def without_ngraph(self, l, config=None):
if config is None:
config = tf.compat.v1.ConfigProto()
openvino_tf_disable_deassign_clusters = os.environ.pop(
'OPENVINO_TF_DISABLE_DEASSIGN_CLUSTERS', None)
openvino_tensorflow.disable()
with tf.compat.v1.Session(config=config) as sess:
retval = l(sess)
if openvino_tf_disable_deassign_clusters is not None:
os.environ['OPENVINO_TF_DISABLE_DEASSIGN_CLUSTERS'] = \
openvino_tf_disable_deassign_clusters
return retval
if model_file == "":
model = hub.load(
"https://tfhub.dev/google/imagenet/inception_v3/classification/4")
else:
model = tf.saved_model.load(model_file)
if not args.disable_ovtf:
#Print list of available backends
print('Available Backends:')
backends_list = ovtf.list_backends()
for backend in backends_list:
print(backend)
ovtf.set_backend(backend_name)
else:
ovtf.disable()
#Load the labels
cap = None
images = []
if label_file:
labels = load_labels(label_file)
input_mode = get_input_mode(input_file)
if input_mode == "video":
cap = cv2.VideoCapture(input_file)
elif input_mode == "camera":
cap = cv2.VideoCapture(0)
elif input_mode == 'image':
images = [input_file]
elif input_mode == 'directory':
if not os.path.isdir(input_file):
def test_disable(self):
openvino_tensorflow.disable()
if not openvino_tensorflow.is_enabled() == 0:
raise AssertionError