Welcome to AI on the Edge – Lesson 17: Decorating and Annotating Video Frames in OpenCV. In this lesson we take our live video stream from the Raspberry Pi camera and start making it really useful and professional-looking. Now that we can grab frames and display them, it’s time to learn how to draw directly on top of those frames. We’re talking rectangles, lines, arrows, circles, and crisp text overlays — all the visual elements you’ll need when you start adding real AI like face detection or object recognition.
You’ll see exactly how to use OpenCV’s drawing functions to create clean, scalable annotations that look great whether you’re running at 320×180 for maximum speed or higher resolutions like 1280×720. We cover how to control line thickness, use filled shapes, position text properly, and most importantly, how to make all your drawings scale automatically with your chosen resolution so everything stays nicely proportioned.
By the end of this lesson you’ll have the skills to draw bounding boxes around detected objects, add confidence scores, label people or items, draw tracking lines — basically anything you need to show what your AI is seeing. This is one of those foundational skills that you’ll use over and over again in your computer vision projects.As always, I encourage you to type the code along with me in the video, then start playing with colors, sizes, positions, and messages. Change things around, break it, and make it your own. That’s the best way to really learn this stuff.
So fire up your Raspberry Pi 5, grab that camera, and let’s start turning raw video frames into clear, informative, and great-looking annotated output!
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import cv2 from picamera2 import Picamera2 piCam = Picamera2() W=1280 H=720 # W= 640 # H= 360 W=320 H=180 RES = (W,H) piCam.preview_configuration.main.size = RES piCam.preview_configuration.main.format = "RGB888" piCam.preview_configuration.controls.FrameRate=60 piCam.preview_configuration.align() piCam.configure("preview") piCam.start() while True: frame= piCam.capture_array() frame=cv2.flip(frame,-1) upperLeft = (int((W-1)*.1),int((H-1)*.1)) lowerRight = (int((W-1)*.9),int((H-1)*.9)) myColor = (255,0,0) myThick = int(W/250) cv2.rectangle(frame,upperLeft,lowerRight,myColor,myThick) upperLeft = (int((W-1)*.3),int((H-1)*.3)) lowerRight = (int((W-1)*.7),int((H-1)*.7)) myColor = (0,0,255) myThick = int(W/250) myThick = -1 cv2.rectangle(frame,upperLeft,lowerRight,myColor,myThick) startingPoint = (int((W-1)*.1),int((H-1)*.1)) endingPoint = (int((W-1)*.9),int((H-1)*.9)) myColor = (255,0,0) myThick = int(W/250) cv2.line(frame,startingPoint,endingPoint,myColor,myThick) startingPoint = (int((W-1)*.7),int((H-1)*.3)) endingPoint = (int((W-1)*.3),int((H-1)*.7)) myColor = (0,255,0) myThick = int(W/250) cv2.arrowedLine(frame,startingPoint,endingPoint,myColor,myThick) myCenter = (int((W-1)/2),int((H-1)/2)) myRadius = int(.1*(H-1)) myThick = int(W/250) myColor = (0,255,0) cv2.circle(frame,myCenter,myRadius,myColor,myThick) myCenter1 = (int((W-1)*.3),int((H-1)*.3)) myCenter2 = (int((W-1)*.7),int((H-1)*.7)) myCenter3 = (int((W-1)*.7),int((H-1)*.3)) myCenter4 = (int((W-1)*.3),int((H-1)*.7)) myRadius = int((W-1)*.05) myColor = (255,0,0) myThick= -1 cv2.circle(frame,myCenter1,myRadius,myColor,myThick) cv2.circle(frame,myCenter2,myRadius,myColor,myThick) cv2.circle(frame,myCenter3,myRadius,myColor,myThick) cv2.circle(frame,myCenter4,myRadius,myColor,myThick) myText = "My Excellent Label" textLowerLeft= (int(W*.01),int(H*.05)) fontFace = cv2.FONT_HERSHEY_SIMPLEX fontThickness = int(W/450) fontScale = H*.0015 fontColor = (255,0,255) cv2.putText(frame,myText,textLowerLeft,fontFace,fontScale, fontColor, fontThickness) cv2.imshow("Camera", frame) cv2.moveWindow("Camera",0,60) if cv2.waitKey(1)==ord('q'): break cv2.destroyAllWindows() print('Program Terminated') |