IGN
Datasets
All datasets matching “IGN”quantum-like-attention-framework-1.3b-untuned-validation
Quantum Like Attention Framework (Q.L.A.F) 1.3b untuned
This repository contains the model checkpoints, downstream evaluation scores, and pretraining convergence logs for the Quantum Like Attention Framework (Q.L.A.F) 1.3B configuration.
Key Specifications & Architecture
Model Name: Q.L.A.F 1.3b untuned (Quantum Like Attention Framework - Hybrid Architecture)
Parameters: 1.3B parameters total configuration (327M active parameter student subset)
Layer Count: 12… See the full description on the dataset page: https://huggingface.co/datasets/IgnisCogitationis/quantum-like-attention-framework-1.3b-untuned-validation.PASTIS-HD
🌱 PASTIS-HD 🌿 Panoptic Agricultural Satellite TIme Series : optical time series, radar time series and very high resolution image
PASTIS is a benchmark dataset for panoptic and semantic segmentation of agricultural parcels from satellite time series.
It contains 2,433 patches within the French metropolitan territory with panoptic annotations (instance index + semantic label for each pixel).
Each patch is a Sentinel-2 multispectral image time series of variable lentgh.
This… See the full description on the dataset page: https://huggingface.co/datasets/IGNF/PASTIS-HD.FLAIR-HUB
FLAIR-HUB : Large-scale Multimodal Dataset for Land Cover and Crop Mapping
FLAIR-HUB builds upon and includes the FLAIR#1 and FLAIR#2 datasets, expanding them into a unified, large-scale, multi-sensor land-cover resource with very-high-resolution
annotations. Spanning over 2,500 km² of diverse French ecoclimates and landscapes, it features 63 billion hand-annotated pixels across 19 land-cover and
23 crop type classes.
The dataset integrates complementary data sources including… See the full description on the dataset page: https://huggingface.co/datasets/IGNF/FLAIR-HUB.FLAIR-1-2
Dataset Card for FLAIR land-cover semantic segmentation
Context & Data
The hereby FLAIR (#1 and #2) dataset is sampled countrywide and is composed of over 20 billion annotated pixels of very high resolution aerial imagery at 0.2 m spatial resolution, acquired over three years and different months (spatio-temporal domains).
Aerial imagery patches consist of 5 channels (RVB-Near Infrared-Elevation) and have corresponding annotation (with 19 semantic classes or 13 for the… See the full description on the dataset page: https://huggingface.co/datasets/IGNF/FLAIR-1-2.TreeSatAI-Time-Series
TreeSatAI-Time-Series
This dataset was introduced in the ECCV24 paper OmniSat.
Ahlswede et al. (https://essd.copernicus.org/articles/15/681/2023/) introduced the TreeSatAI Benchmark Archive, a new dataset for tree species classification in Central Europe based on multi-sensor data from aerial,
Sentinel-1 and Sentinel-2. The dataset contains labels of 20 European tree species (i.e., 15 tree genera) derived from forest administration data of the federal state of Lower Saxony… See the full description on the dataset page: https://huggingface.co/datasets/IGNF/TreeSatAI-Time-Series.IGNITE-fire-dataset
IGNITE: A Multimodal UAV-Collected Dataset for Wildfire Detection
IGNITE contains radiometric FLIR TIFF frames aligned with RGB video frames from four UAV-collected prescribed-fire sequences. The release includes 1,854 approved aligned samples. Processing code and release provenance are available in the companion GitHub repository.
Dataset Viewer
Each Viewer row is one aligned sample. The five image columns are:
thermal: display rendering of the radiometric… See the full description on the dataset page: https://huggingface.co/datasets/Kyoma001/IGNITE-fire-dataset.
figDesigns in components, not screens. Sends you the one variant you were avoiding.
pixelIcons, spacing, and the pixel you were going to leave at 13px.
bloomWordmarks, colour and the restraint to use one accent.
dexDesigns endpoints that survive their second consumer.
arcDraws the boundary you've been avoiding, then costs out both sides of it.