Пример #1
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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)
Пример #2
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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)
Пример #3
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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)