kandi background
Explore Kits

PRiMEStereoMatch | fully parallel stereo matching algorithm for depth | Computer Vision library

 by   PRiME-project C++ Version: Current License: Non-SPDX

 by   PRiME-project C++ Version: Current License: Non-SPDX

Download this library from

kandi X-RAY | PRiMEStereoMatch Summary

PRiMEStereoMatch is a C++ library typically used in Artificial Intelligence, Computer Vision, Deep Learning, OpenCV applications. PRiMEStereoMatch has no bugs, it has no vulnerabilities and it has low support. However PRiMEStereoMatch has a Non-SPDX License. You can download it from GitHub.
Please use these citations in your publication if you use this work: (bibtex here). Charles Leech, Charan Kumar, Amit Acharyya, Sheng Yang, Geoff V. Merrett, and Bashir M. Al-Hashimi. 2017. Runtime Performance and Power Optimization of Parallel Disparity Estimation on Many-Core Platforms. ACM Transactions on Embedded Computing Systems (TECS) Volume 17 Issue 2, Article 41 (November 2017), 19 pages. DOI: https://doi.org/10.1145/3133560. Leech, Charles (2018) Runtime energy management of multi-core processors. University of Southampton, Doctoral Thesis, 293pp.
Support
Support
Quality
Quality
Security
Security
License
License
Reuse
Reuse

kandi-support Support

  • PRiMEStereoMatch has a low active ecosystem.
  • It has 194 star(s) with 56 fork(s). There are 17 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 3 open issues and 2 have been closed. On average issues are closed in 289 days. There are no pull requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of PRiMEStereoMatch is current.
PRiMEStereoMatch Support
Best in #Computer Vision
Average in #Computer Vision
PRiMEStereoMatch Support
Best in #Computer Vision
Average in #Computer Vision

quality kandi Quality

  • PRiMEStereoMatch has no bugs reported.
PRiMEStereoMatch Quality
Best in #Computer Vision
Average in #Computer Vision
PRiMEStereoMatch Quality
Best in #Computer Vision
Average in #Computer Vision

securitySecurity

  • PRiMEStereoMatch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
PRiMEStereoMatch Security
Best in #Computer Vision
Average in #Computer Vision
PRiMEStereoMatch Security
Best in #Computer Vision
Average in #Computer Vision

license License

  • PRiMEStereoMatch has a Non-SPDX License.
  • Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.
PRiMEStereoMatch License
Best in #Computer Vision
Average in #Computer Vision
PRiMEStereoMatch License
Best in #Computer Vision
Average in #Computer Vision

buildReuse

  • PRiMEStereoMatch releases are not available. You will need to build from source code and install.
  • Installation instructions are not available. Examples and code snippets are available.
PRiMEStereoMatch Reuse
Best in #Computer Vision
Average in #Computer Vision
PRiMEStereoMatch Reuse
Best in #Computer Vision
Average in #Computer Vision
Top functions reviewed by kandi - BETA

kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample Here

Get all kandi verified functions for this library.

Get all kandi verified functions for this library.

PRiMEStereoMatch Key Features

A heterogeneous and fully parallel stereo matching algorithm for depth estimation, implementing a local adaptive support weight (ADSW) Guided Image Filter (GIF) cost aggregation stage. Developed in both C++ and OpenCL.

PRiMEStereoMatch Examples and Code Snippets

See all related Code Snippets

Directory Structure

copy iconCopydownload iconDownload
folders:
	assets			- OpenCL kernel files
	data			- program data including input images, stereo camera parameters, calibration images
	docs			- images for the readme & wiki
	include			- Project header files (h/hpp)
	src			- Project source files (c/cpp)
	
files:
	CMakeLists.txt		- cmake project compilation file
	LICENCE.txt			- license file
	README.md			- this readme file

