茶树嫩芽采摘数据

嫩叶是制作优质茶叶的重要原料，采集茶树嫩芽长势监测图像，利用机器视觉技术分析茶树嫩叶占比，并通过茶叶专家给出的茶叶采摘值，实现茶叶嫩芽长势自动识别，帮助茶农提供及时的采摘嫩芽时机，提高生产效率和品质。1数据来源
在茶园部署物联网摄像头，每天采集茶树嫩叶长势图像数据，自动上传到服务器。采集数据字段包括采集时间、设备id、识别图片。
2.数据处理
2.1基于opencv色域转换算法，将图像转换到hsv色域空间。
2.2根据嫩叶的色域范围，hsv色域分割算法提取处茶树树叶图像中嫩叶的位置，基于轮廓提取等算法，找到图像中属于茶树树叶的范围，计算在嫩叶色域范围内的像素点数量占图像总像素的比列、以及茶树树叶像素点数量占图像总像素的比例，再通过计算嫩叶占比来评估茶树嫩叶长势情况：
嫩叶占比=嫩叶像素占比/树叶像素占比。
2.3 设置采摘预警为0.4，即当嫩叶占比大于0.4时，采摘预警为1，提示采摘茶叶。
3.数据应用
嫩叶是制作优质茶叶的重要原料，采集茶树嫩芽长势监测图像，利用机器视觉技术分析茶树嫩叶占比，并通过茶叶专家给出的茶叶采摘值，实现茶叶嫩芽长势自动识别，帮助茶农提供及时的采摘嫩芽时机，提高生产效率和品质。

Young leaves are critical raw materials for manufacturing high-quality tea. This dataset collects growth monitoring images of tea tree tender shoots, employs machine vision techniques to analyze the proportion of young tea leaves, and integrates tea picking thresholds provided by tea experts to achieve automatic recognition of tea shoot growth status, thereby helping tea farmers determine the optimal picking timing promptly and enhancing production efficiency and quality.

1. Data Source
IoT cameras are deployed in tea gardens to collect daily image data of young tea leaf growth, which are automatically uploaded to the server. The collected data fields include collection time, device ID, and recognized images.

2. Data Processing
2.1 Utilize the OpenCV color gamut conversion algorithm to convert images into the HSV color space.
2.2 Based on the color gamut range of young leaves, the HSV color gamut segmentation algorithm extracts the positions of young leaves from tea tree leaf images. Algorithms such as contour extraction are applied to identify the regions belonging to tea tree leaves in the images. Calculate the proportion of pixels within the young leaf color gamut range to the total pixels of the image, as well as the proportion of tea tree leaf pixels to the total pixels of the image. Then evaluate the growth status of tea tree young leaves by computing the young leaf proportion:
Young Leaf Proportion = Young Leaf Pixel Proportion / Leaf Pixel Proportion.
2.3 Set the picking warning threshold to 0.4, i.e., when the young leaf proportion exceeds 0.4, the picking warning is set to 1, which prompts tea picking.

3. Data Application
Young leaves are critical raw materials for manufacturing high-quality tea. This dataset collects growth monitoring images of tea tree tender shoots, employs machine vision techniques to analyze the proportion of young tea leaves, and integrates tea picking thresholds provided by tea experts to achieve automatic recognition of tea shoot growth status, thereby helping tea farmers determine the optimal picking timing promptly and enhancing production efficiency and quality.

搜集汇总

数据集介绍

特点

茶树嫩芽采摘数据是一个用于监测茶树嫩叶长势的企业数据集，包含65536条记录，通过机器视觉技术分析嫩叶占比，帮助茶农提高采摘效率和茶叶品质。