# Spatial location calculator This example shows how to retrieve spatial location data (X,Y,Z) on a runtime configurable ROI. You can move the ROI using WASD keys. X,Y,Z coordinates are relative to the center of depth map. You can also calculate spatial coordinates on host side, [demo here](https://github.com/luxonis/oak-examples/tree/master/gen2-calc-spatials-on-host). ### Similar samples: * [Spatial object tracker on RGB](https://docs.luxonis.com/software/depthai/examples/spatial_object_tracker.md) * [RGB & MobilenetSSD with spatial data](https://docs.luxonis.com/software/depthai/examples/spatial_mobilenet.md) * [Mono & MobilenetSSD with spatial data](https://docs.luxonis.com/software/depthai/examples/spatial_mobilenet_mono.md) * [RGB & TinyYolo with spatial data](https://docs.luxonis.com/software/depthai/examples/spatial_tiny_yolo.md) ## Demo ## Setup Please run the [install script](https://github.com/luxonis/depthai-python/blob/main/examples/install_requirements.py) to download all required dependencies. Please note that this script must be ran from git context, so you have to download the [depthai-python](https://github.com/luxonis/depthai-python) repository first and then run the script ```bash git clone https://github.com/luxonis/depthai-python.git cd depthai-python/examples python3 install_requirements.py ``` For additional information, please follow the [installation guide](https://docs.luxonis.com/software/depthai/manual-install.md). ## Source code #### Python ```python #!/usr/bin/env python3 import cv2 import depthai as dai import numpy as np stepSize = 0.05 newConfig = False # Create pipeline pipeline = dai.Pipeline() # Define sources and outputs monoLeft = pipeline.create(dai.node.MonoCamera) monoRight = pipeline.create(dai.node.MonoCamera) stereo = pipeline.create(dai.node.StereoDepth) spatialLocationCalculator = pipeline.create(dai.node.SpatialLocationCalculator) xoutDepth = pipeline.create(dai.node.XLinkOut) xoutSpatialData = pipeline.create(dai.node.XLinkOut) xinSpatialCalcConfig = pipeline.create(dai.node.XLinkIn) xoutDepth.setStreamName("depth") xoutSpatialData.setStreamName("spatialData") xinSpatialCalcConfig.setStreamName("spatialCalcConfig") # Properties monoLeft.setResolution(dai.MonoCameraProperties.SensorResolution.THE_400_P) monoLeft.setCamera("left") monoRight.setResolution(dai.MonoCameraProperties.SensorResolution.THE_400_P) monoRight.setCamera("right") stereo.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.HIGH_DENSITY) stereo.setLeftRightCheck(True) stereo.setSubpixel(True) # Config topLeft = dai.Point2f(0.4, 0.4) bottomRight = dai.Point2f(0.6, 0.6) config = dai.SpatialLocationCalculatorConfigData() config.depthThresholds.lowerThreshold = 100 config.depthThresholds.upperThreshold = 10000 calculationAlgorithm = dai.SpatialLocationCalculatorAlgorithm.MEDIAN config.roi = dai.Rect(topLeft, bottomRight) spatialLocationCalculator.inputConfig.setWaitForMessage(False) spatialLocationCalculator.initialConfig.addROI(config) # Linking monoLeft.out.link(stereo.left) monoRight.out.link(stereo.right) spatialLocationCalculator.passthroughDepth.link(xoutDepth.input) stereo.depth.link(spatialLocationCalculator.inputDepth) spatialLocationCalculator.out.link(xoutSpatialData.input) xinSpatialCalcConfig.out.link(spatialLocationCalculator.inputConfig) # Connect to device and start pipeline with dai.Device(pipeline) as device: # Output