loopbio

Loopy Video Analysis and Tracking Features

• Tracking

  Track One or Multiple Subjects in Videos

  Loopy includes a number of general purpose algorithms for tracking the position of subjects in videos, including common laboratory model species, such as zebrafish, larvae, mice, and many more. Loopy includes barcode tracking functionality, and an easy to use tracking wizard, which helps to determine an optimal set of tracking parameters for your experiment.

  For even more challenging tracking problems, Loopy is the only all-in-one software which lets you train and then immediately use, your own custom deep learning based tracking solution.

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• Deep Learning

  Animal and Pose Tracking using Deep Learning

  Conventional image processing requires tedious hand tuning of parameters and strong visual differences between the animal and the background, usually resulting in poor solutions.

  Deep learning based models learn how to locate the animals when provided with a small fraction of the videos annotated, even working in data collected in the field. Loopy lets you train your own deep learning tracking solution for single and multiple animal and animal-pose tracking.

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• 3D

  3D Tracking of Animal Movement

  The real world is not two dimensional, and neither should your science be. Loopy includes tools for tracking and reconstructing the position of single or multiple animals or subject body parts - including using deep learning to detect and track previously manually impossible to track attributes.

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• Coding

  Scoring and Coding of Subject Behavior

  Loopy includes a powerful and efficient interface for coding focal or non-focal subject behavior from videos. One can code the occurrence and duration of events for multiple individuals. The tool also includes support for coding social paradigms where the directed interaction between individuals can be recorded. Loopy also includes plotting and analysis tools for understanding coded behavior.

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• Annotation

  Annotation of Subject Position or Attributes

  Loopy includes a web-based tool for annotating objects in videos. Collected annotation information, which can be bounding-box (rectangle) or object coordinates, can be used for training your own custom deep learning models, 3D tracking, or the raw data can downloaded for use in your own analyses.

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• Proc​essing

  Video Editing and General Video Processing Operations

  Loopy comes with a number of general purpose image processing algorithms including slow-motion and timelapse, video generation, audio waveform and spectrogram visualisation, OCR, color and white-balance correction and much more. These operations can be used to pre-process videos before tracking, or as stand-alone tools.

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Video and Metadata Management

Managing large sets of videos can be a challenging task. Videos can come from a variety of sources and it can be easy to mislabel or confuse similar data. Loopy includes powerful features for attaching structured metadata to videos and then using this metadata for organization and navigation throughout the site.

For example, you can define a project which requires entering the genotype, treatment, age, or any other label or tag you define, to all uploaded videos.

Projects describe the types of metadata that must be attached to videos.

Many types of metadata are available: numbers text, dates, etc.

When uploading a video you can choose to associate it with a project. In this case, Loopy ensures that you have filled out all the required metadata before making the video available for analysis.

Compulsory metadata enforcement can help with license, regulatory, or experimental protocol compliance by ensuring all necessary information is collected. If you have a large number of users or an on-site instance then it can be used to ensure all members of your research group adhere to the same naming, reporting and data management standards.

Until the required metadata has been supplied, videos are held in a special 'quarantine'.

If you have multiple projects you can choose to browse the site 'as this project'. This means that only videos, and data related to those videos, from the selected project are shown.