Open-source alternatives to Geo Data Viewer

This is an open-source autonomous driving perception pipeline that processes camera and lidar sensor data to detect, track, and fuse objects in real-world driving environments. The project integrates an end-to-end perception workflow combining sensor calibration, deep learning object detection, Kalman filter tracking, and sensor fusion for robust scene understanding. The pipeline includes camera calibration tools to remove lens distortion from raw images, deep learning model training for object classification and detection, and multi-object tracking using Kalman filters with data association

This project serves as a comprehensive educational resource and curriculum for mastering machine learning and deep learning within the Python data science ecosystem. It provides a structured collection of tutorials and code examples designed to guide users through the end-to-end process of building, training, and deploying predictive models. The material focuses on practical implementation, covering the construction of machine learning pipelines that integrate data processing, feature engineering, and model training. It distinguishes itself by offering hands-on guidance for complex domains, i

Remove stripes from images with a combined wavelet/FFT approach

A Python tool to perform deep learning experiments on various hyperspectral datasets.

AugLy is a multimodal data augmentation library and machine learning dataset augmentor. It provides a system for generating synthetic variations of training data across audio, image, text, and video datasets to increase sample diversity and improve model robustness. The library functions as a multimedia noise simulator, specifically designed to mimic real-world user captures by overlaying social media templates and internet artifacts onto media. It includes a data provenance tracker to record the specific transformations and intensity levels applied to each piece of augmented data. The tool

imagededup is a Python library used for finding exact and near-duplicate images. It provides utilities for generating image fingerprints, computing neural embeddings, and evaluating the precision of deduplication processes. The tool utilizes perceptual hashing to identify visually similar files regardless of size or format and employs deep learning models to encode images into vectors for high-accuracy similarity searches. It includes a system for measuring the precision and recall of these processes by comparing results against known ground truth datasets. The library covers broader capabil

ImageHash

Kornia is a differentiable computer vision library and cross-framework tensor vision toolset. It implements vision operations as differentiable tensors to enable integration into deep learning pipelines and supports the transpilation of operations across PyTorch, TensorFlow, JAX, and NumPy. The project provides specialized toolsets for geometric vision and stereo depth, including algorithms for 3D scene reconstruction, camera calibration, and pose estimation. It further distinguishes itself as a differentiable image augmentation framework, applying random geometric and color transformations w

This repository holds both the frontend web-application and backend server that make up our "Land Cover Mapping" tool.

Ning Zhang, Lin Zhang*, and Zaixi Cheng

Tiler is an image mosaic generator and tiling engine designed to assemble large composite images by arranging a collection of smaller tiles to match a target visual. It functions as a tool for algorithmic art composition, mapping source image fragments to target pixel data. The system includes a mosaic tile library generator that produces multiple colored versions and rotations of a source image. This process expands the available tile set to increase the accuracy of the final composite visual. The project handles the technical process of mosaic creation through grid-based spatial partitioni

SAHI is a sliced inference framework and computer vision pipeline designed to detect small objects in high-resolution images. It provides a system for dividing large images into overlapping patches to prevent the detail loss that typically occurs during standard model downscaling, alongside an image tiling utility and a COCO dataset toolkit. The project distinguishes itself by offering a model-agnostic prediction wrapper that standardizes different machine learning frameworks into a unified interface. This allows it to implement sliced inference and object detection across various model backe

A noGDAL tool for reading geotiff files

This project is a Python wrapper for the OpenCV computer vision library, providing a bridge that exposes high-performance C++ functions to the Python programming language. It serves as a collection of tools for real-time image processing, object detection, and machine learning on visual data. The project provides precompiled binary distributions, allowing for the integration of vision capabilities into Python applications without requiring a local C++ compiler. It offers multi-variant package distributions, including headless versions designed for server or cloud environments where a graphica

xbatcher: Batch Generation from Xarray Datasets

PhotoPrism is a self-hosted digital asset management platform designed to organize, classify, and manage large collections of photos and videos on personal infrastructure. It functions as a private alternative to cloud-based services, ensuring that all media remains under the user's control. The platform utilizes neural-network-based media analysis to automatically detect objects, faces, and locations, providing a comprehensive, AI-powered approach to library organization. The project distinguishes itself through its containerized architecture, which simplifies deployment and lifecycle manage

Satellite imagery for dummies.

Deep learning docker files and docker images for geospatial anaysis. It contains the most popular deep learning frameworks(PyTorch and Tensorflow) with CPU and GPU support (CUDA and cuDNN included). And some other commonly used packages in machine learning and geospatial anaysis.

TorchSat is an open-source deep learning framework for satellite imagery analysis based on PyTorch.

nvtop is a terminal-based dashboard used for monitoring the performance, memory usage, and temperature of multiple graphics processors and hardware accelerators. It functions as a centralized administration tool to track the health and compute load of several devices across a single system. The tool distinguishes itself by correlating system process IDs with hardware resource consumption, allowing users to identify specific applications consuming GPU resources. It employs a vendor-agnostic abstraction layer to support hardware from multiple different manufacturers within a single interface.

A module to programmatically create geotiff images which can be used for unit tests.

Hub is a multimodal AI data lake and vector database designed for storing and querying embeddings, text, audio, and images. It functions as a dataset version control system and a machine learning data streaming engine to support large-scale model training. The system utilizes a serverless PostgreSQL vector store to index high-dimensional embeddings for semantic search. It provides a visual interface for inspecting multimodal datasets and viewing annotations such as bounding boxes and masks. The platform handles cloud-agnostic storage synchronization and implements lazy, compressed data strea

FiftyOne is a visual tool for curating, analyzing, and managing image and video datasets for machine learning model training. It serves as a platform for identifying annotation errors, refining ground truth labels, and evaluating vision model performance by comparing predictions against ground truth to identify failure modes. The system functions as a containerized data platform that supports team collaboration on large-scale visual datasets in a cloud environment. It includes specialized capabilities for exploring high-dimensional embeddings to discover data clusters and retrieve correspondi

Albumentations is a computer vision image augmentation library designed to increase training data diversity for deep learning models. It provides a toolset for applying geometric and color transformations to images and annotations, including a specialized collection of 3D operations for volumetric data used in medical and scientific imaging. The library functions as an image mask and bounding box transformer, automatically updating masks, bounding boxes, and keypoints when images undergo geometric changes. This ensures that spatial alterations remain synchronized across images and their assoc

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A tiny Python library for writing multi-channel TIFF stacks.