コード例 #1
0
def strongTransform(parameters, data=None, target=None):
    assert ((data is not None) or (target is not None))
    data, target = transformsgpu.mix(mask = parameters["Mix"], data = data, target = target)
    data, target = transformsgpu.colorJitter(colorJitter = parameters["ColorJitter"], img_mean = torch.from_numpy(IMG_MEAN.copy()).cuda(), data = data, target = target)
    data, target = transformsgpu.gaussian_blur(blur = parameters["GaussianBlur"], data = data, target = None)
    data, target = transformsgpu.flip(flip = parameters["flip"], data = data, target = target)
    return data, target
コード例 #2
0
def augmentationTransform(parameters,
                          data=None,
                          target=None,
                          probs=None,
                          jitter_vale=0.4,
                          min_sigma=0.2,
                          max_sigma=2.,
                          ignore_label=255):
    """

    Args:
        parameters: dictionary with the augmentation configuration
        data: BxCxWxH input data to augment
        target: BxWxH labels to augment
        probs: BxWxH probability map to augment
        jitter_vale:  jitter augmentation value
        min_sigma: min sigma value for blur
        max_sigma: max sigma value for blur
        ignore_label: value for ignore class

    Returns:
            augmented data, target, probs
    """
    assert ((data is not None) or (target is not None))
    if "Mix" in parameters:
        data, target, probs = transformsgpu.mix(mask=parameters["Mix"],
                                                data=data,
                                                target=target,
                                                probs=probs)

    if "RandomScaleCrop" in parameters:
        data, target, probs = transformsgpu.random_scale_crop(
            scale=parameters["RandomScaleCrop"],
            data=data,
            target=target,
            probs=probs,
            ignore_label=ignore_label)
    if "flip" in parameters:
        data, target, probs = transformsgpu.flip(flip=parameters["flip"],
                                                 data=data,
                                                 target=target,
                                                 probs=probs)

    if "ColorJitter" in parameters:
        data, target, probs = transformsgpu.colorJitter(
            colorJitter=parameters["ColorJitter"],
            data=data,
            target=target,
            probs=probs,
            s=jitter_vale)
    if "GaussianBlur" in parameters:
        data, target, probs = transformsgpu.gaussian_blur(
            blur=parameters["GaussianBlur"],
            data=data,
            target=target,
            probs=probs,
            min_sigma=min_sigma,
            max_sigma=max_sigma)

    if "Grayscale" in parameters:
        data, target, probs = transformsgpu.grayscale(
            grayscale=parameters["Grayscale"],
            data=data,
            target=target,
            probs=probs)
    if "Solarize" in parameters:
        data, target, probs = transformsgpu.solarize(
            solarize=parameters["Solarize"],
            data=data,
            target=target,
            probs=probs)

    return data, target, probs