Found 19 repositories(showing 19)
souvikmajumder26
🛣 Building an end-to-end Promptable Semantic Segmentation (Computer Vision) project from training to inferencing a model on LandCover.ai data (Satellite Imagery).
scrose
Python Landscape Classification Tool (PyLC) - PyTorch-based semantic segmentation network for land cover classification of oblique ground-based photography.
No description available
aicodecraft1004
No description available
VishalPainjane
A PyTorch implementation of DeepLabV3+ with an EfficientNet backbone for Land Use/Land Cover (LULC) semantic segmentation.
🛣 Building an end-to-end Promptable Semantic Segmentation (Computer Vision) project from training to inferencing a model on LandCover.ai data (Satellite Imagery).
XaXtric7
🛰️🌲Terra_Mask 2.0 is an end-to-end computer vision project for semantic segmentation in land cover classification. It uses deep learning with PyTorch to classify features in high-resolution satellite imagery — such as buildings, woodland, water, and roads.
xultaeculcis
Land Cover Semantic Segmentation using Pytorch-Lightning
thomasnynas12
Python Landscape Classification Tool (PyLC) - PyTorch-based semantic segmentation network for land cover classification of oblique ground-based photography.
XaXtric7
🛰️🌲Terra_Mask is an end-to-end computer vision project for semantic segmentation in land cover classification. It uses deep learning with PyTorch to classify features in high-resolution satellite imagery — such as buildings, woodland, water, and roads.
SelcukOzdemir23
EcoSat-Analyzer is a state-of-the-art Semantic Segmentation Web Application designed to analyze high-resolution aerial and satellite imagery. Built with PyTorch (U-Net), NiceGUI, and Docker, it identifies and segments land cover features like buildings, woodlands, water, and roads.
No description available
rsawankumar
No description available
No description available
MinitChitroda
No description available
Devguruparashar
Introducing Land-Cover-Semantic-Segmentation-PyTorch, a versatile Computer Vision project for Semantic Segmentation. Customize model parameters and select specific classes for inference, providing flexibility for diverse datasets and use cases.
No description available
a PyTorch Lightning + Segmentation Models Pytorch (SMP) ipynb for semantic segmentation tasks; example dataset uses satellite images from the DeepGlobe Land Cover Classification Challenge (2018)
HenriqueSAMartins
Deep learning U-Net model for 10-class semantic segmentation of multispectral satellite imagery (B, G, R, NIR channels). Includes PyTorch training pipeline, IoU/Dice metrics, and visualization tools for Earth observation and land cover classification.
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