A Common Language for EO Machine Learning Data
Project description
mlstac
A Common Language for EO Machine Learning Data
import mlstac
# Read the data online
path = "https://huggingface.co/datasets/JulioContrerasH/prueba1/resolve/main/images_2000.mlstac"
metadata = mlstac.core.load_metadata(path)
data = mlstac.core.load_data(metadata[0:4])
data.shape
# Read the data locally
path = "/home/cesar/Downloads/images_2000.mlstac"
dataset = mlstac.core.load_metadata(path)
data = mlstac.core.load_data(dataset[0:4])
# From mlstac to GEOTIFF
import rasterio as rio
path = "https://huggingface.co/datasets/JulioContrerasH/prueba1/resolve/main/images_2000.mlstac"
metadata = mlstac.core.load_metadata(path)
data, metadata = mlstac.core.load_data(metadata[0:1], save_metadata_datapoint=True)[0]
with rio.open("data.tif", "w", **metadata) as dst:
dst.write(data)
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
mlstac-0.1.3.tar.gz
(23.4 kB
view details)
Built Distribution
mlstac-0.1.3-py3-none-any.whl
(29.3 kB
view details)
File details
Details for the file mlstac-0.1.3.tar.gz.
File metadata
- Download URL: mlstac-0.1.3.tar.gz
- Upload date:
- Size: 23.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 colorama/0.4.4 importlib-metadata/7.0.1 keyring/24.3.1 pkginfo/1.9.6 readme-renderer/34.0 requests-toolbelt/1.0.0 requests/2.32.3 rfc3986/1.5.0 tqdm/4.66.1 urllib3/2.2.1 CPython/3.10.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 1b246e0ac453c7c23edda67e733daf7317dc6bcb11897d5e6ce4900c6a594a69 |
|
| MD5 | 87bf71c399d3a96b358e534b5c44567a |
|
| BLAKE2b-256 | 2b4cdfd94925db86b655688ab80e1252fc58594cb6479d4b1f8d505109c64102 |
File details
Details for the file mlstac-0.1.3-py3-none-any.whl.
File metadata
- Download URL: mlstac-0.1.3-py3-none-any.whl
- Upload date:
- Size: 29.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 colorama/0.4.4 importlib-metadata/7.0.1 keyring/24.3.1 pkginfo/1.9.6 readme-renderer/34.0 requests-toolbelt/1.0.0 requests/2.32.3 rfc3986/1.5.0 tqdm/4.66.1 urllib3/2.2.1 CPython/3.10.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 7564a42199b2f7c8f7dd4d85db68b53cbc52e9be8d84b824ce2a3506e8a2a21e |
|
| MD5 | d31aeb4b259a0c21a7d3e9b4efab188f |
|
| BLAKE2b-256 | 313c0244176fc4e3f47433410f051d4cf7c47d336a59e2de94c2f9cfeff73f94 |
