import os

INFERENCE_GPUS = [8]

CENTER_SIZE = 2000  # The effective patch size.

BORDER_SIZE = 100  # The boarder size containing surrounding information.

PATCH_SIZE = CENTER_SIZE + 2 * BORDER_SIZE

format_mapping = {

    'tif': 'OpenSlide',

    'svs': 'OpenSlide',

    'ndpi': 'OpenSlide',

    'scn': 'OpenSlide',

    'mrxs': 'OpenSlide',

    'bif': 'OpenSlide',

    'vms': 'OpenSlide',

}

MODEL_NAME = 'stomach'

INPUT_KEY = 'output'

PREDICT_KEY = 'output'

TF_SERVING_HOST = os.environ.get('TF_SERVING_HOST', '127.0.0.1')

TF_SERVING_PORT = int(os.environ.get('TF_SERVING_PORT', 9000))

TEMP_DIR = './temp/'  # Where to save the predicted patches.

THUMBNAIL_RATIO = 10  # Down-sample ratio from the predictions to the thumbnail.

KEEP_TEMP = False  # Whether to keep the predicted patches after generated the thumbnail.

DO_POST_PROCESSING = False  # Whether to post-process the predicted patches.

FILTER_KERNEL = 9  # The kernel size for post-processing.