接收來自 ROS Topic 的影像並偵測畫面中的動作 - 24小时 - 剑客 -「科技引领未来」

接收來自 ROS Topic 的影像並偵測畫面中的動作

這次來帶大家玩個基礎的應用 - 動作偵測,用自己筆電的相機再加上 OpenCV 的 API,就可以做到動作偵測並把在動的地方框起來。可以透過這篇

這次來帶大家玩個基礎的應用 - 動作偵測,用自己筆電的相機再加上 OpenCV 的 API,就可以做到動作偵測並把在動的地方框起來。可以透過這篇學習怎麼使用 ROS Topic 來接收影像並做後續的處理。

開 package 寫程式

首先來開一個 motion_detector package:

catkin_create_pkg motion_detector rospy sensor_msgs cv_bridge usb_cam/

cd motion_detector

vim src/motion_detector.py

程式碼長這樣,裡面主要是用到 OpenCV 的 MOG2

這個前背景分類的工具,切出來的前景就用一個框框來表示。

#!/usr/bin/env python

importrospy

importcv2

importnumpyasnp

fromcv_bridgeimportCvBridge, CvBridgeError

fromsensor_msgs.msgimportImage

kernel_elliptic_7 = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (7,7))

kernel_elliptic_15 = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (15,15))

area_threshold = 2000

classMOG2:

def__init__(self):

self.fgbg = cv2.BackgroundSubtractorMOG2(history=150, varThreshold=500, bShadowDetection=True)

defdetect(self,image):

fgmask = self.fgbg.apply(image)

cv2.morphologyEx(fgmask, cv2.MORPH_CLOSE, kernel_elliptic_7, dst=fgmask)

cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel_elliptic_15, dst=fgmask)

contours = cv2.findContours(fgmask.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

area_box = ((cv2.contourArea(contour), cv2.boundingRect(contour)) forcontourincontours[0])

area_box = [(area, box) for(area, box)inarea_boxifarea > area_threshold]

area_box.sort(reverse=True)

bounding_boxes = [((x, y), (x+w, y+h)) for_, (x, y, w, h)inarea_box[:5]]

forp1, p2inbounding_boxes:

cv2.rectangle(image, p1, p2, (0,255,0),2)

returnimage

#return fgmask #for param tuning

classMotion:

def__init__(self):

rospy.init_node("motion_detector_node")

self.bridge = CvBridge()

self.pub = rospy.Publisher('camera/visible/image', Image, queue_size=2)

rospy.Subscriber("usb_cam/image_raw", Image, self.imageCallback)

self.motion_detector = MOG2()

rospy.spin()

defimageCallback(self, image):

ifself.motion_detector:

cv_image = self.bridge.imgmsg_to_cv2(image, "bgr8")

result_img = self.motion_detector.detect(cv_image)

image = self.bridge.cv2_to_imgmsg(result_img, "bgr8")

#image = self.bridge.cv2_to_imgmsg(result_img, "mono8") #for param tuning

self.pub.publish(image)

if__name__ =='__main__':

detector = Motion()

執行程式

先把程式變成可執行的 node,接着來寫個 launch file 方便執行:

chmod +x src/motion_detector.py

mkdir launch

vim launch/motion_detection.launch

<launch>

<!-- Launch the motion detector node for image processing. -->

<nodepkg="motion_detector"name="MotionDetector"type="motion_detector.py"/>

<!-- Launch the driver node for our usb camera. -->

<nodename="usb_cam"pkg="usb_cam"type="usb_cam_node"output="screen">

<paramname="video_device"value="/dev/video0"/>

<paramname="image_width"value="640"/>

<paramname="image_height"value="480"/>

<paramname="pixel_format"value="yuyv"/>

<paramname="camera_frame_id"value="usb_cam"/>

<paramname="io_method"value="mmap"/>

</node>

<nodename="rviz"pkg="rviz"type="rviz"required="true"

args="-d $(find motion_detector)/rviz/motion.rviz"/>

</launch>

這邊想順便教大家一個技巧,你可以把 rviz 的檔案先寫好,這樣每次重新啓動 Rviz 就很方便,不用重新選想要看的資料類型。

vim rviz/motion.rviz

其實這個檔案可以直接從 Rviz 存出來,或是你也可以很 hardcore 地自己寫XD

Panels:

- Class: rviz/Displays

Help Height: 78

Name: Displays

Property Tree Widget:

Expanded:

- /Global Options1

- /Status1

- /Image1

Splitter Ratio: 0.5

Tree Height: 387

- Class: rviz/Selection

Name: Selection

- Class: rviz/Tool Properties

Expanded:

- /2D Pose Estimate1

- /2D Nav Goal1

- /Publish Point1

Name: Tool Properties

Splitter Ratio: 0.588679

- Class: rviz/Views

Expanded:

- /Current View1

Name: Views

Splitter Ratio: 0.5

- Class: rviz/Time

Experimental: false

Name: Time

SyncMode: 0

SyncSource: Image

Visualization Manager:

Class: ""

Displays:

- Alpha: 0.5

Cell Size: 1

Class: rviz/Grid

Color: 160; 160; 164

Enabled: true

Line Style:

Line Width: 0.03

Value: Lines

Name: Grid

Normal Cell Count: 0

Offset:

X: 0

Y: 0

Z: 0

Plane: XY

Plane Cell Count: 10

Reference Frame: <FixedFrame>

Value: true

- Class: rviz/Image

Enabled: true

Image Topic: /camera/visible/image

Max Value: 1

Median window: 5

Min Value: 0

Name: Image

Normalize Range: true

Queue Size: 2

Transport Hint: raw

Unreliable: false

Value: true

Enabled: true

Global Options:

Background Color: 48; 48; 48

Fixed Frame: map

Frame Rate: 30

Name: root

Tools:

- Class: rviz/Interact

Hide Inactive Objects: true

- Class: rviz/MoveCamera

- Class: rviz/Select

- Class: rviz/FocusCamera

- Class: rviz/Measure

- Class: rviz/SetInitialPose

Topic: /initialpose

- Class: rviz/SetGoal

Topic: /move_base_simple/goal

- Class: rviz/PublishPoint

Single click: true

Topic: /clicked_point

Value: true

Views:

Current:

Class: rviz/Orbit

Distance: 10

Enable Stereo Rendering:

Stereo Eye Separation: 0.06

Stereo Focal Distance: 1

Swap Stereo Eyes: false

Value: false

Focal Point:

X: 0

Y: 0

Z: 0

Name: Current View

Near Clip Distance: 0.01

Pitch: 0.785398

Target Frame: <FixedFrame>

Value: Orbit (rviz)

Yaw: 0.785398

Saved: ~

Window Geometry:

Displays:

collapsed: false

Height: 668

Hide Left Dock: false

Hide Right Dock: false

Image:

collapsed: false

QMainWindow State: 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

Selection:

collapsed: false

Time:

collapsed: false

Tool Properties:

collapsed: false

Views:

collapsed: false

Width: 1200

X: 55

Y: 14

執行結果

roslaunch motion_detector motion_detection.launch

用上面的指令跑起來之後,就可以看到在動的東西被框框圈起來啦!

接收來自 ROS Topic 的影像並偵測畫面中的動作

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