Defect-Classification-AOI-Aidea

Automated Optical Inspection (AOI) [1] is a high-speed and high-precision optical image inspection system that uses machine vision as the standard inspection technology to improve the shortcomings of traditional manual inspection using optical instruments.

In the training process I use the single CNN models using Efficient Net. I change the epochs and learning rate of the model manually, I don't use an automatic learning rate at the time.

Steps

1. Here we use the data from Industrial Technology Research Institute - Aidea to classify the defect. Unzip the file, it includes:

• train_images.zip： 2528 images.
• test_images.zip：10142 images.
• train.csv：two columns, ID and Label respectively.
• test.csv：two columns, ID and Label respectively.
• ID is for the name of the png file. Label is for the class (0: normal, 1: void, 2: horizontal defect, 3: vertical defect, 4: edge defect, 5: particle)

2. Create a folder. Put the file inside the floder. And create

• Train_image
• Test_image
• Run the py file.

Results

99.45745 % in accuracy (27th)

Reference

https://aidea-web.tw/topic/285ef3be-44eb-43dd-85cc-f0388bf85ea4?lang=en

Special Thanks

Asia University Taiwan - AI Summer Program 2023
Aidea