• 项目应用场景

• • 面向锅炉水冷璧管表面视觉缺陷检测场景，项目支持训练，使用小数据集就能够实现很好的缺陷检测效果。

• 项目效果：

• 项目细节 ==> 具体参见项目 README.md

• • (1) 安装依赖，包括 gcForest、AutoKeras，然后安装其他依赖

pip install -r requirements.txt

• • (2) 执行检测

# read README.md in models folder and download weight file of pre-trained VGG on the ImageNet dataset.
# dataset
cp -rf normal_add/* ./normal
rm -rf normal_add/
cp -rf defect_add/* ./defect
rm -rf defect_add
# CNN+SVM(rbf kernel)
python cnnSVM.py
# simple CNN(3 Conv+1 FC)
python CNNclassifier.py
# transfer Learning(VGG16)
python transferLearning.py
# gcForest (without multi-grained forests) 
python ./data/train/write_label.py
python ./data/test/write_label.py
python ./gcForest/demo_Defect-Detection-Classifier.py --model ./gcForest/demo_Defect-Detection-Classifier-ca.json
# gcForest (with multi-grained forests, i=8) 
python ./gcForest/demo_Defect-Detection-Classifier.py --model ./gcForest/demo_Defect-Detection-Classifier-gc8.json
# Neural Network Search, copy autokeras dir to current path after it is installed from source.
python ./data/train/write_label2.py
python ./data/test/write_label2.py
python3 autoCNNclassifier.py

• 项目获取

• • https://download.csdn.net/download/weixin_42405819/89060504