import json

import matplotlib.pyplot as plt

import numpy as np

from bottleneck import Bottleneck

from cnn import build_cnn

from identification import get_scores, calc_metrics

WEIGHTS_DIR = 'data/weights/'

BATCH_SIZE = 32

dev_x = np.load('data/dev_x.npy')

with open('data/meta.json', 'r') as f:

meta = json.load(f)

model = build_cnn(227, meta['n_subjects'])

weights_to_load = WEIGHTS_DIR + 'weights.best.h5'

model.load_weights(weights_to_load)

bottleneck = Bottleneck(model, ~1)

dev_y = bottleneck.predict(dev_x, batch_size=BATCH_SIZE)

protocol = np.load('data/dev_protocol.npy')

tsc, isc = get_scores(dev_y, protocol)

eer, fars, frrs, dists = calc_metrics(tsc, isc)

print('EER: {}'.format(eer * 100))

plt.figure()

plt.hist(tsc, 20, color='g', normed=True, alpha=0.3)

plt.hist(isc, 20, color='r', normed=True, alpha=0.3)

plt.figure()

plt.loglog(fars, frrs)

plt.show()