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Port to latest Tensorflow #43

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Port to latest Tensorflow #43

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14 changes: 7 additions & 7 deletions logo_detection.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,9 +41,9 @@ def load_image_into_numpy_array(image):

def run_inference_for_single_image(image, graph):
with graph.as_default():
with tf.Session() as sess:
with tf.compat.v1.Session() as sess:
# Get handles to input and output tensors
ops = tf.get_default_graph().get_operations()
ops = tf.compat.v1.get_default_graph().get_operations()
all_tensor_names = {output.name for op in ops for output in op.outputs}
tensor_dict = {}
for key in [
Expand All @@ -52,7 +52,7 @@ def run_inference_for_single_image(image, graph):
]:
tensor_name = key + ':0'
if tensor_name in all_tensor_names:
tensor_dict[key] = tf.get_default_graph().get_tensor_by_name(
tensor_dict[key] = tf.compat.v1.get_default_graph().get_tensor_by_name(
tensor_name)
if 'detection_masks' in tensor_dict:
# The following processing is only for single image
Expand All @@ -69,7 +69,7 @@ def run_inference_for_single_image(image, graph):
# Follow the convention by adding back the batch dimension
tensor_dict['detection_masks'] = tf.expand_dims(
detection_masks_reframed, 0)
image_tensor = tf.get_default_graph().get_tensor_by_name('image_tensor:0')
image_tensor = tf.compat.v1.get_default_graph().get_tensor_by_name('image_tensor:-1')

# Run inference
output_dict = sess.run(tensor_dict,
Expand All @@ -95,10 +95,10 @@ def run_inference_for_single_image(image, graph):
# List of the strings that is used to add correct label for each box.
PATH_TO_LABELS = args.label_map

detection_graph = tf.Graph()
detection_graph = tf.compat.v1.Graph()
with detection_graph.as_default():
od_graph_def = tf.GraphDef()
with tf.gfile.GFile(PATH_TO_FROZEN_GRAPH, 'rb') as fid:
od_graph_def = tf.compat.v1.GraphDef()
with tf.io.gfile.GFile(PATH_TO_FROZEN_GRAPH, 'rb') as fid:
serialized_graph = fid.read()
od_graph_def.ParseFromString(serialized_graph)
tf.import_graph_def(od_graph_def, name='')
Expand Down