Published October 10, 2019
| Version v1
Dataset
Open
BarkNet 1.0
Contributors
Contact person (2):
Data collector:
- 1. Université Laval
Description
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 for species recognition.
Files
BOJ.zip
Files
(32.3 GB)
| Name | Size | |
|---|---|---|
|
md5:58a42fd886eb18697c012383bb6c3f23
|
1.2 GB | Preview Download |
|
md5:8abf29b918827c89ddafc430639a201c
|
1.0 GB | Preview Download |
|
md5:fd0d493f2486b0a0fae8c17c529856fd
|
3.8 GB | Preview Download |
|
md5:3e5e7ccb86ecfbdb040996b78880da0b
|
741.4 MB | Preview Download |
|
md5:5eddd7a8e9c9a996a5a800795ba9351d
|
1.6 GB | Preview Download |
|
md5:7390243052d68f78be922a1dab4965a7
|
1.4 GB | Preview Download |
|
md5:8210a9df074be6f012ecba5c1ed49898
|
781.7 MB | Preview Download |
|
md5:a8644eb05d2daf4a11f03e8e89d8a543
|
98.1 MB | Preview Download |
|
md5:25643c6795a486aea53388c62882b9ad
|
2.1 GB | Preview Download |
|
md5:114f0e5f07bb1b7d7e0a1fafbb472876
|
3.1 GB | Preview Download |
|
md5:f4dfb3f7cbcf58a00aa6093af7b5ed8d
|
2.5 GB | Preview Download |
|
md5:380d583182c3527c5c6ed8c737a380be
|
767.6 MB | Preview Download |
|
md5:e9206271b6bc7b842159dea6e02d986f
|
4.2 GB | Preview Download |
|
md5:5ee52763647dc44cc7ddff9658a81021
|
1.4 GB | Preview Download |
|
md5:b56d0b5c72f4a6957e4a4e85b391e702
|
1.0 GB | Preview Download |
|
md5:6bcd5c2f990c9892e8dde79f4efa41d1
|
99.1 MB | Preview Download |
|
md5:cdc598f39c90bb9178e29f95296a6a6c
|
2.3 GB | Preview Download |
|
md5:3f83595f4f5687d64f60c6e70d66c11d
|
959.9 MB | Preview Download |
|
md5:9405c256e02356eea5bfb10c1e3e7285
|
86.2 MB | Preview Download |
|
md5:58eb5772bbd44390817fb44cd32634df
|
580.6 MB | Preview Download |
|
md5:7ab1d81dd203af811ec9ea98e172c4a0
|
891.1 MB | Preview Download |
|
md5:62b5850b714588ebdad03080ec8f3cb2
|
1.3 kB | Preview Download |
|
md5:b964677842de65112c2de4dc5db462cb
|
1.1 GB | Preview Download |
|
md5:9722c06366f1736fc582090af7fc27d5
|
673.7 MB | Preview Download |
Additional details
Related works
- Is published in
- Conference paper: 10.1109/IROS.2018.8593514 (DOI)
Software
- Repository URL
- https://github.com/ulaval-damas/tree-bark-classification