def estimateBackground():
"""
Example of a face detection background estimation.
"""
image = VLImage.load(filename=EXAMPLE_4)
faceEngine = VLFaceEngine()
detector = faceEngine.createFaceDetector(DetectorType.FACE_DET_V3)
backgroundEstimator = faceEngine.createFaceDetectionBackgroundEstimator()
faceDetection = detector.detectOne(image)
#: single estimation
imageWithFaceDetection = ImageWithFaceDetection(image, faceDetection.boundingBox)
background = backgroundEstimator.estimate(imageWithFaceDetection)
pprint.pprint(background)
image2 = VLImage.load(filename=EXAMPLE_4)
faceDetection2 = detector.detectOne(image2)
#: batch estimation
imageWithFaceDetectionList = [
ImageWithFaceDetection(image, faceDetection.boundingBox),
ImageWithFaceDetection(image2, faceDetection2.boundingBox),
]
backgrounds = backgroundEstimator.estimateBatch(imageWithFaceDetectionList)
pprint.pprint(backgrounds)
async def asyncEstimateBackground():
"""
Example of an async background estimation.
"""
image = VLImage.load(filename=EXAMPLE_4)
faceEngine = VLFaceEngine()
detector = faceEngine.createFaceDetector(DetectorType.FACE_DET_V3)
backgroundEstimator = faceEngine.createFaceDetectionBackgroundEstimator()
faceDetection = detector.detectOne(image)
# async estimation
imageWithFaceDetection = ImageWithFaceDetection(image, faceDetection.boundingBox)
backgrounds = await backgroundEstimator.estimate(imageWithFaceDetection, asyncEstimate=True)
pprint.pprint(backgrounds.asDict())
# run tasks and get results
task1 = backgroundEstimator.estimate(imageWithFaceDetection, asyncEstimate=True)
task2 = backgroundEstimator.estimate(imageWithFaceDetection, asyncEstimate=True)
for task in (task1, task2):
pprint.pprint(task.get().asDict())
