volume-visualization/volumes/processing/service/Normalizer.py

import numpy
import logging

logger = logging.getLogger(__name__)


def normalize_image(frames, volumeId):
    logger.debug('volId: %s, float frames detected, normalize them' % volumeId)
    collection_min = frames.min()
    collection_max = frames.max()
    logger.debug('volId: %s, imagesmin: %d, imagesmax: %d' %(volumeId, collection_min, collection_max))

    # due to memory problems, we have to trigger it for each frame
    for frame in frames:
        for frame_slice in frame:
            frame_slice = (frame_slice - collection_min) / (collection_max - collection_min)

    logger.debug('volId: %s, after normalization imagesmin: %d, imagesmax: %d' %(volumeId, frames.min(), frames.max()))