def main():
tl.check_arguments(sys.argv, 1, "You have to specify settings file!\n./classify.py settings_file")
settings_filename = sys.argv[1]
settings = tl.load_settings(settings_filename)
caffe_prototxt = settings["caffe_prototxt"]
caffe_model = settings["caffe_model"]
test_list = settings["test_list"]
caffe.set_mode_gpu()
net = caffe.Net(caffe_prototxt, caffe_model, caffe.TEST)
transformer = create_transformer(net)
img_test_names, img_test_labels = tl.read_img_names_from_csv(test_list,
skip_header=False,
delimiter=',')
submission_file, confusion_matrix, accuracy = classify_images(net,
transformer,
img_test_names,
img_test_labels,
settings)
if (settings["print_csv"]):
print "Results written to " + submission_file
print "Accuracy: " + str(accuracy)
# Confusion matrix
if (settings["conf_matrix"]):
plt.figure(figsize=(2,2), dpi=200)
plt.clf()
plt.imshow(confusion_matrix, norm=LogNorm())
#plt.colorbar()
plt.savefig(settings["conf_matrix_path"])
def main():
tl.check_arguments(sys.argv, 1, "You have to specify settings file!\n./train.py settings_file")
settings_filename = sys.argv[1]
settings = tl.load_settings(settings_filename)
train_id = tl.generate_unique_id()
settings = modify_solver(train_id, settings)
caffe_stream = io.StringIO()
with tl.redirect_caffe_log(caffe_stream):
caffe.set_mode_gpu()
prepare_data(settings)
solver = prepare_model(settings)
train_loss, duration, iteration = train_model(solver, settings)
log(solver, train_loss, duration, iteration, caffe_stream, settings)
