A benchmark designed to advance foundation models for Earth monitoring, tailored for remote sensing. It encompasses six classification and six segmentation tasks, curated for precision and model evaluation. The package also features a comprehensive evaluation methodology and showcases results from 20 established baseline models.
Project description
GEO-Bench: Toward Foundation Models for Earth Monitoring
GeoBench is a ServiceNow Research project.
GEO-Bench is a General Earth Observation benchmark for evaluating the performances of large pre-trained models on geospatial data. Read the full paper for usage details and evaluation of existing pre-trained vision models.
Installation
You can install GEO-Bench with pip:
pip install geo-benchmark
Downloading the data
Set $GEO_BENCH_DIR
to your preferred location. If not set, it will be stored in $HOME/dataset/geobench
.
Next, use the download script. This will automatically download from Zenodo
Run the command:
geobench-download
The current version of the benchmark is 0.9.1. It will soon be updated to incorporate minor changes
This will download all datasets in parallel. If some files are already downloaded, it will verify the md5 checksum. Feel free to restart the downloader if it is interrupted or if you get Error: TOO MANY REQUESTS
.
m-bigearthnet
takes the longest time and Zenodo is a bit slow some days.
Test installation
Optionnaly run tests:
geobench-test
Loading Datasets
See example_load_dataset.py
for how to iterate over datasets.
import geobench
for task in geobench.task_iterator(benchmark_name="classification_v0.9.1"):
dataset = task.get_dataset(split="train")
sample = dataset[0]
for band in sample.bands:
print(f"{band.band_info.name}: {band.data.shape}")
Visualizing Results
See the notebook baseline_results.ipynb
for an example of how to visualize the results.
Project details
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