test.py

from keras.models import Model
from keras.layers import Input, Dense, Dropout, Flatten, Conv2D, MaxPooling2D, BatchNormalization
from keras.callbacks import ModelCheckpoint, EarlyStopping, TensorBoard
from PIL import Image
import numpy as np
import csv


in1 = Input((60, 200, 3))

print("Reading training data...")
traincsv = open('./data/56_imitate_train_set/len_train.csv', 'r', encoding = 'utf8')

'''
for row in csv.reader(traincsv):
    tmp = [np.array(Image.open("./data/56_imitate_train_set/" + '{0:05}'.format(int(row[0])) + ".jpg"))/255.0]

train_data = np.stack(tmp)
'''


train_data = np.stack([np.array(Image.open("./data/56_imitate_train_set/" + '{0:05}'.format(int(row[0])) + ".jpg"))/255.0 for row in csv.reader(traincsv)])