This is the Windows 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.
Download and run online this app named Raster Vision with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.
- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application and install it.
- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.
Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.
SCREENSHOTS
Ad
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.
