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A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health in Python
A data generation pipeline for creating semi-realistic synthetic multi-object videos with rich annotations such as instance segmentation masks, depth maps, and optical flow.
A data augmentations library for audio, image, text, and video.
FFCV: Fast Forward Computer Vision (and other ML workloads!)
AiTLAS implements state-of-the-art AI methods for exploratory and predictive analysis of satellite images.
Serve, optimize and scale PyTorch models in production
Apache Superset is a Data Visualization and Data Exploration Platform
This is a Python Flask application server. The purpose of this app is to illustrate how a geospatial API can be created in Flask.
Learning Geospatial Analysis with Python – Third Edition, published by Packt
The SpaceNet 7 Baseline Algorithm
CosmiQ Works Geospatial Machine Learning Analysis Toolkit
Urban Spatial Data Analysis Method--Python Implementation /代码为caDesign（cadesign.cn）设计研究中“python知识系统部分”即"城市空间数据分析方法——PYTHON语言实现"。
A curated list of awesome resources for semantic understanding of aerial scene
A library for solving the satellite structure from motion problem
[NeurIPS 2021] Code for Unsupervised Learning of Compositional Energy Concepts
A curated list of awesome tools, tutorials, code, projects, links, stuff about Earth Observation, Geospatial Satellite Imagery
PyTorch implementation of popular datasets and models in remote sensing
bottle.py is a fast and simple micro-framework for python web-applications.
6D - Pose Annotation Tool (6D-PAT) - is a tool that allows the user to load a set of images and also a set of 3D models and annotate where in the 2D image the 3D object ist placed.
Set of methods to ensemble boxes from different object detection models, including implementation of "Weighted boxes fusion (WBF)" method.
Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning
A PyTorch library and evaluation platform for end-to-end compression research
Open source implementation of "Spreading Vectors for Similarity Search"
The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
Open Source Deep Learning Serving System with Web Interface
Model summary in PyTorch similar to `model.summary()` in Keras