Dstl_unet
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Sahi | 3,340 |  | 12 | 3 months ago | 101 | November 05, 2023 | 11 | mit | Python | |
| Framework agnostic sliced/tiled inference + interactive ui + error analysis plots | ||||||||||
| Raster Vision | 1,956 |  | 7 | 3 months ago | 11 | October 17, 2023 | 42 | other | Python | |
| An open source library and framework for deep learning on satellite and aerial imagery. | ||||||||||
| Ternausnetv2 | 500 | 4 years ago | 14 | bsd-3-clause | Jupyter Notebook | |||||
| TernausNetV2: Fully Convolutional Network for Instance Segmentation | ||||||||||
| Label Maker | 358 | 3 years ago | 18 | November 19, 2020 | 40 | mit | Python | |||
| Data Preparation for Satellite Machine Learning | ||||||||||
| Torchsat | 285 | 4 years ago | 4 | April 20, 2018 | 3 | mit | Python | |||
| 🔥TorchSat 🌏 is an open-source deep learning framework for satellite imagery analysis based on PyTorch. | ||||||||||
| Eye In The Sky | 248 | 2 years ago | 6 | apache-2.0 | Python | |||||
| Satellite Image Classification using semantic segmentation methods in deep learning | ||||||||||
| Geospatial Machine Learning | 196 | 6 years ago | mit | |||||||
| A curated list of resources focused on Machine Learning in Geospatial Data Science. | ||||||||||
| Keras Unet | 194 | 3 years ago | 7 | July 27, 2020 | 8 | mit | Python | |||
| Helper package with multiple U-Net implementations in Keras as well as useful utility tools helpful when working with image semantic segmentation tasks. This library and underlying tools come from multiple projects I performed working on semantic segmentation tasks | ||||||||||
| Delta | 169 | 2 years ago | 2 | apache-2.0 | Python | |||||
| Deep Learning for Satellite Imagery | ||||||||||
| Aitlas | 157 | 9 months ago | 2 | apache-2.0 | Python | |||||
| AiTLAS implements state-of-the-art AI methods for exploratory and predictive analysis of satellite images. | ||||||||||
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Unet