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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!

A group of 7 friends
Image preloaded as 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.

Diese Übung ist Teil des Kurses

Image Processing in Python

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Anleitung zur Übung

  • Load the trained file .lbp_frontal_face_cascade_filename(). from the data module.
  • Initialize the detector cascade with trained file.
  • Detect the faces in the image, setting a scale_factor of 1.2 and step_ratio of 1.

Interaktive Übung

Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.

# 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)
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