1

At the beginning of the year I started to look into Tensorflow and ML. A friend of mine with some code sample to train some classes for custom objects using FASTER_RCNN_RESNET_101. Because I had no GPU and the training was taking quite some time on my machine he was running the training on his machine and he was providing me the files needed for me in the image detection code.
Meanwhile I have bought a GPU and I tried to do all the steps on my machine. I am doing all the steps I was doing with him but now when I run the detection no objects are detected after the training.
The step that I have no documentation is the one that generates the .pb file. I tried to use models\research\object_detection\export_inference_graph.py to generate the file like:
python models\research\object_detection\export_inference_graph.py --input_type image_tensor --pipeline_config_path data\pipeline_vio.config --trained_checkpoint_prefix data\train_folder\model.ckpt-497416 --output_directory train_folder\exported_graphs
I encounter a problem:
Using the .pb file generated no object is recognized but if I use the file he provided the objects are recognized.
Last time I did the training using
python train.py --logtostderr --train_dir=data\train_folder --pipeline_config_path=data\pipeline_vio.config
Is there a method to see the difference between the 2 graphs or something to understand why one of the graphs works but not the other

Viorel Mirea
  • 371
  • 3
  • 6
  • Maybe look at [this SO answer](https://stackoverflow.com/a/50652415/2202359) as a starting point. – j2abro Jan 17 '21 at 02:35
  • You can use [Tensorboard](https://www.tensorflow.org/tensorboard/graphs) to visualize two models(.pb) separately and compare them. Similar issue https://stackoverflow.com/a/50722185/14290244 solution might help you. Thanks! –  Jan 19 '21 at 09:53

0 Answers0