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Desktop open source interactive software system for facilitating the precise annotation of benthic species in orthophoto of the bottom of the sea. Python [5] GPL [6] [7] VoTT (Visual Object Tagging Tool) Free and open source electron app for image annotation and labeling developed by Microsoft. TypeScript/Electron (Windows, Linux, macOS) MIT ...
Eclipse ImageJ Plugin - An plugin which integrates ImageJ in a flexible tabbed view interface and also offers a powerful macro editor with a debugging interface. [14] Bitplane - producers of image processing software with ImageJ compatibility; CellProfiler, a software package for high-throughput image analysis by interactive construction of ...
VoTT (Visual Object Tagging Tool) is a free and open source Electron app for image annotation and labeling developed by Microsoft. [1] The software is written in the TypeScript programming language and used for building end-to-end object detection models from image and videos assets for computer vision algorithms.
This is a list of free and open-source software (FOSS) packages, computer software licensed under free software licenses and open-source licenses.Software that fits the Free Software Definition may be more appropriately called free software; the GNU project in particular objects to their works being referred to as open-source. [1]
Eclipse Deeplearning4j is a programming library written in Java for the Java virtual machine (JVM). [ 2 ] [ 3 ] It is a framework with wide support for deep learning algorithms. [ 4 ] Deeplearning4j includes implementations of the restricted Boltzmann machine , deep belief net , deep autoencoder, stacked denoising autoencoder and recursive ...
Fiji [4] [5] is an open source image processing package based on ImageJ2. Fiji's main purpose is to provide a distribution of ImageJ2 with many bundled plugins. Fiji features an integrated updating system and aims to provide users with a coherent menu structure, extensive documentation in the form of detailed algorithm descriptions and ...
Classification, object detection, object localization 2017 [56] M. Kragh et al. Daimler Monocular Pedestrian Detection dataset It is a dataset of pedestrians in urban environments. Pedestrians are box-wise labeled. Labeled part contains 15560 samples with pedestrians and 6744 samples without. Test set contains 21790 images without labels. Images
CVIP has the ability to read various image formats, including TIFF, PNG, GIF, JPEG, BMP, and RAW formats. It supports standard image processing functions, image compression, restoration, logical and arithmetical operations between images, contrast manipulation, image sharpening, frequency transformation, edge detection, segmentation, and geometric transformations.