This is the Linux app named Raster Vision whose latest release can be downloaded as RasterVision0.21.3sourcecode.zip. It can be run online in the free hosting provider OnWorks for workstations.
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Raster Vision
DESCRIPTION
Raster Vision is an open source framework for Python developers building computer vision models on satellite, aerial, and other large imagery sets (including oblique drone imagery). There is built-in support for chip classification, object detection, and semantic segmentation using PyTorch. Raster Vision allows engineers to quickly and repeatably configure pipelines that go through core components of a machine learning workflow: analyzing training data, creating training chips, training models, creating predictions, evaluating models, and bundling the model files and configuration for easy deployment. The input to a Raster Vision pipeline is a set of images and training data, optionally with Areas of Interest (AOIs) that describe where the images are labeled. The output of a Raster Vision pipeline is a model bundle that allows you to easily utilize models in various deployment scenarios.
Features
- Gather dataset-level statistics and metrics for use in downstream processes
- Create training chips from a variety of image and label sources
- Train a model using a “backend” such as PyTorch
- Make predictions using trained models on validation and test data
- Derive evaluation metrics such as F1 score, precision and recall against the model’s predictions on validation datasets
- Bundle the trained model and associated configuration into a model bundle, which can be deployed in batch processes, live servers, and other workflows
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/raster-vision.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
