# AprilTags from camera (12MP) Utilizes the [AprilTag](https://docs.luxonis.com/software-v3/depthai/depthai-components/nodes/april_tag.md) node to detect apriltag markers on the camera stream at 12MP. It outlines detected tags and their IDs on the screen. To preserve bandwidth, instead of streaming 12MP video stream to the host computer, the example uses [ImageManip](https://docs.luxonis.com/software-v3/depthai/depthai-components/nodes/image_manip.md) to downscale 12MP frames to 1332x1000 (3x smaller) before sending it to the host computer. ## Demo This example requires the DepthAI v3 API, see [installation instructions](https://docs.luxonis.com/software-v3/depthai.md). ## Pipeline ### examples/april_tags_12mp.pipeline.json ```json {"pipeline": {"connections": [{"node1Id": 2, "node1Output": "out", "node1OutputGroup": "", "node2Id": 5, "node2Input": "in", "node2InputGroup": ""}, {"node1Id": 0, "node1Output": "0", "node1OutputGroup": "dynamicOutputs", "node2Id": 3, "node2Input": "in", "node2InputGroup": ""}, {"node1Id": 0, "node1Output": "0", "node1OutputGroup": "dynamicOutputs", "node2Id": 2, "node2Input": "inputImage", "node2InputGroup": ""}], "globalProperties": {"calibData": null, "cameraTuningBlobSize": null, "cameraTuningBlobUri": "", "leonCssFrequencyHz": 700000000.0, "leonMssFrequencyHz": 700000000.0, "pipelineName": null, "pipelineVersion": null, "sippBufferSize": 18432, "sippDmaBufferSize": 16384, "xlinkChunkSize": -1}, "nodes": [[5, {"alias": "", "id": 5, "ioInfo": [[["", "in"], {"blocking": true, "group": "", "id": 8, "name": "in", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "XLinkOut", "parentId": -1, "properties": {"maxFpsLimit": -1.0, "metadataOnly": false, "streamName": "__x_2_out"}}], [3, {"alias": "", "id": 3, "ioInfo": [[["", "in"], {"blocking": true, "group": "", "id": 7, "name": "in", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "XLinkOut", "parentId": -1, "properties": {"maxFpsLimit": -1.0, "metadataOnly": false, "streamName": "__x_0_dynamicOutputs_0"}}], [2, {"alias": "", "id": 2, "ioInfo": [[["", "out"], {"blocking": false, "group": "", "id": 6, "name": "out", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "inputImage"], {"blocking": true, "group": "", "id": 5, "name": "inputImage", "queueSize": 3, "type": 3, "waitForMessage": false}], [["", "inputConfig"], {"blocking": true, "group": "", "id": 4, "name": "inputConfig", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "ImageManip", "parentId": -1, "properties": {"backend": 0, "initialConfig": {"base": {"background": 0, "backgroundB": 0, "backgroundG": 0, "backgroundR": 0, "center": true, "colormap": 0, "operations": [], "outputHeight": 1000, "outputWidth": 1332, "resizeMode": 1, "undistort": false}, "outputFrameType": 33, "reusePreviousImage": false, "skipCurrentImage": false}, "numFramesPool": 4, "outputFrameSize": 2162688, "performanceMode": 0}}], [0, {"alias": "", "id": 0, "ioInfo": [[["dynamicOutputs", "0"], {"blocking": false, "group": "dynamicOutputs", "id": 3, "name": "0", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "raw"], {"blocking": false, "group": "", "id": 2, "name": "raw", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "mockIsp"], {"blocking": true, "group": "", "id": 1, "name": "mockIsp", "queueSize": 8, "type": 3, "waitForMessage": false}], [["", "inputControl"], {"blocking": true, "group": "", "id": 