This project forked from finlay-liu/baidu-dog2017
http://js.baidu.com/
使用各种Pre-trained的模型进行提取特征,并concat到一起,然后只用训练最后一层FC层,可复现线上0.173成绩.
TODO:数据扩充和物体检测.
代码使用方法:
# 提取VGG13特征,并进行保存
python torch_feature.py --model vgg13 --ffpath ./feature/vgg13.h5
# 提取DenseNet169特征,并进行保存
python torch_feature.py --model densenet169 --ffpath ./feature/densenet169.h5
# 使用提取的特征跑二层模型
python torch_l2.py
代码有问题请自己解决,谢谢,希望大家玩的开心!
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