classifier study based on caffe

Deps

prepare datasets
create the related soft links to caffe
1_dataset.py: generate train and test dataset lists, and write class name label list
2_images_to_lmdb.sh: convert images to lmdb format
3_compute_image_mean.sh: get image mean values
modify the prototxt files, and prepare to train and test

Name		Name	Last commit message	Last commit date
Latest commit History 17 Commits
AlexNet		AlexNet
DenseNet		DenseNet
GoogLeNet		GoogLeNet
LeNet		LeNet
ResNet		ResNet
SqeezeNet_v1.1		SqeezeNet_v1.1
VGG		VGG
WRN28_10		WRN28_10
data		data
examples		examples
models		models
multilabel		multilabel
netvisualize		netvisualize
nin		nin
testimages		testimages
.gitignore		.gitignore
1_create_dataset_lists.py		1_create_dataset_lists.py
2_images_to_lmdb.sh		2_images_to_lmdb.sh
3_compute_image_mean.sh		3_compute_image_mean.sh
README.md		README.md
TEST.md		TEST.md
caffe		caffe
classification		classification
compute_image_mean		compute_image_mean
convert_imageset		convert_imageset
extract_features.bin		extract_features.bin
genImgsMultiPatches.py		genImgsMultiPatches.py
layerfeature_visualize.py		layerfeature_visualize.py
multi_convert_imageset		multi_convert_imageset