def estimateAttributes():
"""
Estimate human descriptor.
"""
image = VLImage.load(filename=EXAMPLE_SEVERAL_FACES)
faceEngine = VLFaceEngine()
detector = faceEngine.createHumanDetector()
humanDetection = detector.detect([image])
warper = faceEngine.createHumanWarper()
warp1 = warper.warp(humanDetection[0][0])
warp2 = warper.warp(humanDetection[0][1])
estimator = faceEngine.createBodyAttributesEstimator()
pprint.pprint(estimator.estimate(warp1.warpedImage).asDict())
pprint.pprint(
estimator.estimateBatch([warp1.warpedImage, warp2.warpedImage]))
aggregated = estimator.aggregate(
estimator.estimateBatch([warp1.warpedImage, warp2.warpedImage]))
pprint.pprint(aggregated)
async def asyncEstimateAttribures():
"""
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)
estimator = faceEngine.createBodyAttributesEstimator()
pprint.pprint(await
estimator.estimateBatch([warp.warpedImage, warp.warpedImage],
asyncEstimate=True))
# run tasks and get results
task1 = estimator.estimate(warp.warpedImage, asyncEstimate=True)
task2 = estimator.estimate(warp.warpedImage, asyncEstimate=True)
for task in (task1, task2):
pprint.pprint(task.get().asDict())