metadata
dataset_info:
features:
- name: height
dtype: int64
- name: width
dtype: int64
- name: fold
dtype: string
- name: raster_name
dtype: string
- name: location
dtype: string
- name: image
dtype: image
- name: tile_name
dtype: string
- name: annotations
struct:
- name: bbox
sequence:
sequence: float64
- name: segmentation
dtype: 'null'
- name: area
sequence: float64
- name: iscrowd
sequence: int64
- name: is_rle_format
dtype: 'null'
- name: category
sequence: string
- name: tile_metadata
struct:
- name: crs
dtype: string
- name: transform
sequence: float64
- name: bounds
sequence: float64
- name: width
dtype: int64
- name: height
dtype: int64
- name: count
dtype: int64
- name: dtypes
sequence: string
- name: nodata
dtype: 'null'
splits:
- name: train
num_bytes: 16884458976
num_examples: 585
- name: validation
num_bytes: 2786536280
num_examples: 387
- name: test
num_bytes: 11729504363.402
num_examples: 1477
download_size: 31336873232
dataset_size: 31400499619.402
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
license: cc-by-4.0
SelvaBox: A high-resolution dataset for tropical tree
This is the version of the SelvaBox dataset that has been pre-processed and presented in our SelvaBox paper.
The dataset is made of 14 rasters resampled at 4.5 cm GSD, from three different countries: Brazil, Ecuador and Panama. It comprises over 83 000 human bounding box annotations for tropical tree crowns in dense canopies.
Training tiles are 3555x3555 pixels, while validation and test tiles are 1777x1777 pixels, equivalent to 80x80 meters spatial extent. There is 50% overlap between train and validation tiles, and 75% between test tiles (to ensure that the largest trees of 50+ meters in diameter will fit entirely in at least one tile).
Link to our paper will come soon.