def __init__(self, shape, mean=pr.BGR_IMAGENET_MEAN):
super(PreprocessImage, self).__init__()
self.add(pr.ResizeImage(shape))
self.add(pr.CastImage(float))
if mean is None:
self.add(pr.NormalizeImage())
else:
self.add(pr.SubtractMeanImage(mean))
def __init__(self, model, colors=None):
super(PostprocessSegmentation, self).__init__()
self.add(PreprocessImage())
self.add(pr.ExpandDims(0))
self.add(pr.Predict(model))
self.add(pr.Squeeze(0))
self.add(Round())
self.add(MasksToColors(model.output_shape[-1], colors))
self.add(pr.DenormalizeImage())
self.add(pr.CastImage('uint8'))
self.add(pr.ShowImage())
def __init__(self, model, colors=None):
super(PostprocessSegmentation, self).__init__()
self.add(pr.UnpackDictionary(['image_path']))
self.add(pr.LoadImage())
self.add(pr.ResizeImage(model.input_shape[1:3]))
self.add(pr.ConvertColorSpace(pr.RGB2BGR))
self.add(pr.SubtractMeanImage(pr.BGR_IMAGENET_MEAN))
self.add(pr.ExpandDims(0))
self.add(pr.Predict(model))
self.add(pr.Squeeze(0))
self.add(Round())
self.add(MasksToColors(model.output_shape[-1], colors))
self.add(pr.DenormalizeImage())
self.add(pr.CastImage('uint8'))
self.add(pr.ShowImage())
def __init__(self, shape=(48, 48)):
self.shape = shape
super(PostrocessEigenFace, self).__init__()
self.add(pe.MinMaxNormalization(255.0))
self.add(pe.Reshape(shape))
self.add(pr.CastImage('uint8'))
def __init__(self):
super(PostProcessImage, self).__init__()
self.add(pr.AddMeanImage(pr.BGR_IMAGENET_MEAN))
self.add(pr.CastImage('uint8'))
self.add(pr.ConvertColorSpace(pr.BGR2RGB))
def __init__(self, num_classes, colors=None):
super(PostprocessSegmentationIds, self).__init__()
self.add(MasksToColors(num_classes, colors))
self.add(pr.DenormalizeImage())
self.add(pr.CastImage('uint8'))