Motion detection with camera in Raspberry Pi - Mini Project: Build & Apply

Motion detection with camera

📖 Scenario: You have a Raspberry Pi with a camera module. You want to detect when something moves in front of the camera. This project will help you write a simple program to detect motion by comparing images.

🎯 Goal: Build a Python program that captures images from the Raspberry Pi camera, compares them to detect motion, and prints a message when motion is detected.

📋 What You'll Learn

Use the picamera library to capture images.

Use the PIL (Pillow) library to process images.

Compare two images to detect changes.

Print Motion detected! when movement is found.

💡 Why This Matters

🌍 Real World

Motion detection is used in home security cameras to alert owners when someone moves in front of the camera.

💼 Career

Understanding how to capture and process images on devices like Raspberry Pi is useful for jobs in IoT, embedded systems, and security technology.

1

Set up initial variables and import libraries

Import the picamera and PIL.Image libraries. Create two variables called image1_path and image2_path with values 'image1.jpg' and 'image2.jpg' respectively.

Raspberry Pi

# Import picamera and PIL.Image
# Create variables image1_path and image2_path
# Your code here

Hint

Use import picamera and from PIL import Image. Then assign the file names as strings to the variables.

2

Capture two images with the camera

Create a picamera.PiCamera() object called camera. Use camera.capture() to take two pictures saved to image1_path and image2_path.

Raspberry Pi

import picamera
from PIL import Image

image1_path = 'image1.jpg'
image2_path = 'image2.jpg'

# Create camera object and capture two images
# Your code here

Hint

Create the camera with picamera.PiCamera(). Use camera.capture() twice with the file paths.

3

Compare the two images to detect motion

Open the images from image1_path and image2_path using Image.open(). Convert them to grayscale with .convert('L'). Calculate the difference by subtracting pixel values and count how many pixels differ by more than 30. Store this count in a variable called motion_pixels.

Raspberry Pi

import picamera
from PIL import Image

image1_path = 'image1.jpg'
image2_path = 'image2.jpg'

camera = picamera.PiCamera()
camera.capture(image1_path)
camera.capture(image2_path)

# Open images, convert to grayscale, and count differing pixels
# Your code here

Hint

Use Image.open() and .convert('L') to get grayscale images. Use getdata() to get pixels. Loop through pixels and count differences over 30.

4

Print motion detection result

If motion_pixels is greater than 1000, print Motion detected!. Otherwise, print No motion detected.

Raspberry Pi

import picamera
from PIL import Image

image1_path = 'image1.jpg'
image2_path = 'image2.jpg'

camera = picamera.PiCamera()
camera.capture(image1_path)
camera.capture(image2_path)

img1 = Image.open(image1_path).convert('L')
img2 = Image.open(image2_path).convert('L')

pixels1 = list(img1.getdata())
pixels2 = list(img2.getdata())

motion_pixels = 0
for p1, p2 in zip(pixels1, pixels2):
    if abs(p1 - p2) > 30:
        motion_pixels += 1

# Print motion detection message
# Your code here

Hint

Use an if statement to check if motion_pixels is greater than 1000. Print the correct message accordingly.

Practice

1. What is the main purpose of motion detection when using a camera on a Raspberry Pi?

easy

A. To increase the camera resolution automatically

B. To find changes between consecutive images

C. To save battery life of the Raspberry Pi

D. To connect the camera to the internet

Solution

1. Step 1: Understand motion detection basics

   Motion detection works by comparing images to find differences or changes.

2. Step 2: Identify the main goal of motion detection

   The goal is to detect movement by noticing changes between frames, not to change resolution or save power.

3. Final Answer:

   To find changes between consecutive images -> Option B

4. Quick Check:

   Motion detection = find changes [OK]

Hint: Motion detection means spotting changes between pictures [OK]

Common Mistakes:

• Confusing motion detection with camera settings
• Thinking motion detection saves power
• Assuming it connects camera to internet

2. Which of the following Python code snippets correctly imports OpenCV for motion detection on Raspberry Pi?

easy

A. import camera

B. import opencv

C. import cv

D. import cv2

Solution

1. Step 1: Recall the correct OpenCV import statement

   OpenCV in Python is imported using 'import cv2'.

