# * mode: image or video (default)
# * custom: False (default). If you wish to extend the FaceDetect class, specify the method that it needs to execute
# * method: call native callback methods during detection or bypass with a custom method
# * draw: draws the detection on the canvas if set to True (default)
# * print: prints the face locations and labels on the console
# * face-extraction: extracts captures of the faces into their own images. Applicable only to mode image
# * face-features: Draws the specified face features. Off by default. Pass the list ['face'] to draw the whole face
# * known-faces: Setting need for facial recognition when 'method' is set to 'recognize'
# It is a dictionary of face labels and image paths associated.
# For example: {'John': 'person1.png', 'Jane': 'person2.png'}
#
# Passing settings (the default ones are being passed for comparison purposes with main.py)
facedetector = FaceDetect({
'mode': 'video',
'custom': False,
'method': 'detect',
'draw': True
})
try:
# When the start method is not given an image or video path, it starts the webcam
# For Image file: facedetector.start('<path to image file>')
# For Video: facedetector.start('<path to video file>')
# Press 'q' to exit
facedetector.start()
# FaceDetect always generates a FaceDetect Exception
except Exception as error:
print(error)
# Initialize FaceDetect
# Params:
# - settings (optional): Dictionary with settings to be passed to the FaceDetector
# * mode: image or video (default)
# * custom: False (default). If you wish to extend the FaceDetect class, specify the method that it needs to execute
# * method: call native callback methods during detection or bypass with a custom method
# * draw: draws the detection on the canvas if set to True (default)
# * print: prints the face locations and labels on the console
# * face-extraction: extracts captures of the faces into their own images. Applicable only to mode image
# * face-features: Draws the specified face features. Off by default. Pass the list ['face'] to draw the whole face
# * known-faces: Setting need for facial recognition when 'method' is set to 'recognize'
# It is a dictionary of face labels and image paths associated.
# For example: {'John': 'person1.png', 'Jane': 'person2.png'}
#
facedetector = FaceDetect({'mode': 'image', 'face-features': ['face']})
# you can also choose to draw particular features such as:
# 'chin', 'left_eye', 'right_eye', 'left_eyebrow', 'right_eyebrow', 'nose_bridge', 'nose_tip', 'top_lip', 'bottom_lip'
try:
# When the start method is not given an image or video path, it starts the webcam
# For Image file: facedetector.start('<path to image file>')
# For Video: facedetector.start('<path to video file>')
# Press 'q' to exit
facedetector.start('resources/people.jpg')
# FaceDetect always generates a FaceDetect Exception
except Exception as error:
print(error)
# Import the FaceDetect class
from FaceDetect.facedetect import FaceDetect
# Initialize FaceDetect
# Params:
# - settings (optional): Dictionary with settings to be passed to the FaceDetector
# * mode: image or video (default)
# * custom: False (default). If you wish to extend the FaceDetect class, specify the method that it needs to execute
# * method: call native callback methods during detection or bypass with a custom method
# * draw: draws the detection on the canvas if set to True (default)
# * print: prints the face locations and labels on the console
# * face-extraction: extracts captures of the faces into their own images. Applicable only to mode image
# * face-features: Draws the specified face features. Off by default. Pass the list ['face'] to draw the whole face
# * known-faces: Setting need for facial recognition when 'method' is set to 'recognize'
# It is a dictionary of face labels and image paths associated.
# For example: {'John': 'person1.png', 'Jane': 'person2.png'}
#
facedetector = FaceDetect({'mode': 'image'})
try:
# When the start method is not given an image or video path, it starts the webcam
# For Image file: facedetector.start('<path to image file>')
# For Video: facedetector.start('<path to video file>')
# Press 'q' to exit
facedetector.start('resources/people.jpg')
# FaceDetect always generates a FaceDetect Exception
except Exception as error:
print(error)
