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data for 'Task Feature Decoupling YOLOv8n Realizes Power Adapter Appearance Defect Detection'
- Citation Author(s):
- Submitted by:
- Jie Chen
- Last updated:
- Thu, 05/16/2024 - 08:18
- DOI:
- 10.21227/tfk9-r934
- Data Format:
- License:
50 Views- Categories:
- Keywords:
Abstract
This data set is from the pictures collected at the industrial production site of the power adapter.The dataset contains surface defects such as scratches, glue spills, dirt, dirty spots, and off-frame labels that occur during the production process of the power adapter. The original dataset contains 235 images with a height and width of 2448 and 2048, which are annotated in VOC2007 format. These defects were categorized into five classes: label, mark, scratch, smudge, and spill, with each class containing 32, 38, 58, 80, and 32 images.
This data set is from the pictures collected at the industrial production site of the power adapter.The dataset contains surface defects such as scratches, glue spills, dirt, dirty spots, and off-frame labels that occur during the production process of the power adapter. The original dataset contains 235 images with a height and width of 2448 and 2048, which are annotated in VOC2007 format. These defects were categorized into five classes: label, mark, scratch, smudge, and spill, with each class containing 32, 38, 58, 80, and 32 images.
