nasaharvest / presto

Lightweight, Pre-trained Transformers for Remote Sensing Timeseries
https://arxiv.org/abs/2304.14065
MIT License
151 stars 26 forks source link

Data access #1

Open gabrieltseng opened 1 year ago

gabrieltseng commented 1 year ago

Data is currently stored in a private google cloud bucket. We will need to move it to a more generally accessible location (likely Zenodo).

GISScience commented 1 year ago

or, upload in google drive or drop box. please also provide the pre-trained model to check.

gabrieltseng commented 1 year ago

or, upload in google drive or drop box. please also provide the pre-trained model to check.

The pretrained model is available on github. From #4 :

The trained model is available here: https://github.com/nasaharvest/presto/blob/main/data/default_model.pt You can load the pretrained model with the following code:

from presto import Presto
encoder_decoder = Presto.load_pretrained()

where load_pretrained just loads the state dict in default_model.pt.

Struggling10000 commented 7 months ago

Could you please provide the datasets used in the eval model?

gabrieltseng commented 7 months ago

Hi @Struggling10000 ,

Which datasets are you interested in? 3 of the datasets are publicly available:

  1. EuroSat (the readme has instructions on downloading)
  2. TreeSat, which should be downloaded into this folder (I'll add some instructions making this explicit update: instructions added in the readme).
  3. CropHarvest, which is automatically downloaded when you run the CropHarvest eval task.

Adding the fuel moisture and algae blooms data to Zenodo is on my todos!