Convert DarkNet weights to .pb file

Create frozen graph from DarkNet weights

DarkFlow is a very useful and handy tool to train YOLO implemented with TensorFlow. By finishing the training it is possible to write out the graph and its weights into a protobuff file, called frozen graph. Later this frozen graph can be read and executed by the TensorFlow framework. Unfortunately, beside the advantages the DarkFlow has many disatvantages too, for example sometimes it is lately adapted for the YOLO architecture changes and for this reason different incompatibility issues can appear. Probably, you are already familiar with the assertion error message, when you try to retrain your model: "AssertionError: expect 64701556 bytes, found 180357512". A possible solution is to train your model with the DarkNet which is the reference implementation of this neural network framework, then convert the weights by using DarkFlow. The Google Colaboratory tutorial is available here.

In this article we present you a possible solution to convert the DarkNet weights to .pb file. At this point we suppose that you are already familiar with these two frameworks. If you aren't please read the following two articles:

• Train YOLO with DarkNet;
• Train YOLO with DarkFlow;

At the end of the "Train YOLO with DarkNet" tutorial we obtained the trained weights (it is accessible here). We will use this file to convert it to .pb format.

Download this file or use your own and place it into a sub-directory like ./weights, in the DarkFlow root directory.

Here we will use the same configuration file what we used in the previous tutorial. You can get it by using the wget application:

• $ wget https://oc.codespring.ro/s/KcMNWpdnsEzkrtL/download - rename it properly, and place it into the ./cfg directory.

The command to convert it to .pb format is:

• $ ./flow --model cfg/yolov2-tiny-voc.cfg --load weights/yolov2-tiny-voc_10000.weights --savepb

When you execute this command the following outputs appear:

Parsing cfg/yolov2-tiny-voc.cfg

Loading weights/yolov2-tiny-voc_10000.weights ...

Traceback (most recent call last):

  File "./flow", line 6, in <module>

    cliHandler(sys.argv)

  File "/home/ubbcluj/Documents/Egyetem/FinalExam/Darknet/Darknet/darkflow/darkflow/cli.py", line 26, in cliHandler

    tfnet = TFNet(FLAGS)

  File "/home/ubbcluj/Documents/Egyetem/FinalExam/Darknet/Darknet/darkflow/darkflow/net/build.py", line 58, in __init__

    darknet = Darknet(FLAGS)

  File "/home/ubbcluj/Documents/Egyetem/FinalExam/Darknet/Darknet/darkflow/darkflow/dark/darknet.py", line 27, in __init__

    self.load_weights()

  File "/home/ubbcluj/Documents/Egyetem/FinalExam/Darknet/Darknet/darkflow/darkflow/dark/darknet.py", line 82, in load_weights

    wgts_loader = loader.create_loader(*args)

  File "/home/ubbcluj/Documents/Egyetem/FinalExam/Darknet/Darknet/darkflow/darkflow/utils/loader.py", line 105, in create_loader

    return load_type(path, cfg)

  File "/home/ubbcluj/Documents/Egyetem/FinalExam/Darknet/Darknet/darkflow/darkflow/utils/loader.py", line 19, in __init__

    self.load(*args)

  File "/home/ubbcluj/Documents/Egyetem/FinalExam/Darknet/Darknet/darkflow/darkflow/utils/loader.py", line 77, in load

    walker.offset, walker.size)

AssertionError: expect 63102554 bytes, found 63102560

It is already familiar to us. Isn't it?

The solution is very simple, let's modify the line self.offset = 16 in the ./darkflow/utils/loader.py file and replace with self.offset = 20. Execute again the previous command. After running the command two files will appear in the ./built_graph directory:

• yolov2-tiny-voc.meta;
• yolov2-tiny-voc.pb;