Resize per channel reasons

[iroilomamnou]

Thanks for sharing this great work. I'm just wondering about the reasons behind resize the image per channel and not resizing it as 3 channels array. I'm referring to this piece of code in the file resize.py.

def resize_single_channel(x_np, output_size):
    s1, s2 = output_size
    img = Image.fromarray(x_np.astype(np.float32), mode='F')
    img = img.resize(output_size, resample=Image.Resampling.BICUBIC)
    return np.asarray(img).clip(0, 255).reshape(s2, s1, 1)
def resize_channels(x, new_size):
    x = [resize_single_channel(x[:, :, idx], new_size) for idx in range(3)]
    x = np.concatenate(x, axis=2).astype(np.uint8)
    return x

I hope this is the way to ask questions here since It's my first time to ask a question on Issues instead of submitting an issue.

Thanks for your understanding.

[GaParmar]

Hi thanks for your interest in this work! We perform the resizing this per channel so that we can use mode="F" which does not quantize the image to 8-bit float and keeps the image values as type float 32.