def start():
config = DataConfig()
histories = sorted(glob.glob(config.history_location + "*.pickle"))
data = {}
for hist in histories:
file = open(hist, 'rb')
h = pickle.loads(pickle.load(file))
for k, v in h.items():
if k not in data.keys():
data[k] = []
for item in v:
data[k].append(item)
for i, kv in enumerate(data.items()):
plt.subplot(1, len(data), i + 1)
plt.title(kv[0])
plt.plot(kv[1])
plt.show()
def test():
config = ModelConfig()
data = get_audio_data(config, '../data/audio/train',
'../data/audio/train_wav')
data_config = DataConfig()
X1, X2, labels = get_dataset(data_config, config)
img0 = img_to_array(img0)
img1 = img_to_array(img1)
img0 = rgb_to_hsv(img0)
img1 = rgb_to_hsv(img1)
img = img1[:, :, 2] - img0[:, :, 2]
img = rescale_intensity(img,
in_range=(-255, 255),
out_range=(0, 255))
img = np.array(img, dtype=np.uint8)
X[i - num_channels, :, :, j] = img
return X, np.array(df["angle"].iloc[num_channels:])
if __name__ == "__main__":
config = DataConfig()
data_path = config.data_path
row, col = config.img_height, config.img_width
num_channels = config.num_channels
# print "Pre-processing phase 1 data..."
# X_train, y_train = make_hsv_grayscale_diff_data("data/train_round1.txt", 4)
# np.save("{}/X_train_round1_hsv_gray_diff_ch4".format(data_path), X_train)
# np.save("{}/y_train_round1_hsv_gray_diff_ch4".format(data_path), y_train)
# X_val, y_val = make_hsv_grayscale_diff_data("data/val_round1.txt", 4)
# np.save("{}/X_train_round1_hsv_gray_diff_ch4".format(data_path), X_val)
# np.save("{}/y_train_round1_hsv_gray_diff_ch4".format(data_path), y_val)
print "Pre-processing phase 2 data..."
for i in range(1, 6):
''' Data preparation '''
# coding: utf-8
# Setup
import pandas as pd
import itertools
import pickle
from config import DataConfig
# Load data
data_config = DataConfig()
train_df = pd.read_csv(data_config.data_source + "/train.all",
sep="\t",
engine='python',
header=None,
skiprows=0,
names=[
"Class", "Text", "Phone_CZ", "Phone_EN", "Phone_HU",
"Phone_RU", "Embed"
])
test_df = pd.read_csv(data_config.data_source + "/dev.all",
sep="\t",
engine='python',
header=None,
skiprows=0,
names=[
"Class", "Text", "Phone_CZ", "Phone_EN", "Phone_HU",