# Import the FaceDetect class
from FaceDetect.facedetect import FaceDetect
# Initialize FaceDetect
# Params:
# - settings (optional): Dictionary with settings to be passed to the FaceDetector
# * mode: image or video (default)
# * custom: False (default). If you wish to extend the FaceDetect class, specify the method that it needs to execute
# * method: call native callback methods during detection or bypass with a custom method
# * draw: draws the detection on the canvas if set to True (default)
# * print: prints the face locations and labels on the console
# * face-extraction: extracts captures of the faces into their own images. Applicable only to mode image
# * face-features: Draws the specified face features. Off by default. Pass the list ['face'] to draw the whole face
# * known-faces: Setting need for facial recognition when 'method' is set to 'recognize'
# It is a dictionary of face labels and image paths associated.
# For example: {'John': 'person1.png', 'Jane': 'person2.png'}
#
facedetector = FaceDetect()
try:
# When the start method is not given an image or video path, it starts the webcam
# For Image file: facedetector.start('<path to image file>')
# For Video: facedetector.start('<path to video file>')
# Press 'q' to exit
facedetector.start()
# FaceDetect always generates a FaceDetect Exception
except Exception as error:
print(error)
# * custom: False (default). If you wish to extend the FaceDetect class, specify the method that it needs to execute
# * method: call native callback methods during detection or bypass with a custom method
# * draw: draws the detection on the canvas if set to True (default)
# * print: prints the face locations and labels on the console
# * face-extraction: extracts captures of the faces into their own images. Applicable only to mode image
# * face-features: Draws the specified face features. Off by default. Pass the list ['face'] to draw the whole face
# * known-faces: Setting need for facial recognition when 'method' is set to 'recognize'
# It is a dictionary of face labels and image paths associated.
# For example: {'John': 'person1.png', 'Jane': 'person2.png'}
#
# Set the method to recognize and provide a dictionary of known faces names and image path
facedetector = FaceDetect({
'method': 'recognize',
'known-faces': {
'John': 'resources/person1.png',
'Jane': 'resources/person2.png'
}
})
try:
# When the start method is not given an image or video path, it starts the webcam
# For Image file: facedetector.start('<path to image file>')
# For Video: facedetector.start('<path to video file>')
# Press 'q' to exit
facedetector.start()
# FaceDetect always generates a FaceDetect Exception
except Exception as error:
print(error)
# Import the FaceDetect class
from FaceDetect.facedetect import FaceDetect
# Initialize FaceDetect
# Params:
# - settings (optional): Dictionary with settings to be passed to the FaceDetector
# * mode: image or video (default)
# * custom: False (default). If you wish to extend the FaceDetect class, specify the method that it needs to execute
# * method: call native callback methods during detection or bypass with a custom method
# * draw: draws the detection on the canvas if set to True (default)
# * print: prints the face locations and labels on the console
# * face-extraction: extracts captures of the faces into their own images. Applicable only to mode image
# * face-features: Draws the specified face features. Off by default. Pass the list ['face'] to draw the whole face
# * known-faces: Setting need for facial recognition when 'method' is set to 'recognize'
# It is a dictionary of face labels and image paths associated.
# For example: {'John': 'person1.png', 'Jane': 'person2.png'}
#
facedetector = FaceDetect({'mode': 'image', 'face-extraction': True})
try:
# When the start method is not given an image or video path, it starts the webcam
# For Image file: facedetector.start('<path to image file>')
# For Video: facedetector.start('<path to video file>')
# Press 'q' to exit
facedetector.start('resources/people.jpg')
# FaceDetect always generates a FaceDetect Exception
except Exception as error:
print(error)
# * custom: False (default). If you wish to extend the FaceDetect class, specify the method that it needs to execute
# * method: call native callback methods during detection or bypass with a custom method
# * draw: draws the detection on the canvas if set to True (default)
# * print: prints the face locations and labels on the console
# * face-extraction: extracts captures of the faces into their own images. Applicable only to mode image
# * face-features: Draws the specified face features. Off by default. Pass the list ['face'] to draw the whole face
# * known-faces: Setting need for facial recognition when 'method' is set to 'recognize'
# It is a dictionary of face labels and image paths associated.
# For example: {'John': 'person1.png', 'Jane': 'person2.png'}
#
# Set the method to recognize and provide a dictionary of known faces names and image path
facedetector = FaceDetect({
'mode': 'image',
'method': 'recognize',
'known-faces': {
'John': 'resources/person1.png',
'Jane': 'resources/person2.png'
}
})
try:
# When the start method is not given an image or video path, it starts the webcam
# For Image file: facedetector.start('<path to image file>')
# For Video: facedetector.start('<path to video file>')
# Press 'q' to exit
facedetector.start('resources/people.jpg')
# FaceDetect always generates a FaceDetect Exception
except Exception as error:
print(error)