Clone [torch](http://torch.ch/) distribution:
git clone https://github.com/torch/distro.git ~/torch --recursive
cd ~/torch
./install.sh
After ./install.sh is finished - it will ask if you want to update .bashrc to include call to initialize torch environment every time you login. If you don't want it, you will have to execute command . ~/torch/install/bin/torch-activate before you will be able to lauch th.
You can install various torch example from https://github.com/torch/demos, here is an output from MNIST digit classieifer training session:
bash-3.2:~/src/demos/train-a-digit-classifier $ th train-on-mnist.lua
<torch> set nb of threads to 4
<mnist> using model:
nn.Sequential {
[input -> (1) -> (2) -> (3) -> (4) -> (5) -> (6) -> (7) -> (8) -> (9) -> (10) -> output]
(1): nn.SpatialConvolutionMM(1 -> 32, 5x5)
(2): nn.Tanh
(3): nn.SpatialMaxPooling(3x3, 3,3, 1,1)
(4): nn.SpatialConvolutionMM(32 -> 64, 5x5)
(5): nn.Tanh
(6): nn.SpatialMaxPooling(2x2, 2,2)
(7): nn.Reshape(576)
(8): nn.Linear(576 -> 200)
(9): nn.Tanh
(10): nn.Linear(200 -> 10)
}
<warning> only using 2000 samples to train quickly (use flag -full to use 60000 samples)
<mnist> loading only 2000 examples
<mnist> done
<mnist> loading only 1000 examples
<mnist> done
<trainer> on training set:
<trainer> online epoch # 1 [batchSize = 10]
[===================>.................... 471/2000 ....................................] ETA: 2m20s | Step: 92ms
git clone https://github.com/jdonald/deep-macos
After that you can launch download_net.sh script to download the pretrained NIN network ( based on https://gist.github.com/szagoruyko/0f5b4c5e2d2b18472854 ) to your $HOME path. WARNING pretrained network is 33Mb file!
You must install a camera luarocks package tweaked to work on macOS.
luarocks install https://raw.githubusercontent.com/jdonald/lua---camera/master/camera-1.1-0.rockspec
To run on a single image: th test_single.lua <path to your image>
To run continious classification using frames from camera ( I recommend using external USB camera) :
nohup th -ldisplay.start 8000 0.0.0.0 &
th camera_interface.lua
Then open web browser and point to to location http://localhost:8000
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