queue will be used to get the depth frames from the outputs defined above depthQueue = device.getOutputQueue(name="depth", maxSize=4, blocking=False) spatialCalcQueue = device.getOutputQueue(name="spatialData", maxSize=4, blocking=False) spatialCalcConfigInQueue = device.getInputQueue("spatialCalcConfig") color = (255, 255, 255) print("Use WASD keys to move ROI!") while True: inDepth = depthQueue.get() # Blocking call, will wait until a new data has arrived depthFrame = inDepth.getFrame() # depthFrame values are in millimeters depth_downscaled = depthFrame[::4] if np.all(depth_downscaled == 0): min_depth = 0 # Set a default minimum depth value when all elements are zero else: min_depth = np.percentile(depth_downscaled[depth_downscaled != 0], 1) max_depth = np.percentile(depth_downscaled, 99) depthFrameColor = np.interp(depthFrame, (min_depth, max_depth), (0, 255)).astype(np.uint8) depthFrameColor = cv2.applyColorMap(depthFrameColor, cv2.COLORMAP_HOT) spatialData = spatialCalcQueue.get().getSpatialLocations() for depthData in spatialData: roi = depthData.config.roi roi = roi.denormalize(width=depthFrameColor.shape[1], height=depthFrameColor.shape[0]) xmin = int(roi.topLeft().x) ymin = int(roi.topLeft().y) xmax = int(roi.bottomRight().x) ymax = int(roi.bottomRight().y) depthMin = depthData.depthMin depthMax = depthData.depthMax fontType = cv2.FONT_HERSHEY_TRIPLEX cv2.rectangle(depthFrameColor, (xmin, ymin), (xmax, ymax), color, 1) cv2.putText(depthFrameColor, f"X: {int(depthData.spatialCoordinates.x)} mm", (xmin + 10, ymin + 20), fontType, 0.5, color) cv2.putText(depthFrameColor, f"Y: {int(depthData.spatialCoordinates.y)} mm", (xmin + 10, ymin + 35), fontType, 0.5, color) cv2.putText(depthFrameColor, f"Z: {int(depthData.spatialCoordinates.z)} mm", (xmin + 10, ymin + 50), fontType, 0.5, color) # Show the frame cv2.imshow("depth", depthFrameColor) key = cv2.waitKey(1) if key == ord('q'): break elif key == ord('w'): if topLeft.y - stepSize >= 0: topLeft.y -= stepSize bottomRight.y -= stepSize newConfig = True elif key == ord('a'): if topLeft.x - stepSize >= 0: topLeft.x -= stepSize bottomRight.x -= stepSize newConfig = True elif key == ord('s'): if bottomRight.y + stepSize <= 1: topLeft.y += stepSize bottomRight.y += stepSize newConfig = True elif key == ord('d'): if bottomRight.x + stepSize <= 1: topLeft.x += stepSize bottomRight.x += stepSize newConfig = True elif key == ord('1'): calculationAlgorithm = dai.SpatialLocationCalculatorAlgorithm.MEAN print('Switching calculation algorithm to MEAN!') newConfig = True elif key == ord('2'): calculationAlgorithm = dai.SpatialLocationCalculatorAlgorithm.MIN print('Switching calculation algorithm to MIN!') newConfig = True elif key == ord('3'): calculationAlgorithm = dai.SpatialLocationCalculatorAlgorithm.MAX print('Switching calculation algorithm to MAX!') newConfig = True elif key == ord('4'): calculationAlgorithm = dai.SpatialLocationCalculatorAlgorithm.MODE print('Switching calculation algorithm to MODE!') newConfig = True elif key == ord('5'): calculationAlgorithm = dai.SpatialLocationCalculatorAlgorithm.MEDIAN print('Switching calculation algorithm to MEDIAN!') newConfig = True if newConfig: config.roi = dai.Rect(topLeft, bottomRight) config.calculationAlgorithm = calculationAlgorithm cfg = dai.SpatialLocationCalculatorConfig() cfg.addROI(config) spatialCalcConfigInQueue.send(cfg) newConfig = False ``` #### C++ ```cpp #include #include "utility.hpp" // Includes common necessary includes for development using depthai library #include "depthai/depthai.hpp" static constexpr float stepSize = 0.05f; static std::atomic newConfig{false}; int main() { using namespace std; // Create pipeline dai::Pipeline pipeline; // Define sources and outputs auto monoLeft = pipeline.create(); auto monoRight = pipeline.create(); auto stereo = pipeline.create(); auto spatialDataCalculator = pipeline.create(); auto xoutDepth = pipeline.create(); auto xoutSpatialData = pipeline.create(); auto xinSpatialCalcConfig = pipeline.create(); xoutDepth->setStreamName("depth"); xoutSpatialData->setStreamName("spatialData"); xinSpatialCalcConfig->setStreamName("spatialCalcConfig"); // Properties monoLeft->setResolution(dai::MonoCameraProperties::SensorResolution::THE_400_P); monoLeft->setCamera("left"); monoRight->setResolution(dai::MonoCameraProperties::SensorResolution::THE_400_P); monoRight->setCamera("right"); bool lrcheck = false; bool subpixel = false; stereo->setDefaultProfilePreset(dai::node::StereoDepth::PresetMode::HIGH_DENSITY); stereo->setLeftRightCheck(lrcheck); stereo->setSubpixel(subpixel); // Config dai::Point2f topLeft(0.4f, 0.4f); dai::Point2f bottomRight(0.6f, 0.6f); dai::SpatialLocationCalculatorConfigData config; config.depthThresholds.lowerThreshold = 100; config.depthThresholds.upperThreshold = 10000; auto calculationAlgorithm = dai::SpatialLocationCalculatorAlgorithm::MEDIAN; config.calculationAlgorithm = calculationAlgorithm; config.roi = dai::Rect(topLeft, bottomRight); spatialDataCalculator->inputConfig.setWaitForMessage(false); spatialDataCalculator->initialConfig.addROI(config); // Linking monoLeft->out.link(stereo->left); monoRight->out.link(stereo->right); spatialDataCalculator->passthroughDepth.link(xoutDepth->input); stereo->depth.link(spatialDataCalculator->inputDepth); spatialDataCalculator->out.link(xoutSpatialData->input); xinSpatialCalcConfig->out.link(spatialDataCalculator->inputConfig); // Connect to device and start pipeline dai::Device device(pipeline); // Output queue will be used to get the depth frames from the outputs defined above auto depthQueue = device.getOutputQueue("depth", 8, false); auto spatialCalcQueue = device.getOutputQueue("spatialData", 8, false); auto spatialCalcConfigInQueue = device.getInputQueue("spatialCalcConfig"); auto color = cv::Scalar(255, 255, 255); std::cout << "Use WASD keys to move ROI!" << std::endl; while(true) { auto inDepth = depthQueue->get(); cv::Mat depthFrame = inDepth->getFrame(); // depthFrame values are in millimeters cv::Mat depthFrameColor; cv::normalize(depthFrame, depthFrameColor, 255, 0, cv::NORM_INF, CV_8UC1); cv::equalizeHist(depthFrameColor, depthFrameColor); cv::applyColorMap(depthFrameColor, depthFrameColor, cv::COLORMAP_HOT); auto spatialData = spatialCalcQueue->get()->getSpatialLocations(); for(auto depthData : spatialData) { auto roi = depthData.config.roi; roi = roi.denormalize(depthFrameColor.cols, depthFrameColor.rows); auto xmin = (int)roi.topLeft().x; auto ymin = (int)roi.topLeft().y; auto xmax = (int)roi.bottomRight().x; auto ymax = (int)roi.bottomRight().y; auto depthMin = depthData.depthMin; auto depthMax = depthData.depthMax; cv::rectangle(depthFrameColor, cv::Rect(cv::Point(xmin, ymin), cv::Point(xmax, ymax)), color, cv::FONT_HERSHEY_SIMPLEX); std::stringstream depthX; depthX << "X: " << (int)depthData.spatialCoordinates.x << " mm"; cv::putText(depthFrameColor, depthX.str(), cv::Point(xmin + 10, ymin + 20), cv::FONT_HERSHEY_TRIPLEX, 0.5, color); std::stringstream depthY; depthY << "Y: " << (int)depthData.spatialCoordinates.y << " mm"; cv::putText(depthFrameColor, depthY.str(), cv::Point(xmin + 10, ymin + 35), cv::FONT_HERSHEY_TRIPLEX, 0.5, color); std::stringstream depthZ; depthZ << "Z: " << (int)depthData.spatialCoordinates.z << " mm"; cv::putText(depthFrameColor, depthZ.str(), cv::Point(xmin + 10, ymin + 50), cv::FONT_HERSHEY_TRIPLEX, 0.5, color); } // Show the frame cv::imshow("depth", depthFrameColor); int key = cv::waitKey(1); switch(key) { case 'q': return 0; case 'w': if(topLeft.y - stepSize >= 0) { topLeft.y -= stepSize; bottomRight.y -= stepSize; newConfig = true; } break; case 'a': if(topLeft.x - stepSize >= 0) { topLeft.x -= stepSize; bottomRight.x -= stepSize; newConfig = true; } break; case 's': if(bottomRight.y + stepSize <= 1) { topLeft.y += stepSize; bottomRight.y += stepSize; newConfig = true; } break; case 'd': if(bottomRight.x + stepSize <= 1) { topLeft.x += stepSize; bottomRight.x += stepSize; newConfig = true; } break; case '1': calculationAlgorithm = dai::SpatialLocationCalculatorAlgorithm::MEAN; newConfig = true; std::cout << "Switching calculation algorithm to MEAN!" << std::endl; break; case '2': calculationAlgorithm = dai::SpatialLocationCalculatorAlgorithm::MIN; newConfig = true; std::cout << "Switching calculation algorithm to MIN!" << std::endl; break; case '3': calculationAlgorithm = dai::SpatialLocationCalculatorAlgorithm::MAX; newConfig = true; std::cout << "Switching calculation algorithm to MAX!" << std::endl; break; case '4': calculationAlgorithm = dai::SpatialLocationCalculatorAlgorithm::MODE; newConfig = true; std::cout << "Switching calculation algorithm to MODE!" << std::endl; break; case '5': calculationAlgorithm = dai::SpatialLocationCalculatorAlgorithm::MEDIAN; newConfig = true; std::cout << "Switching calculation algorithm to MEDIAN!" << std::endl; break; default: break; } if(newConfig) { config.roi = dai::Rect(topLeft, bottomRight); config.calculationAlgorithm = calculationAlgorithm; dai::SpatialLocationCalculatorConfig cfg; cfg.addROI(config); spatialCalcConfigInQueue->send(cfg); newConfig = false; } } return 0; } ``` ## Pipeline ### examples/spatial_location_calculator.pipeline.json ```json { "pipeline": { "connections": [ { "node1Id": 0, "node1Output": "out", "node1OutputGroup": "", "node2Id": 2, "node2Input": "left", "node2InputGroup": "" }, { "node1Id": 1, "node1Output": "out", "node1OutputGroup": "", "node2Id": 2, "node2Input": "right", "node2InputGroup": "" }, { "node1Id": 3, "node1Output": "passthroughDepth", 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"ioInfo": [ [ [ "", "in" ], { "blocking": true, "group": "", "id": 30, "name": "in", "queueSize": 8, "type": 3, "waitForMessage": true } ] ], "name": "XLinkOut", "properties": { "maxFpsLimit": -1.0, "metadataOnly": false, "streamName": "spatialData" } } ], [ 6, { "id": 6, "ioInfo": [ [ [ "", "out" ], { "blocking": false, "group": "", "id": 31, "name": "out", "queueSize": 8, "type": 0, "waitForMessage": false } ] ], "name": "XLinkIn", "properties": { "maxDataSize": 5242880, "numFrames": 8, "streamName": "spatialCalcConfig" } } ] ] } } ``` ### Need assistance? 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