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How to run TensorFlow Object Detection model on Jetson Nano | DLology
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import tensorflow as tf | |
def get_frozen_graph(graph_file): | |
"""Read Frozen Graph file from disk.""" | |
with tf.gfile.FastGFile(graph_file, "rb") as f: | |
graph_def = tf.GraphDef() | |
graph_def.ParseFromString(f.read()) | |
return graph_def | |
# The TensorRT inference graph file downloaded from Colab or your local machine. | |
pb_fname = "./model/trt_graph.pb" | |
trt_graph = get_frozen_graph(pb_fname) | |
input_names = ['image_tensor'] | |
# Create session and load graph | |
tf_config = tf.ConfigProto() | |
tf_config.gpu_options.allow_growth = True | |
tf_sess = tf.Session(config=tf_config) | |
tf.import_graph_def(trt_graph, name='') | |
tf_input = tf_sess.graph.get_tensor_by_name(input_names[0] + ':0') | |
tf_scores = tf_sess.graph.get_tensor_by_name('detection_scores:0') | |
tf_boxes = tf_sess.graph.get_tensor_by_name('detection_boxes:0') | |
tf_classes = tf_sess.graph.get_tensor_by_name('detection_classes:0') | |
tf_num_detections = tf_sess.graph.get_tensor_by_name('num_detections:0') |
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