2. Step 2: Check other options for correctness

   Options 'opencv', 'cv', and 'camera' are incorrect or outdated module names.

3. Final Answer:

   import cv2 -> Option D

4. Quick Check:

   OpenCV import = cv2 [OK]

Hint: OpenCV Python module is always imported as cv2 [OK]

Common Mistakes:

• Using 'import opencv' instead of 'import cv2'
• Confusing 'cv' with 'cv2'
• Trying to import 'camera' module for OpenCV

3. What will be the output of this code snippet when motion is detected?

import cv2
cap = cv2.VideoCapture(0)
ret, frame1 = cap.read()
ret, frame2 = cap.read()
diff = cv2.absdiff(frame1, frame2)
gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
_, thresh = cv2.threshold(gray, 30, 255, cv2.THRESH_BINARY)
print(thresh.sum() > 10000)

medium

A. True if motion detected, False otherwise

B. Always prints True

C. Always prints False

D. Raises a syntax error

Solution

1. Step 1: Understand the code logic for motion detection

   The code compares two frames, converts difference to grayscale, thresholds it, then sums pixels to detect motion.

2. Step 2: Interpret the print statement

   If the sum of thresholded pixels is greater than 10000, it prints True (motion detected), else False.

3. Final Answer:

   True if motion detected, False otherwise -> Option A

4. Quick Check:

   Threshold sum > 10000 means motion True [OK]

Hint: Sum of thresholded diff > limit means motion detected [OK]

Common Mistakes:

• Assuming it always prints True or False
• Confusing thresholding with color conversion
• Expecting syntax errors from correct code

4. Identify the error in this motion detection code snippet:

import cv2
cap = cv2.VideoCapture(0)
ret, frame1 = cap.read()
ret, frame2 = cap.read()
diff = cv2.absdiff(frame1, frame2)
gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
_, thresh = cv2.threshold(gray, 30, 255, cv2.THRESH_BINARY)
if thresh.sum() > 10000:
    print("Motion detected")
cap.release()

medium

A. Missing loop to continuously read frames

B. Incorrect threshold value used

C. cv2.absdiff should be cv2.subtract

D. cap.release() should be called before reading frames

Solution

1. Step 1: Check code flow for continuous motion detection

   The code reads frames only once, so it cannot detect motion continuously.

2. Step 2: Identify missing loop for repeated frame capture

   Motion detection requires a loop to keep reading frames and comparing them over time.

3. Final Answer:

   Missing loop to continuously read frames -> Option A

4. Quick Check:

   Continuous detection needs a loop [OK]

Hint: Motion detection needs a loop to compare frames repeatedly [OK]

Common Mistakes:

• Thinking threshold value is wrong
• Confusing absdiff with subtract
• Releasing capture too early

5. You want to trigger an alert only when motion is detected for at least 3 seconds continuously using a Raspberry Pi camera. Which approach is best?

hard

A. Use a timer to trigger alert every 3 seconds regardless of motion

B. Trigger alert immediately on first motion detection

C. Count consecutive frames with motion and trigger alert after threshold

D. Ignore motion and trigger alert manually

Solution

1. Step 1: Understand the requirement for continuous motion detection

   We need to detect motion lasting at least 3 seconds, not just a single frame.

2. Step 2: Choose method to track motion duration

   Counting consecutive frames with motion and triggering alert after reaching a threshold time is the best approach.

3. Final Answer:

   Count consecutive frames with motion and trigger alert after threshold -> Option C

4. Quick Check:

   Continuous motion needs counting frames [OK]

Hint: Count frames with motion to confirm duration before alert [OK]

Common Mistakes:

• Triggering alert immediately on any motion
• Using timer without checking motion
• Ignoring motion detection logic