Image Channel Mismatch in Caffe - caffe

Question

I know this may be better asked in caffe user group but I cannot access the user group and don't know where to pose the question as I'm not sure whether this needs to be raised as an issue in git. In any case, what I'm doing is this:
I have a set of grayscale images that I want to use to train a CNN using caffe. I'm using a modified version of the provided caffenet model definitions with minor modifications (ie: channel = 1 instead of 3 as I have grayscale images). So far, I used the imagenet provided mean image to train the CNN and it trained and generated results. Now I wanted to compute the image mean of my own train/test dataset and use that as the mean image so I used the file in build/tools/ to do this. It needed the images to be in lmdb so I first converted images to lmdb using convert_imageset and then used compute_mean to compute the mean. I ensured that I use --gray flag when using convert_imageset as my images are grayscale. When I rerun caffe, I get the following error. From what I can understand, it's a channel mismatch but I have no idea how to fix this. Any help on this is very much appreciated.
I0829 20:41:50.429733 17065 layer_factory.hpp:77] Creating layer data
I0829 20:41:50.429764 17065 net.cpp:100] Creating Layer data
I0829 20:41:50.429769 17065 net.cpp:408] data -> data
I0829 20:41:50.429790 17065 net.cpp:408] data -> label
I0829 20:41:50.429805 17065 data_transformer.cpp:25] Loading mean file from: data/flickr_style/train_mean.binaryproto
I0829 20:41:50.438251 17065 image_data_layer.cpp:38] Opening file data/flickr_style/train.txt
I0829 20:41:50.446666 17065 image_data_layer.cpp:58] A total of 31740 images.
I0829 20:41:50.451941 17065 image_data_layer.cpp:85] output data size: 10,3,227,227
I0829 20:41:50.459661 17065 net.cpp:150] Setting up data
I0829 20:41:50.459692 17065 net.cpp:157] Top shape: 10 3 227 227 (1545870)
I0829 20:41:50.459697 17065 net.cpp:157] Top shape: 10 (10)
I0829 20:41:50.459699 17065 net.cpp:165] Memory required for data: 6183520
I0829 20:41:50.459707 17065 layer_factory.hpp:77] Creating layer conv1
I0829 20:41:50.459728 17065 net.cpp:100] Creating Layer conv1
I0829 20:41:50.459733 17065 net.cpp:434] conv1 <- data
I0829 20:41:50.459744 17065 net.cpp:408] conv1 -> conv1
F0829 20:41:50.463794 17106 data_transformer.cpp:257] Check failed: img_channels == data_mean_.channels() (3 vs. 1)
*** Check failure stack trace: ***
# 0x7f0712106daa (unknown)
# 0x7f0712106ce4 (unknown)
# 0x7f07121066e6 (unknown)
# 0x7f0712109687 (unknown)
# 0x7f071287d6cd caffe::DataTransformer<>::Transform()
# 0x7f07127fde60 caffe::ImageDataLayer<>::load_batch()
# 0x7f0712839539 caffe::BasePrefetchingDataLayer<>::InternalThreadEntry()
# 0x7f0712886020 caffe::InternalThread::entry()
# 0x7f070a762a4a (unknown)
# 0x7f070603e184 start_thread
# 0x7f07111eb37d (unknown)
# (nil) (unknown)
I have the following in train_val.prototxt
name: "FlickrStyleCaffeNet"
layer {
name: "data"
type: "ImageData"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
mirror: true
crop_size: 227
mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
}
image_data_param {
source: "data/flickr_style/mri_train.txt"
batch_size: 10
new_height: 256
new_width: 256
}
}
and this in deploy.prototxt
name: "FlickrStyleCaffeNet"
layer {
name: "data"
type: "Input"
top: "data"
input_param { shape: { dim: 10 dim: 3 dim: 227 dim: 227 } }
}

Answer 1

You (or the interface) have failed to adjust the input for gray scale. Gray has only 1 input channel (value); the model expects 3 channels (RGB). That 3 in the layer's top shape should be 1.
Look in your *.prototxt files for something like this near the top (input layer):
shape {
dim: 10
dim: 3
dim: 227
dim: 227
}
These dimensions are batch_size, channels, rows, and columns. Wherever you have something on this order (there should be only one, and only in input files), change the 3 to 1.

Answer 2

I figured out how to do this. In the train_val.prototxt, there's an image_data_param section under data layer. I had to add is_color: false in it and that fixed the issue.
Thanks everyone for comments and replies, appreciate it.