This short course shows you how to build reliable vision datasets and configure detection models with confidence. You’ll learn how to run a quality-controlled annotation process, review bounding boxes, coach annotators, and check dataset consistency using IoU-based audits. You’ll also explore how to analyze object sizes with clustering to generate anchor box parameters for models like YOLOv8. Through compact videos, guided readings, and hands-on exercises, you’ll practice using tools such as CVAT and Python notebooks to complete tasks common in production vision teams. By the end, you’ll be able to create a clean bounding-box dataset and use real measurements to tune model anchors—skills that support robust, scalable computer-vision pipelines.
Annotate and Analyze Objects for Vision
Annotate and Analyze Objects for Vision
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要了解的详细信息
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积累特定领域的专业知识
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- 通过实践项目培养工作相关技能
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该课程共有1个模块
This short course shows you how to build reliable vision datasets and configure detection models with confidence. You’ll learn how to run a quality-controlled annotation process, review bounding boxes, coach annotators, and check dataset consistency using IoU-based audits. You’ll also explore how to analyze object sizes with clustering to generate anchor box parameters for models like YOLOv8. Through compact videos, guided readings, and hands-on exercises, you’ll practice using tools such as CVAT and Python notebooks to complete tasks common in production vision teams. By the end, you’ll be able to create a clean bounding-box dataset and use real measurements to tune model anchors—skills that support robust, scalable computer-vision pipelines.
涵盖的内容
7个视频4篇阅读材料3个作业
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人们为什么选择 Coursera 来帮助自己实现职业发展
Felipe M.
Jennifer J.
Larry W.
Chaitanya A.
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University of California, Davis
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