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YISA Final

文件说明

原始数据

imges_orginal/image

训练数据的原始图像（10000）

laebles.txt

训练数据的原始标签txt文件

images/image

复赛试题图像

py程序说明及中间处理文件

retrain.py

重训练文件 使用retrain.sh来重新训练Inception V3网络

model_dir/

Inception V3网络

bottlenecks/image

Inception V3网络训练后的图像的特征（10000,2048）

image_labels_dir/

Inception V3网络需要的特征文件夹，选取特征过程不需要，可以为空

image_test/

测试文件顺序创建的文件夹

log/

Inception V3网络训练过程log文件

Model/

Inception V3网络模型

bottlen_handle.py

将图像特征导入至bottlencks.csv文件中

img_data.py

统计并查看image的信息

img_handle.py

尺寸归一化image（可以不需要）（已经abandon）

txt_handle.py

针对多标签神经网络的txt构建（已经abandon）

check_order.py

检查文件的顺序是否和label.txt的顺序一致

randomtree_**_smo.py

随机森林模型，使用SMOTE对数据进行平衡

pro_**.csv

预测的概率文件，为最后的输出提供数据

retrained_graph.pb

神经网络模型图

str_out.txt

格式处理后并提交的文件

target.csv

使用txt_handle.py 从train.txt中提出的标签文件，并且删除了image名字列

tmp*.txt

测试顺序的临时文件

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