
| detectionNetwork->setConfidenceThreshold(0.5f); | ||
| detectionNetwork->setNumClasses(80); | ||
| detectionNetwork->setCoordinateSize(4); | ||
| detectionNetwork->setIouThreshold(0.5f); | ||
| detectionNetwork->setBlobPath(nnPath); | ||
| detectionNetwork->setNumInferenceThreads(2); | ||
| detectionNetwork->input.setBlocking(false); | ||
|
|
||
| // Linking | ||
| camRgb->preview.link(detectionNetwork->input); | ||
| if(syncNN) { | ||
| detectionNetwork->passthrough.link(xoutRgb->input); | ||
| } else { | ||
| camRgb->preview.link(xoutRgb->input); | ||
| } | ||
|
|
||
| detectionNetwork->out.link(nnOut->input); | ||
|
|
||
| // Connect to device and start pipeline | ||
| dai::Device device(pipeline); | ||
|
|
||
| // Output queues will be used to get the rgb frames and nn data from the outputs defined above | ||
| auto qRgb = device.getOutputQueue("rgb", 4, false); | ||
| auto qDet = device.getOutputQueue("detections", 4, false); | ||
|
|
||
| cv::Mat frame; | ||
| std::vector<dai::ImgDetection> detections; | ||
| auto startTime = steady_clock::now(); | ||
| int counter = 0; | ||
| float fps = 0; | ||
| auto color2 = cv::Scalar(255, 255, 255); | ||
|
|
||
| // Add bounding boxes and text to the frame and show it to the user | ||
| auto displayFrame = [](std::string name, cv::Mat frame, std::vector<dai::ImgDetection>& 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, 255); | ||
| 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, 255); | ||
| 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); | ||
| }; | ||
|
|
||
| while(true) { | ||
| std::shared_ptr<dai::ImgFrame> inRgb; | ||
| std::shared_ptr<dai::ImgDetections> inDet; | ||
|
|
||
| if(syncNN) { | ||
| inRgb = qRgb->get<dai::ImgFrame>(); | ||
| inDet = qDet->get<dai::ImgDetections>(); | ||
| } else { | ||
| inRgb = qRgb->tryGet<dai::ImgFrame>(); | ||
| inDet = qDet->tryGet<dai::ImgDetections>(); | ||
| } | ||
|
|
||
| counter++; | ||
| auto currentTime = steady_clock::now(); | ||
| auto elapsed = duration_cast<duration<float>>(currentTime - startTime); | ||
| if(elapsed > seconds(1)) { | ||
| fps = counter / elapsed.count(); | ||
| counter = 0; | ||
| startTime = currentTime; | ||
| } | ||
|
|
||
| if(inRgb) { | ||
| frame = inRgb->getCvFrame(); | ||
| std::stringstream fpsStr; | ||
| fpsStr << "NN fps: " << std::fixed << std::setprecision(2) << fps; | ||
| cv::putText(frame, fpsStr.str(), cv::Point(2, inRgb->getHeight() - 4), cv::FONT_HERSHEY_TRIPLEX, 0.4, color2); | ||
| } | ||
|
|
||
| if(inDet) { | ||
| detections = inDet->detections; | ||
| } | ||
|
|
||
| if(!frame.empty()) { | ||
| displayFrame("rgb", frame, detections); | ||
| } | ||
|
|
||
| int key = cv::waitKey(1); | ||
| if(key == 'q' || key == 'Q') { | ||
| return 0; | ||
| } | ||
| } | ||
| return 0; | ||
| } |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,6 +1,6 @@ | ||
| <package format="3"> | ||
| <name>depthai</name> | ||
| <version>2.28.0</version> | ||
| <version>2.29.0</version> | ||
| <description>DepthAI core is a C++ library which comes with firmware and an API to interact with OAK Platform</description> | ||
|
|
||
| <maintainer email="[email protected]">Adam Serafin</maintainer> | ||
|
|
||
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Oops, something went wrong.