(obj)
return img
Convert an output tensor from BigGAN in a list of images.
        Params:
            obj: tensor or numpy array of shape (batch_size, channels, height, width)
        Output:
            list of Pillow Images of size (height, width)
Convert an output tensor from BigGAN in a list of images.
        Params:
            obj: tensor or numpy array of shape (batch_size, channels, height, width)
        Output:
            list of Pillow Images of size (height, width)
Convert an output tensor from BigGAN in a list of images . Params : obj : tensor or numpy array of shape ( batch_size channels height width ) Output : list of Pillow Images of size ( height width )
def convert_to_images(obj):
    """ Convert an output tensor from BigGAN in a list of images.
        Params:
            obj: tensor or numpy array of shape (batch_size, channels, height, width)
        Output:
            list of Pillow Images of size (height, width)
    """
    try:
        import PIL
    except ImportError:
        raise ImportError("Please install Pillow to use images: pip install Pillow")

    if not isinstance(obj, np.ndarray):
        obj = obj.detach().numpy()

    obj = obj.transpose((0, 2, 3, 1))
    obj = np.clip(((obj + 1) / 2.0) * 256, 0, 255)

    img = []
    for i, out in enumerate(obj):
        out_array = np.asarray(np.uint8(out), dtype=np.uint8)
        img.append(PIL.Image.fromarray(out_array))
    return img
def convert_to_images ( obj ) : try : import PIL except ImportError : raise ImportError ( "Please install Pillow to use images: pip install Pillow" ) if not isinstance ( obj , np . ndarray ) : obj = obj . detach ( ) . numpy ( ) obj = obj . transpose ( ( 0 , 2 , 3 , 1 ) ) obj = np . clip ( ( ( obj + 1 ) / 2.0 ) * 256 , 0 , 255 ) img = [ ] for i , out in enumerate ( obj ) : out_array = np . asarray ( np . uint8 ( out ) , dtype = np . uint8 ) img . append ( PIL . Image . fromarray ( out_array ) ) return img