GitHub

基于视觉注意力机制的细粒度图像分类方法代码仓库

环境包版本 requirements.txt：

matplotlib==3.1.3
numpy==1.18.1
pandas==1.0.3
Pillow==7.0.0
pycparser==2.19
pyparsing==2.4.6
python-dateutil==2.8.1
pytz==2019.3
scikit-learn==0.22.1
scipy==1.4.1
six==1.14.0
torch==1.4.0
torchvision==0.5.0

使用方法

下载数据集放到./data/目录下
训练使用 python GCN_STN_BLN.py
测试已训练好的model，从这里(提取码 flr8)下载三个state_dict，然后运行testCode.py

(PyTorch) shipeiqu1998@torch:~/LT$ python testCode.py 
Test accuracy on CUB_200_2011 dataset is 85.95%

Name		Name	Last commit message	Last commit date
Latest commit History 50 Commits
data		data
.gitignore		.gitignore
AIRCRAFT_loader.py		AIRCRAFT_loader.py
CARS_loader.py		CARS_loader.py
CGLoader.py		CGLoader.py
CUB_loader.py		CUB_loader.py
ChannelGrouping.py		ChannelGrouping.py
CompactBilinearPooling.py		CompactBilinearPooling.py
GCLables.csv		GCLables.csv
GCN_CBLN.py		GCN_CBLN.py
GCN_STN_BLN.py		GCN_STN_BLN.py
README.md		README.md
bilinaerWithStn.py		bilinaerWithStn.py
bilinear_cnn.py		bilinear_cnn.py
channelClusterResult.csv		channelClusterResult.csv
channelPeakPos.csv		channelPeakPos.csv
dataMaker.py		dataMaker.py
getChannelGroup.py		getChannelGroup.py
main.py		main.py
make_3_GroupClusterData.py		make_3_GroupClusterData.py
myDataLoader.py		myDataLoader.py
plotResult.py		plotResult.py
preTrainChannelGroupNet.py		preTrainChannelGroupNet.py
requirements.txt		requirements.txt
stn.py		stn.py
testCode.py		testCode.py

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Repository files navigation

基于视觉注意力机制的细粒度图像分类方法代码仓库

使用方法

About

Releases

Packages

Languages

hefan1/PyTorch

Folders and files

Latest commit

History

Repository files navigation

基于视觉注意力机制的细粒度图像分类方法 代码仓库

使用方法

About

Resources

Stars

Watchers

Forks

Releases

Packages 0

Languages

基于视觉注意力机制的细粒度图像分类方法代码仓库

Packages