# 去畸变相机流 本示例展示了如何使用 [Camera](https://docs.luxonis.com/software-v3/depthai/depthai-components/nodes/camera.md) 节点对宽视场相机流进行去畸变。去畸变不是自动的；它是按输出通过 requestOutput(..., enableUndistortion=True) (或 requestFullResolutionOutput) 启用。任何请求的输出都可以通过此方式去畸变。 注意： * 去畸变不会更改存储的相机内参，也没有公开的“alpha”或等效参数来调整去畸变裁剪。 * 去畸变确实会改变有效视场角；根据您请求的输出大小和调整模式，去畸变后您可能会看到更小的视场角。 ## 演示 这个示例需要DepthAI v3 API，参见[安装说明](https://docs.luxonis.com/software-v3/depthai.md)。 ## 流程 ### examples/camera_undistort.pipeline.json ```json { "pipeline": { "connections": [ { "node1Id": 0, "node1Output": "video", "node1OutputGroup": "", "node2Id": 1, "node2Input": "in", "node2InputGroup": "" }, { "node1Id": 0, "node1Output": "isp", "node1OutputGroup": "", "node2Id": 2, "node2Input": "in", "node2InputGroup": "" } ], "globalProperties": { "calibData": null, "cameraTuningBlobSize": null, "cameraTuningBlobUri": "", "leonCssFrequencyHz": 700000000.0, "leonMssFrequencyHz": 700000000.0, "pipelineName": null, "pipelineVersion": null, "sippBufferSize": 18432, "sippDmaBufferSize": 16384, "xlinkChunkSize": -1 }, "nodes": [ [ 0, { "id": 0, "ioInfo": [ [ [ "", "inputConfig" ], { "blocking": false, "group": "", "id": 1, "name": "inputConfig", "queueSize": 8, "type": 3, "waitForMessage": false } ], [ [ "", "raw" ], { "blocking": false, "group": "", "id": 6, "name": "raw", "queueSize": 8, "type": 0, "waitForMessage": false } ], [ [ "", "still" ], { "blocking": false, "group": "", "id": 7, "name": "still", "queueSize": 8, "type": 0, "waitForMessage": false } ], [ [ "", "inputControl" ], { "blocking": true, "group": "", "id": 2, "name": "inputControl", "queueSize": 8, "type": 3, "waitForMessage": false } ], [ [ "", "video" ], { "blocking": false, "group": "", "id": 3, "name": "video", "queueSize": 8, "type": 0, "waitForMessage": false } ], [ [ "", "isp" ], { "blocking": false, "group": "", "id": 4, "name": "isp", "queueSize": 8, "type": 0, "waitForMessage": false } ], [ [ "", "preview" ], { "blocking": false, "group": "", "id": 5, "name": "preview", "queueSize": 8, "type": 0, "waitForMessage": false } ], [ [ "", "frameEvent" ], { "blocking": false, "group": "", "id": 8, "name": "frameEvent", "queueSize": 8, "type": 0, "waitForMessage": false } ] ], "name": "Camera", "properties": { "boardSocket": 0, "calibAlpha": null, "cameraName": "", "colorOrder": 0, "fp16": false, "fps": 30.0, "imageOrientation": -1, "initialControl": { "aeLockMode": false, "aeMaxExposureTimeUs": 0, "aeRegion": { "height": 0, "priority": 0, "width": 0, "x": 0, "y": 0 }, "afRegion": { "height": 0, "priority": 0, "width": 0, "x": 0, "y": 0 }, "antiBandingMode": 0, "autoFocusMode": 3, "awbLockMode": false, "awbMode": 0, "brightness": 0, "captureIntent": 0, "chromaDenoise": 0, "cmdMask": 0, "contrast": 0, "controlMode": 0, "effectMode": 0, "expCompensation": 0, "expManual": { "exposureTimeUs": 0, "frameDurationUs": 0, "sensitivityIso": 0 }, "frameSyncMode": 0, "lensPosAutoInfinity": 0, "lensPosAutoMacro": 0, "lensPosition": 0, "lensPositionRaw": 0.0, "lowPowerNumFramesBurst": 0, "lowPowerNumFramesDiscard": 0, "lumaDenoise": 0, "saturation": 0, "sceneMode": 0, "sharpness": 0, "strobeConfig": { "activeLevel": 0, "enable": 0, "gpioNumber": 0 }, "strobeTimings": { "durationUs": 0, "exposureBeginOffsetUs": 0, "exposureEndOffsetUs": 0 }, "wbColorTemp": 0 }, "interleaved": true, "isp3aFps": 0, "ispScale": { "horizDenominator": 0, "horizNumerator": 0, "vertDenominator": 0, "vertNumerator": 0 }, "numFramesPoolIsp": 3, "numFramesPoolPreview": 4, "numFramesPoolRaw": 3, "numFramesPoolStill": 4, "numFramesPoolVideo": 4, "previewHeight": 300, "previewKeepAspectRatio": true, "previewWidth": 300, "rawPacked": null, "resolutionHeight": 800, "resolutionWidth": 