0, "name": "inputControl", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "Camera", "parentId": -1, "properties": {"boardSocket": 0, "cameraName": "", "fps": -1.0, "imageOrientation": -1, "initialControl": {"aeLockMode": false, "aeMaxExposureTimeUs": 65544, "aeRegion": {"height": 0, "priority": 0, "width": 0, "x": 0, "y": 0}, "afRegion": {"height": 43, "priority": 131077, "width": 12, "x": 0, "y": 0}, "antiBandingMode": 0, "autoFocusMode": 3, "awbLockMode": false, "awbMode": 0, "brightness": 0, "captureIntent": 0, "chromaDenoise": 136, "cmdMask": 0, "contrast": -116, "controlMode": 12, "effectMode": 0, "enableHdr": false, "expCompensation": 0, "expManual": {"exposureTimeUs": 0, "frameDurationUs": 0, "sensitivityIso": 0}, "frameSyncMode": 6, "lensPosAutoInfinity": 0, "lensPosAutoMacro": 0, "lensPosition": 0, "lensPositionRaw": 0.0, "lowPowerNumFramesBurst": 1, "lowPowerNumFramesDiscard": 0, "lumaDenoise": 0, "miscControls": [], "saturation": 0, "sceneMode": 0, "sharpness": 2, "strobeConfig": {"activeLevel": 110, "enable": 0, "gpioNumber": 111}, "strobeTimings": {"durationUs": 2949132, "exposureBeginOffsetUs": 6649189, "exposureEndOffsetUs": 1704760}, "wbColorTemp": 1}, "isp3aFps": 0, "mockIspHeight": -1, "mockIspWidth": -1, "numFramesPoolIsp": 3, "numFramesPoolPreview": 4, "numFramesPoolRaw": 3, "numFramesPoolStill": 4, "numFramesPoolVideo": 4, "outputRequests": [{"enableUndistortion": null, "fps": {"value": null}, "resizeMode": 0, "size": {"value": {"index": 0, "value": [4000, 3000]}}, "type": null}], "resolutionHeight": -1, "resolutionWidth": -1}}]]}} ``` ## Source code #### Python ```python #!/usr/bin/env python3 import cv2 import depthai as dai import time FULL_RES = (4000, 3000) # 12MP PREVIEW_SIZE = (1332, 1000) # 1/3 of 12MP, to preserve bandwidth with dai.Pipeline() as pipeline: hostCamera = pipeline.create(dai.node.Camera).build() aprilTagNode = pipeline.create(dai.node.AprilTag) outputCam = hostCamera.requestOutput(FULL_RES) outputCam.link(aprilTagNode.inputImage) outQueue = aprilTagNode.out.createOutputQueue() # We use ImageManip instead of creating a new smaller output because of the syncing, # ATM, AprilTags don't contain timestamps, so we can't sync them with frames manip = pipeline.create(dai.node.ImageManip) manip.initialConfig.setOutputSize(PREVIEW_SIZE[0], PREVIEW_SIZE[1], dai.ImageManipConfig.ResizeMode.STRETCH) manip.setMaxOutputFrameSize(2162688) outputCam.link(manip.inputImage) frameQ = manip.out.createOutputQueue() color = (0, 255, 0) startTime = time.monotonic() counter = 0 fps = 0.0 pipeline.start() while pipeline.isRunning(): aprilTagMessage = outQueue.get() assert(isinstance(aprilTagMessage, dai.AprilTags)) aprilTags = aprilTagMessage.aprilTags counter += 1 currentTime = time.monotonic() if (currentTime - startTime) > 1: fps = counter / (currentTime - startTime) counter = 0 startTime = currentTime def rescale(p: dai.Point2f): return (int(p.x / FULL_RES[0] * PREVIEW_SIZE[0]), int(p.y / FULL_RES[1] * PREVIEW_SIZE[1])) passthroughImage: dai.ImgFrame = frameQ.get() frame = passthroughImage.getCvFrame() for tag in aprilTags: topLeft = rescale(tag.topLeft) topRight = rescale(tag.topRight) bottomRight = rescale(tag.bottomRight) bottomLeft = rescale(tag.bottomLeft) center = (int((topLeft[0] + bottomRight[0]) / 2), int((topLeft[1] + bottomRight[1]) / 2)) cv2.line(frame, topLeft, topRight, color, 2, cv2.LINE_AA, 0) cv2.line(frame, topRight,bottomRight, color, 2, cv2.LINE_AA, 0) cv2.line(frame, bottomRight,bottomLeft, color, 