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mkluczek mikonvergence commited on
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Adding SSL4EO embeddings based on S1RTC Major-TOM with metadata and readme version 1.0

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+ *.7z filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ *.tar.* filter=lfs diff=lfs merge=lfs -text
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+ *.zst filter=lfs diff=lfs merge=lfs -text
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+ # Audio files - uncompressed
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+ *.pcm filter=lfs diff=lfs merge=lfs -text
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+ *.sam filter=lfs diff=lfs merge=lfs -text
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+ *.raw filter=lfs diff=lfs merge=lfs -text
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+ *.ogg filter=lfs diff=lfs merge=lfs -text
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+ *.wav filter=lfs diff=lfs merge=lfs -text
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+ # Image files - uncompressed
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+ *.bmp filter=lfs diff=lfs merge=lfs -text
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+ *.png filter=lfs diff=lfs merge=lfs -text
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+ *.tiff filter=lfs diff=lfs merge=lfs -text
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+ # Image files - compressed
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+ *.jpg filter=lfs diff=lfs merge=lfs -text
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+ *.jpeg filter=lfs diff=lfs merge=lfs -text
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+ *.webp filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ license: cc-by-sa-4.0
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+ tags:
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+ - embeddings
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+ - earth-observation
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+ - geospatial
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+ - remote-sesning
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+ - sentinel-1
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+ - sar
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+ - satellite
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+ - synthethic-aperture-radar
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+ - SSL4EO
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+ - satellite-imagery
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+ size_categories:
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+ - 10M<n<100M
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+ ---
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+
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6304c06eeb6d777a838eab63/_pmXpKIwlYdPWG7j-nR05.png)
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+ # Core-S1RTC-SSL4EO 📡⚡🛰️
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+ | Dataset | Modality | Number of Embeddings | Sensing Type | Total Comments | Source Dataset | Source Model | Size |
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+ |:--------:|:--------------:|:-------------------:|:------------:|:--------------:|:--------------:|:--------------:|:--------------:|
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+ |Core-S1RTC-SSL4EO|Sentinel-1 RTC|36,748,875|SAR|General-Purpose Global|[Core-S1RTC](https://huggingface.co/datasets/Major-TOM/Core-S1RTC)|[SSL4EO-ResNet50-MOCO](https://github.com/zhu-xlab/SSL4EO-S12)|332.5 GB|
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+
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+
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+ ## Content
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+ | Field | Type | Description |
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+ |:-----------------:|:--------:|-----------------------------------------------------------------------------|
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+ | unique_id | string | hash generated from geometry, time, product_id, and embedding model |
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+ | embedding | array | raw embedding array |
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+ | grid_cell | string | Major TOM cell |
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+ | grid_row_u | int | Major TOM cell row |
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+ | grid_col_r | int | Major TOM cell col |
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+ | product_id | string | ID of the original product |
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+ | timestamp | string | Timestamp of the sample |
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+ | centre_lat | float | Centre of the fragment latitude |
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+ | centre_lon | float | Centre of the fragment longitude |
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+ | geometry | geometry | Polygon footprint (WGS84) of the fragment |
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+ | utm_footprint | string | Polygon footprint (image UTM) of the fragment |
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+ | utm_crs | string | CRS of the original product |
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+ | pixel_bbox | bbox | Boundary box of the fragment (pixels)
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+
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+
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+ ## Input Data
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+ * Sentinel-1 RTC radar dataset global coverage
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+ * All samples from [**MajorTOM Core-S1RTC**](https://huggingface.co/datasets/Major-TOM/Core-S1RTC)
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+ * Image input size: **224 x 224** pixels, target overlap: 10%, border_shift: True
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+
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+ ## Model
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+ The image encoder of the [**SSL4EO-ResNet50-MOCO model**](https://github.com/zhu-xlab/SSL4EO-S12) was used to extract embeddings.
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+
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+ ## Example Use
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+ Interface scripts are available at
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+
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+ ```python
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+ from datasets import load_dataset
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+ dataset = load_dataset("Major-TOM/Core-S1RTC-SSL4EO")
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+ ```
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+
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+ ## Generate Your Own Embeddings
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+
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+ The [**embedder**](https://github.com/ESA-PhiLab/Major-TOM/tree/main/src/embedder) subpackage of Major TOM provides tools for generating embeddings like this ones. You can see an example of this in a dedicated notebook at (link).
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+ [![GitHub](https://img.shields.io/badge/GitHub-Generate%20Your%20Own%20Embeddings-blue?logo=github&style=flat-square)](https://github.com/ESA-PhiLab/Major-TOM/tree/main/src/embedder)
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+
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+
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+ ---
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+ ## Major TOM Global Embeddings Project 🏭
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+ This dataset is a result of a collaboration between [**CloudFerro**](https://cloudferro.com/) 🔶 and [**Φ-lab, European Space Agency (ESA)**](https://philab.esa.int/) 🛰️ set up in order to provide open and free vectorised expansions of Major TOM datasets and define a standardised manner for releasing Major TOM embedding expansions.
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+
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+ The embeddings extracted from common AI models make it possible to browse and navigate large datasets like Major TOM with reduced storage and computational demand.
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+
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+ The datasets were computed on the [**GPU-accelerated instances**](https://cloudferro.com/ai/ai-computing-services/)⚡ provided by [**CloudFerro**](https://cloudferro.com/) 🔶 on the [**CREODIAS**](https://creodias.eu/) cloud service platform 💻☁️.
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+ Discover more at [**CloudFerro AI services**](https://cloudferro.com/ai/).
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+
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+
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+ ## Authors
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+ [**Marcin Kluczek (CloudFerro)**](https://www.linkedin.com/in/marcin-kluczek-03852a1a8/), [**Mikolaj Czerkawski (Φ-lab, European Space Agency)**](https://mikonvergence.github.io), [**Jędrzej S. Bojanowski (CloudFerro)**](https://www.linkedin.com/in/j%C4%99drzej-s-bojanowski-a5059872/)
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+
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+ # Cite
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+ [![arxiv](https://img.shields.io/badge/Open_Access-arxiv:2402.12095-b31b1b)](https://arxiv.org/)
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+
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+
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+ Powered by [Φ-lab, European Space Agency (ESA) 🛰️](https://philab.esa.int/) in collaboration with [CloudFerro 🔶](https://cloudferro.com/)
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