async def asyncEstimateDescriptor():
"""
Async estimate face descriptor.
"""
image = VLImage.load(filename=EXAMPLE_O)
faceEngine = VLFaceEngine()
detector = faceEngine.createHumanDetector()
humanDetection = detector.detectOne(image)
warper = faceEngine.createHumanWarper()
warp = warper.warp(humanDetection)
extractor = faceEngine.createHumanDescriptorEstimator()
pprint.pprint(await extractor.estimateDescriptorsBatch(
[warp.warpedImage, warp.warpedImage], asyncEstimate=True))
# run tasks and get results
task1 = extractor.estimate(warp.warpedImage, asyncEstimate=True)
task2 = extractor.estimate(warp.warpedImage, asyncEstimate=True)
for task in (task1, task2):
pprint.pprint(task.get().asDict())
def estimateDescriptor():
"""
Estimate human descriptor.
"""
image = VLImage.load(filename=EXAMPLE_O)
faceEngine = VLFaceEngine()
detector = faceEngine.createHumanDetector()
humanDetection = detector.detectOne(image)
warper = faceEngine.createHumanWarper()
warp = warper.warp(humanDetection)
extractor = faceEngine.createHumanDescriptorEstimator()
pprint.pprint(extractor.estimate(warp.warpedImage))
pprint.pprint(
extractor.estimateDescriptorsBatch(
[warp.warpedImage, warp.warpedImage]))
batch, aggregateDescriptor = extractor.estimateDescriptorsBatch(
[warp.warpedImage, warp.warpedImage], aggregate=True)
pprint.pprint(batch)
pprint.pprint(aggregateDescriptor)
