I'm using this code to load my net:

```
net = caffe.Classifier(MODEL_FILE, PRETRAINED,
                   mean=np.load(caffe_root + 'python/caffe/imagenet/ilsvrc_2012_mean.npy').mean(1).mean(1),
                   channel_swap=(2,1,0),
                   raw_scale=255,
                   image_dims=(256, 256))

```

I have doubts on three lines.

1- `mean=np.load(caffe_root + 'python/caffe/imagenet/ilsvrc_2012_mean.npy').mean(1).mean(1)`

What is mean? Should I use this mean value or another? And if yes, where can I get custom mean value? I'm using a custom dataset.

2- `channel_swap=(2,1,0)`

What channel\_swap means? And again, should I use this value or an custom value?

And the last

3- `raw_scale=255` 

What is raw\_scale? And what value should I use?

I'm using [Cohn Kanade](http://www.pitt.edu/~emotion/ck-spread.htm) dataset. All images are 64x64 and in grayscale.