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# 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](https://devblogs.nvidia.com/parallelforall/image-segmentation-using-digits-5) 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: ``` bash $ 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. ##

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