From ac0ebf77f5b21fafad5f635413f510338f5ae084 Mon Sep 17 00:00:00 2001 From: "robin.cole@earthdaily.com" Date: Tue, 4 Jun 2024 06:12:28 +0100 Subject: [PATCH] Update README.md --- README.md | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/README.md b/README.md index bcd84a1..dbccb50 100644 --- a/README.md +++ b/README.md @@ -340,6 +340,13 @@ For semantic segmentation with Sentinel 2 * [dfc2022-baseline](https://github.com/isaaccorley/dfc2022-baseline) -> baseline solution to the 2022 IEEE GRSS Data Fusion Contest (DFC2022) using TorchGeo, PyTorch Lightning, and Segmentation Models PyTorch to train a U-Net with a ResNet-18 backbone and a loss function of Focal + Dice loss to perform semantic segmentation on the DFC2022 dataset * https://github.com/mveo/mveo-challenge +## FLAIR +Semantic segmentation and domain adaptation challenge proposed by the French National Institute of Geographical and Forest Information (IGN). Uses a dataset composed of over 70,000 aerial imagery patches with pixel-based annotations and 50,000 Sentinel-2 satellite acquisitions. +* [Challenge on codalab](https://codalab.lisn.upsaclay.fr/competitions/13447) +* [FLAIR-2 github](https://github.com/IGNF/FLAIR-2) +* [flair-2 8th place solution](https://github.com/association-rosia/flair-2) +* [IGNF HuggingFace](https://huggingface.co/IGNF) + ## ISPRS Semantic segmentation dataset. 38 patches of 6000x6000 pixels, each consisting of a true orthophoto (TOP) extracted from a larger TOP mosaic, and a DSM. Resolution 5 cm * https://www.isprs.org/education/benchmarks/UrbanSemLab/2d-sem-label-potsdam.aspx @@ -566,6 +573,7 @@ Since there is a whole community around GEE I will not reproduce it here but lis * [OpenSARWake](https://github.com/libzzluo/OpenSARWake) -> A SAR ship wake rotation detection benchmark dataset. * [TUE-CD](https://github.com/RSMagneto/MSI-Net) -> A change detection detection for building damage estimation after earthquake * [Overhead Wind Turbine Dataset - NAIP](https://zenodo.org/records/7385227#.Y419qezMLdr) +* [RRSD300](https://github.com/chdwyb/RSHazeNet) -> Remote Sensing Image Dehazing Dataset ## Kaggle Kaggle hosts over > 200 satellite image datasets, [search results here](https://www.kaggle.com/search?q=satellite+image+in%3Adatasets).