1280, "sensorCropX": -1.0, "sensorCropY": -1.0, "sensorType": -1, "stillHeight": -1, "stillWidth": -1, "videoHeight": -1, "videoWidth": -1, "warpMeshHeight": 0, "warpMeshSource": -1, "warpMeshStepHeight": 32, "warpMeshStepWidth": 32, "warpMeshUri": "", "warpMeshWidth": 0 } } ], [ 1, { "id": 1, "ioInfo": [ [ [ "", "in" ], { "blocking": true, "group": "", "id": 9, "name": "in", "queueSize": 8, "type": 3, "waitForMessage": true } ] ], "name": "XLinkOut", "properties": { "maxFpsLimit": -1.0, "metadataOnly": false, "streamName": "video" } } ], [ 2, { "id": 2, "ioInfo": [ [ [ "", "in" ], { "blocking": true, "group": "", "id": 10, "name": "in", "queueSize": 8, "type": 3, "waitForMessage": true } ] ], "name": "XLinkOut", "properties": { "maxFpsLimit": -1.0, "metadataOnly": false, "streamName": "isp" } } ] ] } } ``` ## 源代码 #### Python ```python #!/usr/bin/env python3 import cv2 import depthai as dai # Create pipeline with dai.Pipeline() as pipeline: # Define source and output cam = pipeline.create(dai.node.Camera).build(dai.CameraBoardSocket.CAM_B) croppedQueue = cam.requestOutput((300,300), resizeMode=dai.ImgResizeMode.CROP, enableUndistortion=True).createOutputQueue() stretchedQueue = cam.requestOutput((300,300), resizeMode=dai.ImgResizeMode.STRETCH, enableUndistortion=True).createOutputQueue() letterBoxedQueue = cam.requestOutput((300,300), resizeMode=dai.ImgResizeMode.LETTERBOX, enableUndistortion=True).createOutputQueue() # Connect to device and start pipeline pipeline.start() while pipeline.isRunning(): croppedIn = croppedQueue.get() assert isinstance(croppedIn, dai.ImgFrame) cv2.imshow("cropped undistorted", croppedIn.getCvFrame()) stretchedIn = stretchedQueue.get() assert isinstance(stretchedIn, dai.ImgFrame) cv2.imshow("stretched undistorted", stretchedIn.getCvFrame()) letterBoxedIn = letterBoxedQueue.get() assert isinstance(letterBoxedIn, dai.ImgFrame) cv2.imshow("letterboxed undistorted", letterBoxedIn.getCvFrame()) if cv2.waitKey(1) == ord("q"): break ``` #### C++ ```cpp #include #include #include #include #include #include #include "depthai/depthai.hpp" // Global flag for graceful shutdown std::atomic quitEvent(false); // Signal handler void signalHandler(int signum) { quitEvent = true; } int main() { // Set up signal handlers signal(SIGTERM, signalHandler); signal(SIGINT, signalHandler); try { // Create pipeline dai::Pipeline pipeline; // Define source and outputs auto cam = pipeline.create(); cam->build(dai::CameraBoardSocket::CAM_B, std::nullopt, 30); // Create output queues with different resize modes auto croppedQueue = cam->requestOutput(std::make_pair(300, 300), dai::ImgFrame::Type::NV12, dai::ImgResizeMode::CROP, 20, 20)->createOutputQueue(); auto stretchedQueue = cam->requestOutput(std::make_pair(300, 300), dai::ImgFrame::Type::NV12, dai::ImgResizeMode::STRETCH, 20, 20)->createOutputQueue(); auto letterBoxedQueue = cam->requestOutput(std::make_pair(300, 300), dai::ImgFrame::Type::NV12, dai::ImgResizeMode::LETTERBOX, 20, 20)->createOutputQueue(); // Start pipeline pipeline.start(); // Main loop while(pipeline.isRunning() && !quitEvent) { // Get and show cropped undistorted frame auto croppedIn = croppedQueue->get(); cv::imshow("cropped undistorted", croppedIn->getCvFrame()); // Get and show stretched undistorted frame auto stretchedIn = stretchedQueue->get(); cv::imshow("stretched undistorted", stretchedIn->getCvFrame()); // Get and show letterboxed undistorted frame auto letterBoxedIn = letterBoxedQueue->get(); cv::imshow("letterboxed undistorted", letterBoxedIn->getCvFrame()); // Check for quit key if(cv::waitKey(1) == 'q') { break; } } // Cleanup pipeline.stop(); pipeline.wait(); } catch(const std::exception& e) { std::cerr << "Error: " << e.what() << std::endl; return 1; } return 0; } ``` ### 需要帮助？ 请前往 [OAKChina 官网](https://www.oakchina.cn/) 获取技术支持或解答您的任何疑问。