Day #244 - Data Annotation Guidelines

• Quality of Images and capturing significant traits like styles / shapes / colors
• Object to annotate captured from nearest possible view (Best Possible Angle)
• Impact of poor background light / night and too far images. Discard low quality / poor miniature of objects (Occurs in edges of image)
• Handling partial objects
• When Annotating multiple objects the class imbalance factors between them, Fix before training. Analyzing Number of Objects, Occurrences - Distribution for Sampling balances
• Check for Data set impacts for Daylight / Night and annotate / train / build model accordingly

Guideline - The object under training occupies the center spot / nearest closest better view to know the side / front or reasonably good amount of features like color / styles

Good data / quality data is as important than the model / approach we take.

Happy Mastering DL!!!