new_contents: import csv
  import cv2
  import numpy as np
  
  lines = []
  with open('./data/P3Data_3/driving_log.csv') as csvfile:
  	reader = csv.reader(csvfile)
  	for line in reader:
  		lines.append(line)
  
  center_images=[]
  measurements = []
  for line in lines:
  		source_path = line[0]
  		filename = source_path.split('\\')[-1]
  		current_path = './data/P3Data_3/IMG/' + filename
  		print (current_path)
  		center_image = cv2.imread(current_path)
  		center_images.append(center_image)
  		height, width, channels = center_image.shape
  		print (height, width, channels)
  		measurement = float(line[3])
  		measurements.append(measurement)
  
  X_train = np.array(center_images)
  y_train = np.array(measurements)
  
  from keras.models import Sequential
  from keras.layers import Flatten, Dense
  
  model = Sequential()
  model.add(Flatten(input_shape=(160, 320, 3)))
  model.add(Dense(1))
  
  model.compile(loss='mse', optimizer='adam')
  model.fit(X_train, y_train, validation_split=0.2, shuffle=True, nb_epoch=7)
  model.save('model_3.h5')
  
subject: add trial3.py