Simple STAC Catalogs discovery tool.

Related tags

Deep Learninggeospatialwebmapstackeplerglstreamlit
Overview

STAC Catalog Discovery

Simple STAC discovery tool. Just paste the STAC Catalog link and press Enter.

Details

STAC Discovery tool enables discovering data in a given collection. The idea is to move from the approach of providing geometry and dates to discovering the whole catalog. The main idea is to showcase the value of using STAC specification in describing geospatial information. Just imagine how great would it be to have a single interface to browse geospatial data.

Please note, it is not the best tool to discover data from large data catalogs. Use tools that designed to return first N items for a given area of interest.

This STAC Discovery tool is based on the pystac-client v.0.3.1.

Known Limitations

  • ⚠️ It requires STAC spec v1.0.1
  • ⚠️ Number of items to return is limited to 25000
Owner
Mykola Kozyr
Product Manager. Location BI, Geospatial Services and Technologies
Mykola Kozyr
GitHub Repository https://share.streamlit.io/mykolakozyr/stacdiscovery/main/app.py
Adjust Decision Boundary for Class Imbalanced Learning

Adjusting Decision Boundary for Class Imbalanced Learning This repository is the official PyTorch implementation of WVN-RS, introduced in Adjusting De

Peyton Byungju Kim 16 Jan 04, 2023
SynNet - synthetic tree generation using neural networks

SynNet This repo contains the code and analysis scripts for our amortized approach to synthetic tree generation using neural networks. Our model can s

Wenhao Gao 60 Dec 29, 2022
PyTorch implementation of 'Gen-LaneNet: a generalized and scalable approach for 3D lane detection'

(pytorch) Gen-LaneNet: a generalized and scalable approach for 3D lane detection Introduction This is a pytorch implementation of Gen-LaneNet, which p

Yuliang Guo 233 Jan 06, 2023
PyTorch implementation of EigenGAN

PyTorch Implementation of EigenGAN Train python train.py [image_folder_path] --name [experiment name] Test python test.py [ckpt path] --traverse FFH

62 Nov 12, 2022
Minimal implementation of Denoised Smoothing: A Provable Defense for Pretrained Classifiers in TensorFlow.

Denoised-Smoothing-TF Minimal implementation of Denoised Smoothing: A Provable Defense for Pretrained Classifiers in TensorFlow. Denoised Smoothing is

Sayak Paul 19 Dec 11, 2022
[NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods

Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods Large Scale Learning on Non-Homophilous Graphs: New Benchmark

60 Jan 03, 2023
Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes

Neural Scene Flow Fields PyTorch implementation of paper "Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes", CVPR 2021 [Projec

Zhengqi Li 583 Dec 30, 2022
Codes for 'Dual Parameterization of Sparse Variational Gaussian Processes'

Dual Parameterization of Sparse Variational Gaussian Processes Documentation | Notebooks | API reference Introduction This repository is the official

AaltoML 7 Dec 23, 2022
ICCV2021 Oral SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks

Sign-Agnostic Convolutional Occupancy Networks Paper | Supplementary | Video | Teaser Video | Project Page This repository contains the implementation

64 Jan 05, 2023
NBEATSx: Neural basis expansion analysis with exogenous variables

NBEATSx: Neural basis expansion analysis with exogenous variables We extend the NBEATS model to incorporate exogenous factors. The resulting method, c

Cristian Challu 100 Dec 31, 2022
Framework for training options with different attention mechanism and using them to solve downstream tasks.

Using Attention in HRL Framework for training options with different attention mechanism and using them to solve downstream tasks. Requirements GPU re

5 Nov 03, 2022
A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling"

SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th

Zekarias Tilahun 24 Jun 21, 2022
Visual Question Answering in Pytorch

Visual Question Answering in pytorch /!\ New version of pytorch for VQA available here: https://github.com/Cadene/block.bootstrap.pytorch This repo wa

Remi 672 Jan 01, 2023
Awesome Monocular 3D detection

Awesome Monocular 3D detection Paper list of 3D detetction, keep updating! Contents Paper List 2022 2021 2020 2019 2018 2017 2016 KITTI Results Paper

Zhikang Zou 184 Jan 04, 2023
Range Image-based LiDAR Localization for Autonomous Vehicles Using Mesh Maps

Range Image-based 3D LiDAR Localization This repo contains the code for our ICRA2021 paper: Range Image-based LiDAR Localization for Autonomous Vehicl

Photogrammetry & Robotics Bonn 208 Dec 15, 2022
MDMM - Learning multi-domain multi-modality I2I translation

Multi-Domain Multi-Modality I2I translation Pytorch implementation of multi-modality I2I translation for multi-domains. The project is an extension to

Hsin-Ying Lee 107 Nov 04, 2022
Simple renderer for use with MuJoCo (>=2.1.2) Python Bindings.

Viewer for MuJoCo in Python Interactive renderer to use with the official Python bindings for MuJoCo. Starting with version 2.1.2, MuJoCo comes with n

Rohan P. Singh 62 Dec 30, 2022
Naszilla is a Python library for neural architecture search (NAS)

A repository to compare many popular NAS algorithms seamlessly across three popular benchmarks (NASBench 101, 201, and 301). You can implement your ow

270 Jan 03, 2023
This is the official repository of XVFI (eXtreme Video Frame Interpolation)

XVFI This is the official repository of XVFI (eXtreme Video Frame Interpolation), https://arxiv.org/abs/2103.16206 Last Update: 20210607 We provide th

Jihyong Oh 195 Dec 29, 2022
Plugin adapted from Ultralytics to bring YOLOv5 into Napari

napari-yolov5 Plugin adapted from Ultralytics to bring YOLOv5 into Napari. Training and detection can be done using the GUI. Training dataset must be

2 May 05, 2022