def detectHumans():
"""
Redetect human body on images.
"""
faceEngine = VLFaceEngine()
detector = faceEngine.createHumanDetector()
imageWithOneHuman = VLImage.load(filename=EXAMPLE_O)
detection = detector.detectOne(imageWithOneHuman, detectLandmarks=False)
pprint.pprint(detector.redetectOne(image=imageWithOneHuman,
bBox=detection))
pprint.pprint(
detector.redetectOne(image=imageWithOneHuman,
bBox=detection.boundingBox.rect))
imageWithSeveralHumans = VLImage.load(filename=EXAMPLE_SEVERAL_FACES)
severalHumans = detector.detect([imageWithSeveralHumans],
detectLandmarks=False)
pprint.pprint(
detector.redetect(images=[
ImageForRedetection(
imageWithSeveralHumans,
[human.boundingBox.rect for human in severalHumans[0]]),
ImageForRedetection(imageWithOneHuman,
[detection.boundingBox.rect]),
ImageForRedetection(imageWithOneHuman, [Rect(0, 0, 1, 1)]),
]))
def detectHumanBody():
"""
Detect one human body on an image.
"""
faceEngine = VLFaceEngine()
detector = faceEngine.createHumanDetector()
imageWithOneHuman = VLImage.load(filename=EXAMPLE_O)
pprint.pprint(
detector.detectOne(imageWithOneHuman, detectLandmarks=False).asDict())
imageWithSeveralHumans = VLImage.load(filename=EXAMPLE_SEVERAL_FACES)
pprint.pprint(
detector.detectOne(imageWithSeveralHumans,
detectLandmarks=False).asDict())
severalHumans = detector.detect([imageWithSeveralHumans],
detectLandmarks=True)
pprint.pprint([human.asDict() for human in severalHumans[0]])
imageWithoutHuman = VLImage.load(filename=EXAMPLE_WITHOUT_FACES)
pprint.pprint(
detector.detectOne(imageWithoutHuman, detectLandmarks=False) is None)
severalHumans = detector.detect(
[ImageForDetection(imageWithSeveralHumans, Rect(1, 1, 300.0, 300.0))])
pprint.pprint(severalHumans)
def createWarp():
"""
Create human body warp from human detection.
"""
faceEngine = VLFaceEngine()
image = VLImage.load(filename=EXAMPLE_O)
detector = faceEngine.createHumanDetector()
humanDetection = detector.detectOne(image)
warper = faceEngine.createHumanWarper()
warp = warper.warp(humanDetection)
pprint.pprint(warp.warpedImage.rect)
async def asyncDetectHumanBody():
"""
Async detect one human body on an image.
"""
faceEngine = VLFaceEngine()
detector = faceEngine.createHumanDetector()
imageWithOneHuman = VLImage.load(filename=EXAMPLE_O)
pprint.pprint(detector.detectOne(imageWithOneHuman, detectLandmarks=False).asDict())
imageWithSeveralHumans = VLImage.load(filename=EXAMPLE_SEVERAL_FACES)
human = await detector.detectOne(imageWithSeveralHumans, detectLandmarks=False, asyncEstimate=True)
pprint.pprint(human.asDict())
task1 = detector.detect([imageWithSeveralHumans], detectLandmarks=True, asyncEstimate=True)
task2 = detector.detect([imageWithSeveralHumans], detectLandmarks=True, asyncEstimate=True)
for task in (task1, task2):
pprint.pprint(task.get())
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 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)