9 1 1

Cesar Luis Aybar Camacho

csaybar

http://csaybar.github.io/

AI & ML interests

anime

Recent Activity

updated a dataset 25 days ago

isp-uv-es/opensr-test

New activity 27 days ago

isp-uv-es/CloudSEN12Plus:Meaning of 5 classes for 2000x2000 tiles

New activity about 1 month ago

isp-uv-es/CloudSEN12Plus:Normalization of L1C Data

View all activity

Organizations

csaybar's activity

updated a dataset 25 days ago

isp-uv-es/opensr-test

Updated 25 days ago • 604 • 1

New activity in isp-uv-es/CloudSEN12Plus 27 days ago

Meaning of 5 classes for 2000x2000 tiles

#4 opened 28 days ago by

sblaise

New activity in isp-uv-es/CloudSEN12Plus about 1 month ago

Normalization of L1C Data

#3 opened about 1 month ago by

pmcelroy

updated a dataset about 1 month ago

csaybar/land_demo

Updated Oct 13 • 33

updated a dataset about 2 months ago

tacofoundation/tortilla_demo

Viewer • Updated Oct 4 • 8 • 39

updated 2 datasets 2 months ago

tacofoundation/SEN2NAIPv2-synthethic1

Viewer • Updated Sep 22 • 62.2k • 89

tacofoundation/SEN2NAIPv2-synthethic2

Viewer • Updated Sep 22 • 62.2k • 156

updated a Space 2 months ago

Running

💻

README

updated a dataset 2 months ago

tacofoundation/SEN2NAIPv2-real

Viewer • Updated Sep 21 • 8k • 64

Reacted to aliFrancis's post with 🤗 3 months ago

Post

🗺 Major TOM: Expandable Datasets for Earth Observation

🚨 RECORD-BREAKING EO DATASET: the largest ever ML-ready Sentinel-2 dataset! It covers almost every single point on Earth captured by the Copernicus Sentinel-2 satellite. @mikonvergence and I are thrilled to finally announce the release of Major-TOM/Core-S2L2A and Major-TOM/Core-S2L1C

🌍 About half of the entire planet is covered. That's 2,245,886 patches of 1068 x 1068 pixels, available in both L1C and L2A. At 10 m resolution, we've got 256 million square km with over 2.5 trillion pixels. It's all yours with a few lines of code. See the paper linked below 🔽 for more info!

🧱 And this is just the beginning. We are currently preparing more datasets from different satellites for the Major TOM org. TOM stands for Terrestrial Observation Metaset - a simple set of rules for building an ecosystem of ML-ready EO datasets, which can be seamlessly combined as if they were Lego bricks.

🚴‍♀️ Want to take the dataset for a spin? We have a viewer app on spaces that lets you go anywhere on Earth and shows you the data, if its available Major-TOM/MajorTOM-Core-Viewer

📰 Preprint paper: Major TOM: Expandable Datasets for Earth Observation (2402.12095)
💻 Colab example: https://colab.research.google.com/github/ESA-PhiLab/Major-TOM/blob/main/03-Filtering-in-Colab.ipynb

Thank you to the amazing 🤗Hugging Face team for the support on this one! @osanseviero @lhoestq @BrigitteTousi