I want to know how to use typical models such as GoogleNet

[YOKO HAMA]

Hello.

I started studying deep learning.

I want to identify (classify) my own images.

I learned that there are AlexNet and GoogLeNet as representative models of deep learning.

I'm thinking about using that model to determine my image data.

When using your own image data, what part of the file called prototxt should be changed?

Is it possible to change this part of the data?

What I want to use is a general(?) color image of 128px * 128px. When using the CIFAR-10 prototxt file, it was set to (dim: 1 dim: 3 dim: 255 dim: 255).

Also, is it possible to use a file called mean image (mean.binaryproto) in the transform_param part?

This might be basic, but could you tell me how to set.

deploy

layer { name: "data" type: "Input" top: "data" input_param { shape: { dim: 10 dim: 3 dim: 224 dim: 224 } } }

train

name: "GoogleNet" layer { name: "data" type: "Data" top: "data" top: "label" include { phase: TRAIN } transform_param { mirror: true crop_size: 224 mean_value: 104 mean_value: 117 mean_value: 123 } data_param { source: "examples/imagenet/ilsvrc12_train_lmdb" batch_size: 32 backend: LMDB } } layer { name: "data" type: "Data" top: "data" top: "label" include { phase: TEST } transform_param { mirror: false crop_size: 224 mean_value: 104 mean_value: 117 mean_value: 123 } data_param { source: "examples/imagenet/ilsvrc12_val_lmdb" batch_size: 50 backend: LMDB } }