License

copy iconCopydownload iconDownload
@article{Leech:2017:RPP:3160927.3133560,
 author = {Leech, Charles and Kumar, Charan and Acharyya, Amit and Yang, Sheng and Merrett, Geoff V. and Al-Hashimi, Bashir M.},
 title = {Runtime Performance and Power Optimization of Parallel Disparity Estimation on Many-Core Platforms},
 journal = {ACM Transactions on Embedded Computing Systems (TECS)},
 issue_date = {January 2018},
 volume = {17},
 number = {2},
 month = nov,
 year = {2017},
 issn = {1539-9087},
 pages = {41:1--41:19},
 articleno = {41},
 numpages = {19},
 url = {http://doi.acm.org/10.1145/3133560},
 doi = {10.1145/3133560},
 acmid = {3133560},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {Runtime management, computer vision, many-core platforms, power optimization},
} 

See all related Code Snippets

Community Discussions

Trending Discussions on Computer Vision
  • Image similarity in swift
  • When using pandas_profiling: "ModuleNotFoundError: No module named 'visions.application'"
  • Classify handwritten text using Google Cloud Vision
  • cv2 findChessboardCorners does not detect corners
  • Fastest way to get the RGB average inside of a non-rectangular contour in the CMSampleBuffer
  • UIViewController can't override method from it's superclass
  • X and Y-axis swapped in Vision Framework Swift
  • Swift's Vision framework not recognizing Japanese characters
  • Boxing large objects in image containing both large and small objects of similar color and in high density from a picture
  • Create a LabVIEW IMAQ image from a binary buffer/file with and without NI Vision
Trending Discussions on Computer Vision

QUESTION

Image similarity in swift

Asked 2022-Mar-25 at 11:42

The swift vision similarity feature is able to assign a number to the variance between 2 images. Where 0 variance between the images, means the images are the same. As the number increases this that there is more and more variance between the images.

What I am trying to do is turn this into a percentage of similarity. So one image is for example 80% similar to the other image. Any ideas how I could arrange the logic to accomplish this:

import UIKit
import Vision
func featureprintObservationForImage(atURL url: URL) -> VNFeaturePrintObservation? {
let requestHandler = VNImageRequestHandler(url: url, options: [:])
let request = VNGenerateImageFeaturePrintRequest()
do {
  try requestHandler.perform([request])
  return request.results?.first as? VNFeaturePrintObservation
} catch {
  print("Vision error: \(error)")
  return nil
}
  }
 let apple1 = featureprintObservationForImage(atURL: Bundle.main.url(forResource:"apple1", withExtension: "jpg")!)
let apple2 = featureprintObservationForImage(atURL: Bundle.main.url(forResource:"apple2", withExtension: "jpg")!)
let pear = featureprintObservationForImage(atURL: Bundle.main.url(forResource:"pear", withExtension: "jpg")!)
var distance = Float(0)
try apple1!.computeDistance(&distance, to: apple2!)
var distance2 = Float(0)
try apple1!.computeDistance(&distance2, to: pear!)

ANSWER

Answered 2022-Mar-25 at 10:26

It depends on how you want to scale it. If you just want the percentage you could just use Float.greatestFiniteMagnitude as the maximum value.

1-(distance/Float.greatestFiniteMagnitude)*100

A better solution would probably be to set a lower ceiling and everything above that ceiling would just be 0% similarity.

1-(min(distance, 10)/10)*100

Here the artificial ceiling would be 10, but it can be any arbitrary number.

Source https://stackoverflow.com/questions/71615277

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install PRiMEStereoMatch

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

DOWNLOAD this Library from

Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from
over 430 million Knowledge Items
Find more libraries
Reuse Solution Kits and Libraries Curated by Popular Use Cases
Explore Kits

Save this library and start creating your kit

Share this Page

share link
Reuse Pre-built Kits with PRiMEStereoMatch
Consider Popular Computer Vision Libraries
Try Top Libraries by PRiME-project
Compare Computer Vision Libraries with Highest Support
Compare Computer Vision Libraries with Highest Quality
Compare Computer Vision Libraries with Highest Security
Compare Computer Vision Libraries with Permissive License
Compare Computer Vision Libraries with Highest Reuse
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from
over 430 million Knowledge Items
Find more libraries
Reuse Solution Kits and Libraries Curated by Popular Use Cases
Explore Kits

Save this library and start creating your kit

  • © 2022 Open Weaver Inc.