Team Kyogre at Smart India Hackathon 2022
Code and resources from Team Kyogre's winning participation in Smart India Hackathon, Software Edition, 2022.
India
Pinned Repositories
.github
EyeSea_Awesome-Underwater-Datasets
Pointers to large-scale underwater datasets and relevant resources.
EyeSea_DL-for-Species-Classification
Deep learning models for classification of underwater species from underwater images.
EyeSea_Image-Preprocessing-Algorithms
Callable image enhancement and restoration APIs in Python. Preprocessing experiments and applicators for EyeSea.
EyeSea_Video-Frame-Processing
Real-time video frames depduplication and processing algorithm for frame-wise image processing.
satvision-mapviewer-frontend
SatVision_Land-Cover-Detection
Deep learning for land cover detection from medium resolution satellite imagery
SatVision_MapViewer-Backend
Backend workflows for SatVision's real-time satellite image and land cover segmentation renderer. Deploys the novel patchify-process-reconstruct approach to run DL-driven segmentation inference in real-time.
SatVision_ML-Pipelining-Utils
Utilities to prepare the pipeline elements that integrate into SatVision: deep learning model inference, preprocessing, data acquisition, and post processing.
SatVision_Satellite-Image-Acquisition
Pluggable interfaces and session management wrappers for Sentinel-Hub. Experiments, workflows, and tests to acquire a real-time feed of medium resolution satellite images from any Sentinel-Hub -supported satellites. Sentinel-2 (ESA), Landsat-8 (NASA), and Resourcesat (ISRO) satellites, etc.
Team Kyogre at Smart India Hackathon 2022's Repositories
SIH-22-Kyogre/SatVision_Satellite-Image-Acquisition
Pluggable interfaces and session management wrappers for Sentinel-Hub. Experiments, workflows, and tests to acquire a real-time feed of medium resolution satellite images from any Sentinel-Hub -supported satellites. Sentinel-2 (ESA), Landsat-8 (NASA), and Resourcesat (ISRO) satellites, etc.
SIH-22-Kyogre/.github
SIH-22-Kyogre/EyeSea_Awesome-Underwater-Datasets
Pointers to large-scale underwater datasets and relevant resources.
SIH-22-Kyogre/EyeSea_DL-for-Species-Classification
Deep learning models for classification of underwater species from underwater images.
SIH-22-Kyogre/EyeSea_Image-Preprocessing-Algorithms
Callable image enhancement and restoration APIs in Python. Preprocessing experiments and applicators for EyeSea.
SIH-22-Kyogre/EyeSea_Video-Frame-Processing
Real-time video frames depduplication and processing algorithm for frame-wise image processing.
SIH-22-Kyogre/satvision-mapviewer-frontend
SIH-22-Kyogre/SatVision_Land-Cover-Detection
Deep learning for land cover detection from medium resolution satellite imagery
SIH-22-Kyogre/SatVision_MapViewer-Backend
Backend workflows for SatVision's real-time satellite image and land cover segmentation renderer. Deploys the novel patchify-process-reconstruct approach to run DL-driven segmentation inference in real-time.
SIH-22-Kyogre/SatVision_ML-Pipelining-Utils
Utilities to prepare the pipeline elements that integrate into SatVision: deep learning model inference, preprocessing, data acquisition, and post processing.