predator-vision | Movement-triggered real-time heatmap from your webcam | Graphics library

by idevelop JavaScript Version: Current License: MIT

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kandi X-RAY | predator-vision Summary

predator-vision is a JavaScript library typically used in User Interface, Graphics, Tensorflow, Three.js, WebGL applications. predator-vision has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Movement-triggered real-time heatmap from your webcam

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predator-vision has a low active ecosystem.

It has 87 star(s) with 25 fork(s). There are 5 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 2 have been closed. On average issues are closed in 613 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of predator-vision is current.

Quality

predator-vision has 0 bugs and 0 code smells.

Security

predator-vision has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

predator-vision code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

predator-vision is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

predator-vision releases are not available. You will need to build from source code and install.

predator-vision saves you 36 person hours of effort in developing the same functionality from scratch.

It has 98 lines of code, 0 functions and 6 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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predator-vision Key Features

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predator-vision Examples and Code Snippets

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Community Discussions

Trending Discussions on predator-vision

Only one processor being used while running NetLogo models using parApply

QUESTION

Only one processor being used while running NetLogo models using parApply

Asked 2017-Feb-13 at 14:39

I am using the 'RNetLogo' package to run sensitivity analyses on my NetLogo model. My model has 24 parameters I need to vary - so parallelising this process would be ideal! I've been following along with the example in Thiele's "Parallel processing with the RNetLogo package" vignette, which uses the 'parallel' package in conjunction with 'RNetLogo'.

I've managed to get R to initialise the NetLogo model across all 12 of my processors, which I've verified using gui=TRUE. The problem comes when I try to run the simulation code across the 12 processors using 'parApply'. This line runs without error, but it only runs on one of the processors (using around 8% of my total CPU power). Here's a mock up of my R code file - I've included some commented-out code at the end, showing how I run the simulation without trying to parallelise:

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ANSWER

Answered 2017-Feb-13 at 14:39

I am still in the process of applying a similar technique to perform a Morris Elementary Effects screening with my NetLogo model. For me the parallel execution works fine. I compared your script to mine and noticed that in my version the 'parApply' call of the simulation function (simfun) is embedded in a function statement (see below). Maybe including the function already solves your issue.

Source https://stackoverflow.com/questions/42197208

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