BarkNet 1.0 (Part 1 of 4)

(Part 1 out of 4) 23,000 cropped images of tree bark, for 23 species of trees around Quebec City, Canada. The images were captured at a distance between 20-60 cm away from the trunk. Labels include: individual tree ID, its species, and its DBH (diameter at breast height). Pictures were taken with four different devices: Nexus 5, Samsung Galaxy S5, Samsung Galaxy S7, and a Panasonic Lumix DMC-TS5 camera. The dataset is sufficiently large to train a Deep network such as ResNet.

（共4部分，本部分为第1部分）该数据集包含23000张经裁剪的树皮图像，涵盖加拿大魁北克市周边的23个树种。所有图像均采集于距离树干20至60厘米的位置，标注信息包含单棵树木的唯一标识、所属树种以及胸径（DBH, Diameter at Breast Height）。图像由四款不同设备拍摄：Nexus 5、三星Galaxy S5、三星Galaxy S7以及松下Lumix DMC-TS5相机。该数据集规模充足，可用于训练ResNet等深度神经网络。

搜集汇总

背景与挑战

背景概述

该数据集包含23,000张魁北克市23种树种的树皮图像，标注详细（个体ID、树种、胸径），由四种设备拍摄，适合深度学习模型训练。