DepthAI Tutorials
DepthAI API References

ON THIS PAGE

  • Feature Tracker
  • Demo
  • Setup
  • Source code
  • Pipeline

Feature Tracker

Example shows capabilities of FeatureTracker. It detects features and tracks them between consecutive frames using optical flow by assigning unique ID to matching features. Feature Detector example only detects features.

Demo

Setup

Please run the install script to download all required dependencies. Please note that this script must be ran from git context, so you have to download the depthai-python repository first and then run the script
Command Line
1git clone https://github.com/luxonis/depthai-python.git
2cd depthai-python/examples
3python3 install_requirements.py
For additional information, please follow the installation guide.

Source code

Python
C++

Python

Python
GitHub
1#!/usr/bin/env python3
2
3import cv2
4import depthai as dai
5from collections import deque
6
7class FeatureTrackerDrawer:
8
9    lineColor = (200, 0, 200)
10    pointColor = (0, 0, 255)
11    circleRadius = 2
12    maxTrackedFeaturesPathLength = 30
13    # for how many frames the feature is tracked
14    trackedFeaturesPathLength = 10
15
16    trackedIDs = None
17    trackedFeaturesPath = None
18
19    def onTrackBar(self, val):
20        FeatureTrackerDrawer.trackedFeaturesPathLength = val
21        pass
22
23    def trackFeaturePath(self, features):
24
25        newTrackedIDs = set()
26        for currentFeature in features:
27            currentID = currentFeature.id
28            newTrackedIDs.add(currentID)
29
30            if currentID not in self.trackedFeaturesPath:
31                self.trackedFeaturesPath[currentID] = deque()
32
33            path = self.trackedFeaturesPath[currentID]
34
35            path.append(currentFeature.position)
36            while(len(path) > max(1, FeatureTrackerDrawer.trackedFeaturesPathLength)):
37                path.popleft()
38
39            self.trackedFeaturesPath[currentID] = path
40
41        featuresToRemove = set()
42        for oldId in self.trackedIDs:
43            if oldId not in newTrackedIDs:
44                featuresToRemove.add(oldId)
45
46        for id in featuresToRemove:
47            self.trackedFeaturesPath.pop(id)
48
49        self.trackedIDs = newTrackedIDs
50
51    def drawFeatures(self, img):
52
53        cv2.setTrackbarPos(self.trackbarName, self.windowName, FeatureTrackerDrawer.trackedFeaturesPathLength)
54
55        for featurePath in self.trackedFeaturesPath.values():
56            path = featurePath
57
58            for j in range(len(path) - 1):
59                src = (int(path[j].x), int(path[j].y))
60                dst = (int(path[j + 1].x), int(path[j + 1].y))
61                cv2.line(img, src, dst, self.lineColor, 1, cv2.LINE_AA, 0)
62            j = len(path) - 1
63            cv2.circle(img, (int(path[j].x), int(path[j].y)), self.circleRadius, self.pointColor, -1, cv2.LINE_AA, 0)
64
65    def __init__(self, trackbarName, windowName):
66        self.trackbarName = trackbarName
67        self.windowName = windowName
68        cv2.namedWindow(windowName)
69        cv2.createTrackbar(trackbarName, windowName, FeatureTrackerDrawer.trackedFeaturesPathLength, FeatureTrackerDrawer.maxTrackedFeaturesPathLength, self.onTrackBar)
70        self.trackedIDs = set()
71        self.trackedFeaturesPath = dict()
72
73
74# Create pipeline
75pipeline = dai.Pipeline()
76
77# Define sources and outputs
78monoLeft = pipeline.create(dai.node.MonoCamera)
79monoRight = pipeline.create(dai.node.MonoCamera)
80featureTrackerLeft = pipeline.create(dai.node.FeatureTracker)
81featureTrackerRight = pipeline.create(dai.node.FeatureTracker)
82
83xoutPassthroughFrameLeft = pipeline.create(dai.node.XLinkOut)
84xoutTrackedFeaturesLeft = pipeline.create(dai.node.XLinkOut)
85xoutPassthroughFrameRight = pipeline.create(dai.node.XLinkOut)
86xoutTrackedFeaturesRight = pipeline.create(dai.node.XLinkOut)
87xinTrackedFeaturesConfig = pipeline.create(dai.node.XLinkIn)
88
89xoutPassthroughFrameLeft.setStreamName("passthroughFrameLeft")
90xoutTrackedFeaturesLeft.setStreamName("trackedFeaturesLeft")
91xoutPassthroughFrameRight.setStreamName("passthroughFrameRight")
