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I am trying to convert squeezedet caffemodel to run on movidius stick using the following command
mvNCCompile squeezedet.prototxt -w squeezeDet.caffemodel -s 12 -o graph
I am getting the following error
[Warning: 37] Output layer's name (Slice) must match its top (pred_class_probs)
[Error 17] Toolkit Error: Internal Error: Could not build graph. Missing link: conv1_shadow
Contents of squeezedet.prototxt is as follows (Only first have as the file is too long)
name: "SqueezeDet"
input: "data"
input_shape {
dim: 1
dim: 3
dim: 384
dim: 1248
}
input: "conv1_shadow"
input_shape {
dim: 1
dim: 64
dim: 192
dim: 624
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 64
weight_filler {
type: "xavier"
}
pad: 2
kernel_size: 3
stride: 2
}
}
layer {
name: "conv1_crop"
type: "Crop"
bottom: "conv1"
bottom: "conv1_shadow"
top: "conv1_crop"
crop_param {
axis: 1
offset: 0
offset: 1
offset: 1
}
}
layer {
name: "con1_relu"
type: "ReLU"
bottom: "conv1_crop"
top: "conv1_relu"
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1_relu"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
# ------- Fire2 Block ------- #
# (B x C x 96 x 312)
layer {
name: "fire2/squeeze1x1"
type: "Convolution"
bottom: "pool1"
top: "fire2/squeeze1x1"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 16
weight_filler {
type: "xavier"
}
kernel_size: 1
stride: 1
}
}
layer {
name: "fire2/squeeze1x1_relu"
type: "ReLU"
bottom: "fire2/squeeze1x1"
top: "fire2/squeeze1x1"
}
layer {
name: "fire2/expand1x1"
type: "Convolution"
bottom: "fire2/squeeze1x1"
top: "fire2/expand1x1"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 64
weight_filler {
type: "xavier"
}
kernel_size: 1
stride: 1
}
}
layer {
name: "fire2/expand1x1_relu"
type: "ReLU"
bottom: "fire2/expand1x1"
top: "fire2/expand1x1"
}
layer {
name: "fire2/expand3x3"
type: "Convolution"
bottom: "fire2/squeeze1x1"
top: "fire2/expand3x3"
convolution_param {
num_output: 64
weight_filler {
type: "xavier"
}
pad: 1
kernel_size: 3
stride: 1
}
}
layer {
name: "fire2/expand3x3_relu"
type: "ReLU"
bottom: "fire2/expand3x3"
top: "fire2/expand3x3"
}
layer {
name: "fire2/concat"
type: "Concat"
bottom: "fire2/expand1x1"
bottom: "fire2/expand3x3"
top: "fire2/concat"
}
# ------- Fire3 Block ------- #
layer {
name: "fire3/squeeze1x1"
type: "Convolution"
bottom: "fire2/concat"
top: "fire3/squeeze1x1"
convolution_param {
num_output: 16
weight_filler {
type: "xavier"
}
kernel_size: 1
stride: 1
}
}
layer {
name: "fire3/squeeze1x1_relu"
type: "ReLU"
bottom: "fire3/squeeze1x1"
top: "fire3/squeeze1x1"
}
layer {
name: "fire3/expand1x1"
type: "Convolution"
bottom: "fire3/squeeze1x1"
top: "fire3/expand1x1"
convolution_param {
num_output: 64
weight_filler {
type: "xavier"
}
kernel_size: 1
stride: 1
}
}
layer {
name: "fire3/expand1x1_relu"
type: "ReLU"
bottom: "fire3/expand1x1"
top: "fire3/expand1x1"
}
layer {
name: "fire3/expand3x3"
type: "Convolution"
bottom: "fire3/squeeze1x1"
top: "fire3/expand3x3"
convolution_param {
num_output: 64
weight_filler {
type: "xavier"
}
pad: 1
kernel_size: 3
stride: 1
}
}
layer {
name: "fire3/expand3x3_relu"
type: "ReLU"
bottom: "fire3/expand3x3"
top: "fire3/expand3x3"
}
layer {
name: "fire3/concat"
type: "Concat"
bottom: "fire3/expand1x1"
bottom: "fire3/expand3x3"
top: "fire3/concat"
}
layer {
name: "pool3"
type: "Pooling"
bottom: "fire3/concat"
top: "pool3"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
Does anybody know what is wrong? Anyhelp would be appreciated.
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@gopinath Looks like this model uses multiple inputs. At the moment, the current NCSDK version (2.05) doesn't have support for multiple inputs. There isn't a roadmap that I can provide for this feature at the moment.
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