steermomo

import lightgbm as lgb
import numpy as np
from sklearn.model_selection import train_test_split, GridSearchCV
from sklearn.model_selection import StratifiedKFold
from sklearn.metrics import accuracy_score, auc, roc_auc_score
import datetime
import argparse
import pickle
import data_loader
import warnings

steermomo

# Importing core libraries
import numpy as np
import pandas as pd
from time import time
import pprint
import joblib

# Suppressing warnings because of skopt verbosity
import warnings
warnings.filterwarnings("ignore")

steermomo

import qupath.lib.scripting.QP
import qupath.lib.geom.Point2
import qupath.lib.roi.PolygonROI
import qupath.lib.objects.PathAnnotationObject
import qupath.lib.images.servers.ImageServer


//Aperio Image Scope displays images in a different orientation
def rotated = false

steermomo

def classifier(input_shape, kernel_size, pool_size):
    model = Sequential()

    model.add(Convolution3D(16, kernel_size=kernel_size,
                            padding='valid',
                            input_shape=input_shape))
    model.add(Activation('relu'))
    model.add(MaxPooling3D(pool_size=pool_size))
    model.add(Convolution3D(32, kernel_size=kernel_size))
    model.add(Activation('relu'))