Function load_image

scripts/convert_consistency_decoder.py:193–211

(uri, size=None, center_crop=False)

def load_image(uri, size=None, center_crop=False):
    import numpy as np
    from PIL import Image

    image = Image.open(uri)
    if center_crop:
        image = image.crop(
            (
                (image.width - min(image.width, image.height)) // 2,
                (image.height - min(image.width, image.height)) // 2,
                (image.width + min(image.width, image.height)) // 2,
                (image.height + min(image.width, image.height)) // 2,
            )
        )
    if size is not None:
        image = image.resize(size)
    image = torch.tensor(np.array(image).transpose(2, 0, 1)).unsqueeze(0).float()
    image = image / 127.5 - 1.0
    return image


class TimestepEmbedding_(nn.Module):