'layer type' data not supported

[emmapead]

I am trying to use your code to convert DeepYeast from the caffe model zoo to keras. I followed instructions for conversion running this command

python -m caffe2keras M:\Caffe_CPU\DeepYeast\HOwt_png_vgg_A_bn_deploy.prototxt M:\Caffe_CPU\DeepYeast\HOwt_png_vgg_A_bn_iter_130000.caffemodel deepyeastKeras.h5

and changing the deploy file from:

name: "HOwt_png_quick"
input: "data"
input_shape {
dim: 100
dim: 3
dim: 64
dim: 64
}
layer {
name: "conv1_1"
type: "Convolution"
bottom: "data"
top: "conv1_1"
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
........

to this:

name: "HOwt_png_quick"
input: "data"
input_dim: 100
input_dim:3
input_dim:64
input_dim:64
layer{
name:"data"
type: "data"
top: "data"
top:"label"
}
layer {
name: "conv1_1"
type: "Convolution"
bottom: "data"
top: "conv1_1"
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}

and get this error:

Using Theano backend.
Converting model...
CREATING MODEL
Traceback (most recent call last):
File "C:\Users\xx\AppData\Local\Continuum\anaconda3\envs\dlen35\lib\runpy.py", "main", mod_spec) File "C:\Users\xx\AppData\Local\Continuum\anaconda3\envs\dlen35\lib\runpy.py",
exec(code, run_globals)
File "M:\Caffe_CPU\caffe2keras\caffe2keras_main_.py", line 32, in
main() File "M:\Caffe_CPU\caffe2keras\caffe2keras_main_.py", line 22, in main
model = convert.caffe_to_keras(args.prototxt, args.caffemodel, args.debug)
File "M:\Caffe_CPU\caffe2keras\caffe2keras\convert.py", line 358, in caffe_to_keras tuple(config.input_dim[1:]))
File "M:\Caffe_CPU\caffe2keras\caffe2keras\convert.py", line 483, in create_model
'used in this model is not currently supported')
RuntimeError: ('layer type', 'data', 'used in this model is not currently supported')

I just don't understand what it is I am doing wrong. Any ideas?

Original deploy file can be found here http://kodu.ut.ee/~leopoldp/2016_DeepYeast/code/caffe_model/

[qxcv]

The converter only supports type: "input" layers at the moment (in handle_input). Rearranging the input layers to look like this (modulo names & sizes) should make the model work:

layer {
  name: "image"
  type: "Input"
  top: "image"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 368
      dim: 368
    }
  }
}

I've attached a working .prototxt which I've previously converted (adapted from Convolutional Pose Machines release):

pose_deploy_resize.txt

[emmapead]

okay, so I changed the input layer and now I am getting this error:

CREATING MODEL
Traceback (most recent call last):
File "/home/emma/anaconda3/envs/dlenv/lib/python3.5/runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "/home/emma/anaconda3/envs/dlenv/lib/python3.5/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/emma/Documents/caffe2keras-master/caffe2keras/main.py", line 32, in
main()
File "/home/emma/Documents/caffe2keras-master/caffe2keras/main.py", line 22, in main
model = convert.caffe_to_keras(args.prototxt, args.caffemodel, args.debug)
File "/home/emma/Documents/caffe2keras-master/caffe2keras/convert.py", line 358, in caffe_to_keras
tuple(config.input_dim[1:]))
File "/home/emma/Documents/caffe2keras-master/caffe2keras/convert.py", line 463, in create_model
% (bottom, name)
AssertionError: Must have computed bottom data before reaching layer conv1_1

any ideas?