How to modify faster rcnn with multi data layer input?

[myungki park]

Hi! i'm using  Faster r-cnn code for my own task.

i trained faster rcnn sucessfully with my own datasets ( 3-channel RGB).

But i want to modify original network to has 2 input data layer (3-channel RGB + 3-channel IR) or 6-channel data.

Since in faster rcnn code, the 'Python type' input data layer has 3-channels imdb data foramt like below.

name: "VGG_CNN_M_1024"

layer {

  name: 'data'

  type: 'Python'

  top: 'data'

  top: 'rois'

  top: 'labels'

  top: 'bbox_targets'

  top: 'bbox_inside_weights'

  top: 'bbox_outside_weights'

  python_param {

    module: 'roi_data_layer.layer'

    layer: 'RoIDataLayer'

    param_str: "'num_classes': 2"

  }

My questions are

1) is there any method  imdb data has 6-channel inputs?

2) How to modify faster rcnn code to has two different imdb data as inputs ?

Any clue or advise will be greatly helpful for me....

thanks..