Caffe-使用多个输入Blob进行前向传递 [英] Caffe - Doing forward pass with multiple input blobs
问题描述
以下是我的微调模型的输入层:
Following are the input layers of my fine-tuned model:
layer {
type: "HDF5Data"
name: "data"
top: "Meta"
hdf5_data_param {
source: "/path/to/train.txt"
batch_size: 50
}
include { phase: TRAIN }
}
layer {
name: "data"
type: "ImageData"
top: "X"
top: "Labels"
include {
phase: TRAIN
}
transform_param {
mirror: true
crop_size: 227
mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
}
image_data_param {
source: "/path/to/train.txt"
batch_size: 50
new_height: 256
new_width: 256
}
}
layer {
type: "HDF5Data"
name: "data"
top: "Meta"
hdf5_data_param {
source: "/path/to/val.txt"
batch_size: 50
}
include { phase: TEST }
}
layer {
name: "data"
type: "ImageData"
top: "X"
top: "Labels"
include {
phase: TEST
}
transform_param {
mirror: false
crop_size: 227
mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
}
image_data_param {
source: "/path/to/val.txt"
batch_size: 50
new_height: 256
new_width: 256
}
}
如您所见,它具有一个imagedata输入层和1个hdf5输入层,如果只有1种类型的层,例如imagedata,我可以做到:
As you can see it has one imagedata input layer and 1 hdf5 input layer, if there was only 1 type of layer say imagedata, I could have done:
input_data = {prepare_images(im)}; # dimension 227*227*3*10
,然后
scores = caffe('forward',input_data);
但是在这里我必须给出两种类型的输入数据,我该怎么做?
and then
scores = caffe('forward',input_data);
But here I have to give two types of input data, how can I do this? Please help!
推荐答案
我必须检查matcaffe.cpp(并使用make matcaffe进行重新编译),并打印' 输入大小无效的条件使我无法通过有效的方式来调换input_data。
I had to check matcaffe.cpp (and recompile with make matcaffe) and print the check variables for the 'Invalid Input Size' condition I was failing, to get the idea of transposing input_data which works.
input_data = {prepare_images(im),prepare_other_data()};
scores = caffe('forward', input_data');
因此进行移调对我有用。
Thus taking the transpose worked for me.
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