2018 Baidu merchant signboard classification and testing contest：2018百度商家招牌的分类与检测大赛
This is a summary of my participation in the classification and testing competition of 2018 Baidu merchant signs. Competition homepage: [百度]（https://dianshi.baidu.com/competition/17/rule）。
The project runs on win10 + anaconada. You can also use other environments to run.
The program uses the InceptionV3 model for fine-tuning, and the final classification accuracy is 0.995.
I also tried to use resnet50, vgg16, Xception...they can also get a nice result.
As the project supervisor reason unable to attend the semi-finals
The final fully connected layer and category output layer of the network has changed according to the number of categories of actual classified items. You can also try to make different changes.
python = 3.6.0
tensorflow >= 1.7.0
keras > = 2.1.3
argparse
matplotlib
data_pre.py : Divide the training set into a training set and a validation set.
data_arguement.py : Data enhancement,The default is to enhance 1 to 8 images.
finetune_model.py : Use this script to train.
finetune_model_test.py : Use this script to test.
Before enhancement
| datasets
| test
|image1.jpg
image2.jpg
...
| train
|image1.jpg
image2.jpg
...
| test.txt
| train.txt
After enhancement
| datasets
| test
|image1.jpg
image2.jpg
...
| train
| 1
|image1.jpg
image2.jpg
...
| 2
|image1.jpg
image2.jpg
...
...
| valid
| 1
|image1.jpg
image2.jpg
...
| 2
|image1.jpg
image2.jpg
...
...
| test.txt
| train.txt
Txt file format : image name + label.
