Haar cascade face detection in Computer Vision - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to load the Haar cascade classifier for face detection.

Computer Vision

face_cascade = cv2.CascadeClassifier([1])

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A"haarcascade_frontalface_default.xml"

B"face_detector.xml"

C"face_cascade.xml"

D"haarcascade_eye.xml"

Attempts:

3 left

💡 Hint

Common Mistakes

Using the eye cascade file instead of the face cascade.

Using a non-existent or incorrect file name.

The correct file name for the default Haar cascade face detector is "haarcascade_frontalface_default.xml".

2fill in blank

medium

Complete the code to convert the input image to grayscale before detection.

Computer Vision

gray = cv2.[1](img, cv2.COLOR_BGR2GRAY)

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AtoGray

BconvertColor

CcvtColor

DchangeColor

Attempts:

3 left

💡 Hint

Common Mistakes

Using a non-existent function like convertColor or toGray.

Forgetting to convert to grayscale before detection.

The OpenCV function to convert color spaces is cvtColor.

3fill in blank

hard

Fix the error in the code to detect faces using the cascade classifier.

Computer Vision

faces = face_cascade.[1](gray, scaleFactor=1.1, minNeighbors=5)

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AdetectFaces

BdetectMultiScale

CfindFaces

DdetectObjects

Attempts:

3 left

💡 Hint

Common Mistakes

Using incorrect method names like detectFaces or findFaces.

Calling a method that does not exist on the cascade object.

The correct method to detect objects in Haar cascades is detectMultiScale.

4fill in blank

hard

Fill both blanks to draw rectangles around detected faces with a blue color and thickness 2.

Computer Vision

for (x, y, w, h) in faces:
    cv2.rectangle(img, (x, y), (x + w, y + h), [1], [2])

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A(255, 0, 0)

B2

C(0, 255, 0)

D4

Attempts:

3 left

💡 Hint

Common Mistakes

Using green color instead of blue.

Using thickness 4 which is thicker than needed.

Blue color in BGR is (255, 0, 0) and thickness 2 is standard for drawing rectangles.

5fill in blank

hard

Fill all three blanks to complete the code that loads an image, detects faces, and shows the result window.

Computer Vision

img = cv2.[1]('test.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.[2](gray)
cv2.[3]('Faces', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

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Aimread

BdetectMultiScale

Cimshow

Dimwrite

Attempts:

3 left

💡 Hint

Common Mistakes

Using imwrite instead of imread to load images.

Using wrong method names for detection or display.

imread loads the image, detectMultiScale detects faces, and imshow displays the image window.