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Semantic Segmentation

Generating Pretrained FCN-Alexnet

Fully Convolutional Network (FCN) Alexnet is the network topology that we'll use for segmentation models with DIGITS and TensorRT. See this Parallel ForAll article about the convolutionalizing process. A new feature to DIGITS5 was supporting segmentation datasets and training models.

A script is included with the DIGITS semantic segmentation example which converts the Alexnet model into FCN-Alexnet. This base model is then used as a pre-trained starting point for training future FCN-Alexnet segmentation models on custom datasets.

To generate the pre-trained FCN-Alexnet model, open a terminal, navigate to the DIGITS semantic-segmantation example, and run the net_surgery script:

$ cd DIGITS/examples/semantic-segmentation
$ ./net_surgery.py
Downloading files (this might take a few minutes)...
Downloading https://raw.githubusercontent.com/BVLC/caffe/rc3/models/bvlc_alexnet/deploy.prototxt...
Downloading http://dl.caffe.berkeleyvision.org/bvlc_alexnet.caffemodel...
Loading Alexnet model...
...
Saving FCN-Alexnet model to fcn_alexnet.caffemodel

Next, we'll train our FCN-Alexnet model on the drone dataset in DIGITS.

Next | Training FCN-Alexnet with DIGITS
Back | Semantic Segmentation with SegNet

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