/
spatial_location_calculator.py
executable file
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/
spatial_location_calculator.py
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#!/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