def when_I_add_the_stream_image_filename_using_add_picture(context, filename):
shapes = context.slide.shapes
with open(test_image(filename), "rb") as f:
stream = BytesIO(f.read())
shapes.add_picture(stream, Inches(1.25), Inches(1.25))
def when_I_assign_shapes_add_picture_to_shape(context):
context.shape = context.shapes.add_picture(
test_image('sonic.gif'), Inches(1), Inches(2)
)
def when_I_add_the_image_filename_using_shapes_add_picture(context, filename):
shapes = context.slide.shapes
shapes.add_picture(test_image(filename), Inches(1.25), Inches(1.25))
def when_I_add_the_stream_image_filename_using_add_picture(context, filename):
shapes = context.slide.shapes
with open(test_image(filename), "rb") as f:
stream = BytesIO(f.read())
shapes.add_picture(stream, Inches(1.25), Inches(1.25))
def when_I_add_the_image_filename_using_shapes_add_picture(context, filename):
shapes = context.slide.shapes
shapes.add_picture(test_image(filename), Inches(1.25), Inches(1.25))
def when_I_assign_shapes_add_picture_to_shape(context):
context.shape = context.shapes.add_picture(
test_image("sonic.gif"), Inches(1), Inches(2)
)
def main(argv):
net_name = ""
train_len = 500
alg = ""
autosave_name = ""
testing_name = ""
# read command line arguments
try:
opts, args = getopt.getopt(argv, "hn:l:c:a:as:t:")
except getopt.GetoptError:
print ("Usage: main.py -n <net file to use> -l <training length>, -c <convert images again>, -a <algorithm to use (GEN, BP)> -s <name for autosaving net> -t <name for auto testing file>")
sys.exit(2)
if not argv:
print ("Usage: main.py -n <net file to use> -l <training length>, -c <convert images again>, -a <algorithm to use (GEN, BP)> -s <name for autosaving net> -t <name for auto testing file>")
sys.exit(2)
for opt, arg in opts:
# print usage
if opt == '-h':
print ("Usage: main.py -n <net file to use> -l <training length>, -c <convert images again>, -a <algorithm to use (GEN, BP)> -s <name for autosaving net> -t <name for auto testing file>")
sys.exit()
# store the name of the net to be loaded
elif opt == "-n":
net_name = arg
# store training length
elif opt == "-l":
train_len = int(arg)
# convert images
elif opt == "-c":
converter.convert_images()
# store the name for the net to be saved
elif opt == "-s":
if arg != "":
autosave_name = arg
else:
print("Invalid input for -s")
# store the algorithm to use
elif opt == "-a":
print(arg)
if arg == "GEN" or arg == "BP":
alg = arg
else:
print ("Non-valid algorithm. Choose either GEN for genetic algorithm or BP for Backpropagation")
sys.exit()
elif opt == "-t":
testing_name = arg
# initialize net
# if a net name was given, load that net
if net_name != "":
net = helpers.load_net(net_name)
elif alg == "":
print ("Neither a previous net or training algorithm was chosen. Try again!")
sys.exit()
elif alg == "GEN":
# train the net using gen alg
net = gen.genetic_train(cfg.POP_SIZE, train_len, testing_name)
# if autosave name was given, save the net
if autosave_name != "":
helpers.save_net(net, autosave_name)
else:
# train the net using BP
net = nn.backprop_train(train_len, testing_name)
# if autosave name was given, save the net
if autosave_name != "":
helpers.save_net(net, autosave_name)
print("Net ready!")
# Ask the user for a command
while True:
training_data = []
print("Choose an action:")
print("Q - Quit")
print("T - Run training data")
print("F - Test a file")
print("S - Save the net")
print("C - Continue training")
print("E - Calculate Error")
choice = raw_input("")
# Exit
if choice in ("Q", "q"):
print("Exiting!")
sys.exit()
# run the training results
elif choice in ("T", "t"):
helpers.training_results(net)
# test a specific file
elif choice in ("F", "f"):
# get file path
test_file = raw_input("input path to file: ")
while test_file == "":
test_file = raw_input("Try again!")
# Check if file is accessible
if not os.access(test_file, os.R_OK):
print("file is not accessible :( ")
else:
helpers.test_image(test_file, net)
elif choice in ("S", "s"):
# Save the net
name = ""
while name == "":
name = raw_input("filename: ")
helpers.save_net(net, name)
elif choice in ("C", "c"):
# prompt the user for parameters
train_len = raw_input("training length? ")
while not train_len.isdigit():
train_len = raw_input("try again! ")
train_len = int(train_len)
alg = raw_input("Which algorithm to use? GEN/BP: ")
while not (alg == "GEN" or alg == "BP"):
alg = raw_input("Try again! GEN/BP: ")
# train the net
if alg == "GEN":
gen.continue_gen(net, train_len, cfg.POP_SIZE)
else:
nn.continue_bp(net, train_len)
elif choice in ("E", "e"):
# if training data is not already loaded, load it
if not training_data:
training_data = helpers.load_training_data()
print("Calculating...")
# print out the total error over training data
print("Total error for net: " + str(gen.net_error(net, training_data)))
