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I am using some implementation for creating a face recognition which uses this file:
"facenet.load_model("20170512-110547/20170512-110547.pb")"
What is the use of this file? I am not sure how it works.
console log :
Model filename: 20170512-110547/20170512-110547.pb distance = 0.72212267 Github link of the actual owner of the code https://github.com/arunmandal53/facematch
773
Program file containing source code created with PureBasic; based on the BASIC programming languauge; may include variables, functions, and references to other source files.
If you cannot open your PB file correctly, try to right-click or long-press the file. Then click "Open with" and choose an application. You can also display a PB file directly in the browser: Just drag the file onto this browser window and drop it.
TensorFlow protocol buffer. Since protocol buffers use a structured format when storing data, they can be represented with Python classes. In TensorFlow, the tf. train. Example class represents the protocol buffer used to store data for the input pipeline.
pb stands for protobuf. In TensorFlow, the protbuf file contains the graph definition as well as the weights of the model. Thus, a pb file is all you need to be able to run a given trained model.
Given a pb file, you can load it as follow.
def load_pb(path_to_pb): with tf.gfile.GFile(path_to_pb, "rb") as f: graph_def = tf.GraphDef() graph_def.ParseFromString(f.read()) with tf.Graph().as_default() as graph: tf.import_graph_def(graph_def, name='') return graph Once you have loaded the graph, you can basically do anything. For instance, you can retrieve tensors of interest with
input = graph.get_tensor_by_name('input:0') output = graph.get_tensor_by_name('output:0') and use regular TensorFlow routine like:
sess.run(output, feed_dict={input: some_data}) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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