- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
luoy@TTlyN:~/ncsdk/bin$ make example0Face
example0Face - FaceNet generation
python3 ./mvNCCompile.pyc data/LightenedCNN_B_deploy.prototxt -s 12
mvNCCompile v02.00, Copyright @ Movidius Ltd 2016
Traceback (most recent call last):
File "../../src/./mvNCCompile.py", line 99, in
File "../../src/./mvNCCompile.py", line 81, in create_graph
File "../../src/./Controllers/CaffeParser.py", line 523, in parse_caffe
IndexError: list index (0) out of range
Makefile:39: recipe for target 'example0Face' failed
make: *** [example0Face] Error 1
here is my prototxt file
Link Copied
2 Replies
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
name: "DeepFace_set003_net"
input: "data"
input_shape {
dim: 1
dim: 1
dim: 128
dim: 128
}
layers{
name: "conv1"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 96
kernel_size: 5
stride: 1
pad: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.1
}
}
bottom: "data"
top: "conv1"
}
layers{
name: "slice1"
type:SLICE
slice_param {
slice_dim: 1
}
bottom: "conv1"
top: "slice1_1"
top: "slice1_2"
}
layers{
name: "etlwise1"
type: ELTWISE
bottom: "slice1_1"
bottom: "slice1_2"
top: "eltwise1"
eltwise_param {
operation: MAX
}
}
layers{
name: "pool1"
type: POOLING
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
bottom: "eltwise1"
top: "pool1"
}
layers{
name: "conv2a"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 96
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.1
}
}
bottom: "pool1"
top: "conv2a"
}
layers{
name: "slice2a"
type:SLICE
slice_param {
slice_dim: 1
}
bottom: "conv2a"
top: "slice2a_1"
top: "slice2a_2"
}
layers{
name: "etlwise2a"
type: ELTWISE
bottom: "slice2a_1"
bottom: "slice2a_2"
top: "eltwise2a"
eltwise_param {
operation: MAX
}
}
layers{
name: "conv2"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 192
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.1
}
}
bottom: "eltwise2a"
top: "conv2"
}
layers{
name: "slice2"
type:SLICE
slice_param {
slice_dim: 1
}
bottom: "conv2"
top: "slice2_1"
top: "slice2_2"
}
layers{
name: "etlwise2"
type: ELTWISE
bottom: "slice2_1"
bottom: "slice2_2"
top: "eltwise2"
eltwise_param {
operation: MAX
}
}
layers{
name: "pool2"
type: POOLING
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
bottom: "eltwise2"
top: "pool2"
}
layers{
name: "conv3a"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 192
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.1
}
}
bottom: "pool2"
top: "conv3a"
}
layers{
name: "slice3a"
type:SLICE
slice_param {
slice_dim: 1
}
bottom: "conv3a"
top: "slice3a_1"
top: "slice3a_2"
}
layers{
name: "etlwise3a"
type: ELTWISE
bottom: "slice3a_1"
bottom: "slice3a_2"
top: "eltwise3a"
eltwise_param {
operation: MAX
}
}
layers{
name: "conv3"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 384
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.1
}
}
bottom: "eltwise3a"
top: "conv3"
}
layers{
name: "slice3"
type:SLICE
slice_param {
slice_dim: 1
}
bottom: "conv3"
top: "slice3_1"
top: "slice3_2"
}
layers{
name: "etlwise3"
type: ELTWISE
bottom: "slice3_1"
bottom: "slice3_2"
top: "eltwise3"
eltwise_param {
operation: MAX
}
}
layers{
name: "pool3"
type: POOLING
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
bottom: "eltwise3"
top: "pool3"
}
layers{
name: "conv4a"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param{
num_output: 384
kernel_size: 1
stride: 1
weight_filler{
type:"xavier"
}
bias_filler{
type: "constant"
value: 0.1
}
}
bottom: "pool3"
top: "conv4a"
}
layers{
name: "slice4a"
type:SLICE
slice_param {
slice_dim: 1
}
bottom: "conv4a"
top: "slice4a_1"
top: "slice4a_2"
}
layers{
name: "etlwise4a"
type: ELTWISE
bottom: "slice4a_1"
bottom: "slice4a_2"
top: "eltwise4a"
eltwise_param {
operation: MAX
}
}
layers{
name: "conv4"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param{
num_output: 256
kernel_size: 3
stride: 1
pad: 1
weight_filler{
type:"xavier"
}
bias_filler{
type: "constant"
value: 0.1
}
}
bottom: "eltwise4a"
top: "conv4"
}
layers{
name: "slice4"
type:SLICE
slice_param {
slice_dim: 1
}
bottom: "conv4"
top: "slice4_1"
top: "slice4_2"
}
layers{
name: "etlwise4"
type: ELTWISE
bottom: "slice4_1"
bottom: "slice4_2"
top: "eltwise4"
eltwise_param {
operation: MAX
}
}
layers{
name: "conv5a"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param{
num_output: 256
kernel_size: 1
stride: 1
weight_filler{
type:"xavier"
}
bias_filler{
type: "constant"
value: 0.1
}
}
bottom: "eltwise4"
top: "conv5a"
}
layers{
name: "slice5a"
type:SLICE
slice_param {
slice_dim: 1
}
bottom: "conv5a"
top: "slice5a_1"
top: "slice5a_2"
}
layers{
name: "etlwise5a"
type: ELTWISE
bottom: "slice5a_1"
bottom: "slice5a_2"
top: "eltwise5a"
eltwise_param {
operation: MAX
}
}
layers{
name: "conv5"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param{
num_output: 256
kernel_size: 3
stride: 1
pad: 1
weight_filler{
type:"xavier"
}
bias_filler{
type: "constant"
value: 0.1
}
}
bottom: "eltwise5a"
top: "conv5"
}
layers{
name: "slice5"
type:SLICE
slice_param {
slice_dim: 1
}
bottom: "conv5"
top: "slice5_1"
top: "slice5_2"
}
layers{
name: "etlwise5"
type: ELTWISE
bottom: "slice5_1"
bottom: "slice5_2"
top: "eltwise5"
eltwise_param {
operation: MAX
}
}
layers{
name: "pool4"
type: POOLING
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
bottom: "eltwise5"
top: "pool4"
}
layers{
name: "fc1"
type: INNER_PRODUCT
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
inner_product_param {
num_output: 512
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.1
}
}
bottom: "pool4"
top: "fc1"
}
layers{
name: "slice_fc1"
type:SLICE
slice_param {
slice_dim: 1
}
bottom: "fc1"
top: "slice_fc1_1"
top: "slice_fc1_2"
}
layers{
name: "etlwise_fc1"
type: ELTWISE
bottom: "slice_fc1_1"
bottom: "slice_fc1_2"
top: "eltwise_fc1"
eltwise_param {
operation: MAX
}
}
layers{
name: "drop1"
type: DROPOUT
dropout_param{
dropout_ratio: 0.75
}
bottom: "eltwise_fc1"
top: "eltwise_fc1"
}
layers{
name: "fc2"
type: INNER_PRODUCT
inner_product_param{
num_output: 10575
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.1
}
}
bottom: "eltwise_fc1"
top: "fc2"
}
layers {
name: "softmax"
type: SOFTMAX
bottom: "fc2"
top: "prob"
}
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
@youngluoyang A possible cause could be the missing slice point parameters from your Slice layers. Slice layers should have at least one slice_point per Slice layer. Referring to (http://caffe.berkeleyvision.org/tutorial/layers/slice.html), it seems the slice_points aren't optional. Let us know if this fixes your problem.
Reply
Topic Options
- Subscribe to RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page