2, cv2.LINE_AA, 0) cv2.line(frame, bottomLeft,topLeft, color, 2, cv2.LINE_AA, 0) idStr = "ID: " + str(tag.id) cv2.putText(frame, idStr, center, cv2.FONT_HERSHEY_TRIPLEX, 0.5, color) cv2.putText(frame, f"fps: {fps:.1f}", (200, 20), cv2.FONT_HERSHEY_TRIPLEX, 1, color) cv2.imshow("detections", frame) if cv2.waitKey(1) == ord("q"): break ``` #### C++ ```cpp #include #include #include #include #include #include #include "depthai/depthai.hpp" std::atomic quitEvent(false); void signalHandler(int) { quitEvent = true; } int main() { signal(SIGTERM, signalHandler); signal(SIGINT, signalHandler); // Create device std::shared_ptr device = std::make_shared(); // Create pipeline dai::Pipeline pipeline(device); // Constants const cv::Size FULL_RES(4000, 3000); // 12MP const cv::Size PREVIEW_SIZE(1332, 1000); // 1/3 of 12MP // Create nodes auto hostCamera = pipeline.create()->build(); auto aprilTagNode = pipeline.create(); auto manip = pipeline.create(); // Configure nodes auto outputCam = hostCamera->requestOutput(std::make_pair(FULL_RES.width, FULL_RES.height)); outputCam->link(aprilTagNode->inputImage); // Configure ImageManip manip->initialConfig->setOutputSize(PREVIEW_SIZE.width, PREVIEW_SIZE.height, dai::ImageManipConfig::ResizeMode::STRETCH); manip->setMaxOutputFrameSize(2162688); outputCam->link(manip->inputImage); // Create output queues auto outQueue = aprilTagNode->out.createOutputQueue(); auto frameQ = manip->out.createOutputQueue(); // Start pipeline pipeline.start(); // Variables for FPS calculation auto startTime = std::chrono::steady_clock::now(); int counter = 0; float fps = 0.0f; const cv::Scalar color(0, 255, 0); while(pipeline.isRunning() && !quitEvent) { auto aprilTagMessage = outQueue->get(); if(aprilTagMessage == nullptr) continue; // FPS calculation counter++; auto currentTime = std::chrono::steady_clock::now(); auto elapsed = std::chrono::duration_cast(currentTime - startTime).count(); if(elapsed > 1000) { fps = counter * 1000.0f / elapsed; counter = 0; startTime = currentTime; } // Helper function to rescale points auto rescale = [&FULL_RES, &PREVIEW_SIZE](const dai::Point2f& p) { return cv::Point(static_cast(p.x / FULL_RES.width * PREVIEW_SIZE.width), static_cast(p.y / FULL_RES.height * PREVIEW_SIZE.height)); }; auto frame = frameQ->get(); if(frame == nullptr) continue; cv::Mat cvFrame = frame->getCvFrame(); for(const auto& tag : aprilTagMessage->aprilTags) { auto topLeft = rescale(tag.topLeft); auto topRight = rescale(tag.topRight); auto bottomRight = rescale(tag.bottomRight); auto bottomLeft = rescale(tag.bottomLeft); cv::Point center((topLeft.x + bottomRight.x) / 2, (topLeft.y + bottomRight.y) / 2); // Draw tag boundaries cv::line(cvFrame, topLeft, topRight, color, 2, cv::LINE_AA, 0); cv::line(cvFrame, topRight, bottomRight, color, 2, cv::LINE_AA, 0); cv::line(cvFrame, bottomRight, bottomLeft, color, 2, cv::LINE_AA, 0); cv::line(cvFrame, bottomLeft, topLeft, color, 2, cv::LINE_AA, 0); // Draw tag ID std::string idStr = "ID: " + std::to_string(tag.id); cv::putText(cvFrame, idStr, center, cv::FONT_HERSHEY_TRIPLEX, 0.5, color); // Draw FPS cv::putText(cvFrame, "fps: " + std::to_string(fps).substr(0, 4), cv::Point(200, 20), cv::FONT_HERSHEY_TRIPLEX, 1, color); } cv::imshow("detections", cvFrame); if(cv::waitKey(1) == 'q') { break; } } pipeline.stop(); pipeline.wait(); return 0; } ``` ### Need assistance? 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