TeaLeafAgeQuality: Age-Stratified Tea Leaf Quality Classification Dataset

The "TeaLeafAgeQuality" dataset is curated for tea leaf classification, detection and quality prediction based on leaf age. This dataset encompasses a comprehensive collection of tea leaf images categorized into four classes corresponding to their age-based quality:

Category T1: Age 1 and 2 days, representing the highest quality tea leaves. (562 Raw Images)
Category T2: Age 3 to 4 days, indicating good quality tea leaves. (615 Raw Images)
Category T3: Age 5 to 7 days, indicating average or below-average quality tea leaves. (508 Raw Images)
Category T4: Age 7+ days, denoting tea leaves unsuitable for brewing drinkable tea. (523 Raw Images)

Each category includes images depicting tea leaves at various stages of their age progression, facilitating research and analysis into the relationship between leaf age and tea quality. The dataset aims to contribute to the advancement of deep learning models for tea leaf classification and quality assessment.

This dataset comprises three versions: the first is raw, unannotated data, offering a pure, unmodified collection of tea leaves collected from the different tea gardens located at Sylhet, Bangladesh. The second version includes precise annotations, classified into four categories: T1, T2, T3, and T4, for targeted analysis. Finally, the third version contains both annotated and augmented data, enhancing the dataset for more advanced research applications. Each version caters to different levels of data analysis, from basic to complex.