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PaddleDetection | Object detection and instance segmentation toolkit based | Computer Vision library

 by   PaddlePaddle Python Version: v2.3.0 License: Apache-2.0

 by   PaddlePaddle Python Version: v2.3.0 License: Apache-2.0

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kandi X-RAY | PaddleDetection Summary

PaddleDetection is a Python library typically used in Artificial Intelligence, Computer Vision applications. PaddleDetection has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. However PaddleDetection has 5 bugs. You can install using 'pip install PaddleDetection' or download it from GitHub, PyPI.
Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
Support
Support
Quality
Quality
Security
Security
License
License
Reuse
Reuse

kandi-support Support

  • PaddleDetection has a medium active ecosystem.
  • It has 6559 star(s) with 1709 fork(s). There are 156 watchers for this library.
  • There were 2 major release(s) in the last 12 months.
  • There are 548 open issues and 2589 have been closed. On average issues are closed in 61 days. There are 68 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of PaddleDetection is v2.3.0
PaddleDetection Support
Best in #Computer Vision
Average in #Computer Vision
PaddleDetection Support
Best in #Computer Vision
Average in #Computer Vision

quality kandi Quality

  • PaddleDetection has 5 bugs (3 blocker, 0 critical, 1 major, 1 minor) and 232 code smells.
PaddleDetection Quality
Best in #Computer Vision
Average in #Computer Vision
PaddleDetection Quality
Best in #Computer Vision
Average in #Computer Vision

securitySecurity

  • PaddleDetection has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • PaddleDetection code analysis shows 0 unresolved vulnerabilities.
  • There are 31 security hotspots that need review.
PaddleDetection Security
Best in #Computer Vision
Average in #Computer Vision
PaddleDetection Security
Best in #Computer Vision
Average in #Computer Vision

license License

  • PaddleDetection is licensed under the Apache-2.0 License. This license is Permissive.
  • Permissive licenses have the least restrictions, and you can use them in most projects.
PaddleDetection License
Best in #Computer Vision
Average in #Computer Vision
PaddleDetection License
Best in #Computer Vision
Average in #Computer Vision

buildReuse

  • PaddleDetection releases are available to install and integrate.
  • Deployable package is available in PyPI.
  • Build file is available. You can build the component from source.
  • PaddleDetection saves you 7826 person hours of effort in developing the same functionality from scratch.
  • It has 16124 lines of code, 724 functions and 119 files.
  • It has medium code complexity. Code complexity directly impacts maintainability of the code.
PaddleDetection Reuse
Best in #Computer Vision
Average in #Computer Vision
PaddleDetection Reuse
Best in #Computer Vision
Average in #Computer Vision
Top functions reviewed by kandi - BETA

kandi has reviewed PaddleDetection and discovered the below as its top functions. This is intended to give you an instant insight into PaddleDetection implemented functionality, and help decide if they suit your requirements.

  • Get information about categories .
  • Return a dict mapping ID -19 ID -19 ID to ID19
  • Compute metrics for Hungarian Method
  • Evaluate a sequence SDE model .
  • Provide category information .
  • Get the coco17 category category .
  • Multiclass nms3 layer .
  • Wrapper function for box_coder .
  • Generate proposals for a given image .
  • Train the model .

PaddleDetection Key Features

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

Community Discussions

Trending Discussions on Computer Vision
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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 PaddleDetection

You can install using 'pip install PaddleDetection' or download it from GitHub, PyPI.
You can use PaddleDetection like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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 .

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