def preprocess()

in deployment/handler.py [0:0]

• 18 lines of code
• 2 McCabe index (conditional complexity)

    def preprocess(self, data):
        """
        Scales and normalizes a PIL image for an U-net model
        """
        image = data[0].get("data")
        if image is None:
            image = data[0].get("body")

        image_transform = transforms.Compose(
            [
                # must be consistent with model training
                transforms.Resize((96, 128)),
                transforms.ToTensor(),
                # default statistics from imagenet
                transforms.Normalize(
                    mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
                ),
            ]
        )
        image = Image.open(io.BytesIO(image)).convert(
            "RGB"
        )  # in case of an alpha channel
        image = image_transform(image).unsqueeze_(0)
        return image