番茄花-3类

1. 简介番茄花 3 类数据集旨在训练深度学习模型并协助自动机器人授粉系统，包含番茄花的 YOLO 格式标记图像，按生物学发育阶段分为 3 类，可支持机器人在温室或田间环境的细粒度视觉感知；3 个类别及对应实例数量分别为：花蕾（0 类，闭合或部分开放、不适合授粉，43908 个对象实例）、开花（1 类，完全开放、准备授粉，27629 个对象实例）、花后（2 类，过最佳授粉阶段、衰老，6727 个对象实例）；其核心目标是帮助智能系统确定授粉最佳阶段，避免未成熟或已授粉花朵，提升机器人授粉流程的精度和有效性

1. Introduction
The 3-class tomato flower dataset is designed for training deep learning models and assisting automatic robotic pollination systems. It contains YOLO-formatted annotated images of tomato flowers, categorized into three groups based on biological developmental stages, enabling fine-grained visual perception for robots operating in greenhouse or field environments. The three categories and their corresponding instance counts are listed below:
- Bud (Class 0: closed or partially open, unsuitable for pollination; 43,908 object instances)
- Full bloom (Class 1: fully open and ready for pollination; 27,629 object instances)
- Post-bloom (Class 2: past the optimal pollination stage and senescent; 6,727 object instances)
Its core objective is to help intelligent systems identify the optimal pollination stage, avoid immature or already pollinated flowers, and improve the accuracy and effectiveness of robotic pollination workflows.

搜集汇总

背景与挑战

背景概述

番茄花-3类数据集是一个用于训练深度学习模型以支持自动机器人授粉系统的数据集，包含按发育阶段分类的番茄花图像和YOLO格式标记文件，分为花蕾、开花和花后3类，适用于农业机器人视觉感知技术的研究与开发。