92xoutTrackedFeaturesRight.setStreamName("trackedFeaturesRight")
93xinTrackedFeaturesConfig.setStreamName("trackedFeaturesConfig")
94
95# Properties
96monoLeft.setResolution(dai.MonoCameraProperties.SensorResolution.THE_720_P)
97monoLeft.setCamera("left")
98monoRight.setResolution(dai.MonoCameraProperties.SensorResolution.THE_720_P)
99monoRight.setCamera("right")
100
101# Linking
102monoLeft.out.link(featureTrackerLeft.inputImage)
103featureTrackerLeft.passthroughInputImage.link(xoutPassthroughFrameLeft.input)
104featureTrackerLeft.outputFeatures.link(xoutTrackedFeaturesLeft.input)
105xinTrackedFeaturesConfig.out.link(featureTrackerLeft.inputConfig)
106
107monoRight.out.link(featureTrackerRight.inputImage)
108featureTrackerRight.passthroughInputImage.link(xoutPassthroughFrameRight.input)
109featureTrackerRight.outputFeatures.link(xoutTrackedFeaturesRight.input)
110xinTrackedFeaturesConfig.out.link(featureTrackerRight.inputConfig)
111
112# By default the least mount of resources are allocated
113# increasing it improves performance
114numShaves = 2
115numMemorySlices = 2
116featureTrackerLeft.setHardwareResources(numShaves, numMemorySlices)
117featureTrackerRight.setHardwareResources(numShaves, numMemorySlices)
118
119featureTrackerConfig = featureTrackerRight.initialConfig.get()
120print("Press 's' to switch between Lucas-Kanade optical flow and hardware accelerated motion estimation!")
121
122# Connect to device and start pipeline
123with dai.Device(pipeline) as device:
124
125    # Output queues used to receive the results
126    passthroughImageLeftQueue = device.getOutputQueue("passthroughFrameLeft", 8, False)
127    outputFeaturesLeftQueue = device.getOutputQueue("trackedFeaturesLeft", 8, False)
128    passthroughImageRightQueue = device.getOutputQueue("passthroughFrameRight", 8, False)
129    outputFeaturesRightQueue = device.getOutputQueue("trackedFeaturesRight", 8, False)
130
131    inputFeatureTrackerConfigQueue = device.getInputQueue("trackedFeaturesConfig")
132
133    leftWindowName = "left"
134    leftFeatureDrawer = FeatureTrackerDrawer("Feature tracking duration (frames)", leftWindowName)
135
136    rightWindowName = "right"
137    rightFeatureDrawer = FeatureTrackerDrawer("Feature tracking duration (frames)", rightWindowName)
138
139    while True:
140        inPassthroughFrameLeft = passthroughImageLeftQueue.get()
141        passthroughFrameLeft = inPassthroughFrameLeft.getFrame()
142        leftFrame = cv2.cvtColor(passthroughFrameLeft, cv2.COLOR_GRAY2BGR)
143
144        inPassthroughFrameRight = passthroughImageRightQueue.get()
145        passthroughFrameRight = inPassthroughFrameRight.getFrame()
146        rightFrame = cv2.cvtColor(passthroughFrameRight, cv2.COLOR_GRAY2BGR)
147
148        trackedFeaturesLeft = outputFeaturesLeftQueue.get().trackedFeatures
149        leftFeatureDrawer.trackFeaturePath(trackedFeaturesLeft)
150        leftFeatureDrawer.drawFeatures(leftFrame)
151
152        trackedFeaturesRight = outputFeaturesRightQueue.get().trackedFeatures
153        rightFeatureDrawer.trackFeaturePath(trackedFeaturesRight)
154        rightFeatureDrawer.drawFeatures(rightFrame)
155
156        # Show the frame
157        cv2.imshow(leftWindowName, leftFrame)
158        cv2.imshow(rightWindowName, rightFrame)
159
160        key = cv2.waitKey(1)
161        if key == ord('q'):
162            break
163        elif key == ord('s'):
164            if featureTrackerConfig.motionEstimator.type == dai.FeatureTrackerConfig.MotionEstimator.Type.LUCAS_KANADE_OPTICAL_FLOW:
165                featureTrackerConfig.motionEstimator.type = dai.FeatureTrackerConfig.MotionEstimator.Type.HW_MOTION_ESTIMATION
166                print("Switching to hardware accelerated motion estimation")
167            else:
168                featureTrackerConfig.motionEstimator.type = dai.FeatureTrackerConfig.MotionEstimator.Type.LUCAS_KANADE_OPTICAL_FLOW
169                print("Switching to Lucas-Kanade optical flow")
170
171            cfg = dai.FeatureTrackerConfig()
172            cfg.set(featureTrackerConfig)
173            inputFeatureTrackerConfigQueue.send(cfg)

Pipeline

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