Bangladeshi Fruit Dataset: Classification and Analysis of Seven Native Species for Agricultural Research

This dataset includes 28,500 annotated images of seven tropical fruit species, combining both raw and augmented images to support machine learning applications in fruit detection, classification, and recognition. Key highlights include:
• Total Images: 28,500 (5,470 raw + 23,030 augmented)
• Species: Apple, Banana, Date, Grape, Guava, Orange, Papaya
• Augmentation Techniques: Rotation, scaling, brightness adjustments, contrast variations
• Content: Captures variability in backgrounds, lighting, and maturity stages
• Applications: Agricultural monitoring, biodiversity research, species identification, and AI-based solutions
• Purpose: Enhances machine learning model accuracy and resilience in real-world scenarios

本数据集包含28500张带标注的热带水果图像，涵盖7个品类，整合原始图像与增强图像以支持水果检测、分类与识别相关的机器学习应用。核心亮点如下：
• 总图像量：28500张（其中原始图像5470张，增强图像23030张）
• 覆盖品类：苹果、香蕉、椰枣、葡萄、番石榴、橙子、木瓜
• 图像增强技术：旋转、缩放、亮度调节、对比度调整
• 图像内容：涵盖背景、光照及成熟度的多样变化
• 应用场景：农业监测、生物多样性研究、物种识别及各类人工智能解决方案
• 设计目标：提升机器学习模型在真实场景中的准确率与鲁棒性