def main(argv):
"""
Main function, check module docstring.
"""
(N_TRAIN, T, delete_node_period, max_edge_age) = (1000, 0.6, 100, 30)
if len(argv) >= 2:
N_TRAIN = int(argv[1])
if len(argv) >= 3:
T = int(argv[2])
if len(argv) >= 4:
delete_node_period = int(argv[3])
if len(argv) >= 5:
max_edge_age = int(argv[4])
if len(argv) >= 6:
print("""Usage: ./train_charades.py [N_train] [threshold]
[delete_node period] [max_edge_age]""")
raise IndexError
im_write = True
dumpfile = 'outputs/soinn{0}_{1}_{2}_{3}.dump'.format(
N_TRAIN, delete_node_period, max_edge_age, int(100 * T))
# If a SOINN node already exist for those parameters, use it.
try:
soinn_i = joblib.load(dumpfile)
except:
# If no SOINN already exist, define the dataset according to SOINN parameters
dataset, video_used = prepare_dataset(N_TRAIN, T)
with open('video_used_{}_{}'.format(N_TRAIN, int(100 * T)), 'w') as f:
for title in video_used:
f.write('{}\n'.format(title))
print('New SOINN is created.')
soinn_i = Soinn(delete_node_period=delete_node_period,
max_edge_age=max_edge_age)
learning(soinn_i, dataset)
soinn_i.print_info()
soinn_i.save(dumpfile)
if im_write:
dir_name = "clusters_{0}_{1}_{2}_{3}".format(N_TRAIN,
delete_node_period,
max_edge_age,
int(100 * T))
if not os.path.exists(dir_name):
os.makedirs(dir_name)
os.chdir(dir_name)
for i, node in enumerate(soinn_i.nodes):
print(node)
draw_pose(node, im_write, i, im_show=False)
plt.xlim(0,28)
plt.ylim(0,28)
plt.pcolor(Z)
plt.title("title=%s"%(title), size=8)
plt.gray()
plt.tick_params(labelbottom="off")
plt.tick_params(labelleft="off")
if __name__ == '__main__':
dataset = prepare_dataset()
N_TRAIN = 5000
delete_node_period = 100
max_edge_age = 30
x_train, y_train, x_test, y_test = split_dataset(dataset, N_TRAIN)
dumpfile = 'soinn{0}_{1}_{2}.dump'.format(N_TRAIN,
delete_node_period,
max_edge_age)
try:
import joblib
soinn_i = joblib.load(dumpfile)
except:
print('New SOINN is created.')
soinn_i = Soinn(delete_node_period=delete_node_period,
max_edge_age=max_edge_age)
learning(soinn_i, x_train, y_train)
evaluate(soinn_i, x_test, y_test)
#visualise(soinn_i.nodes)
soinn_i.print_info()
soinn_i.save(dumpfile)
Z = Z[::-1, :] # flip vertical
plt.xlim(0, 28)
plt.ylim(0, 28)
plt.pcolor(Z)
plt.title("title=%s" % (title), size=8)
plt.gray()
plt.tick_params(labelbottom="off")
plt.tick_params(labelleft="off")
if __name__ == '__main__':
dataset = prepare_dataset()
N_TRAIN = 5000
delete_node_period = 100
max_edge_age = 30
x_train, y_train, x_test, y_test = split_dataset(dataset, N_TRAIN)
dumpfile = 'soinn{0}_{1}_{2}.dump'.format(N_TRAIN, delete_node_period,
max_edge_age)
try:
import joblib
soinn_i = joblib.load(dumpfile)
except:
print('New SOINN is created.')
soinn_i = Soinn(delete_node_period=delete_node_period,
max_edge_age=max_edge_age)
learning(soinn_i, x_train, y_train)
evaluate(soinn_i, x_test, y_test)
#visualise(soinn_i.nodes)
soinn_i.print_info()
soinn_i.save(dumpfile)