Multiple faces
In this exercise, you will detect multiple faces in an image and show them individually. Think of this as a way to create a dataset of your own friends' faces!

friends_image
.The Cascade
of classifiers class from feature
module has already been imported, as well as the show_detected_face()
function which is used to display the face marked in the image and crop it so it can be shown separately.
This exercise is part of the course
Image Processing in Python
Exercise instructions
- Load the trained file
.lbp_frontal_face_cascade_filename()
. from thedata
module. - Initialize the detector cascade with trained file.
- Detect the faces in the image, setting a
scale_factor
of 1.2 andstep_ratio
of 1.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Load the trained file from data
trained_file = ____.___()
# Initialize the detector cascade
detector = ____
# Detect faces with scale factor to 1.2 and step ratio to 1
detected = detector.____(img=friends_image,
scale_factor=____,
step_ratio=____,
min_size=(10, 10),
max_size=(200, 200))
# Show the detected faces
show_detected_face(friends_image, detected)