selective_search | Python implementation of selective search | Search Engine library

by ChenjieXu Python Version: v1.1.0 License: MIT

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | selective_search Summary

selective_search is a Python library typically used in Database, Search Engine applications. selective_search has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install selective_search' or download it from GitHub, PyPI.

Python implementation of selective search

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selective_search has a low active ecosystem.

It has 43 star(s) with 15 fork(s). There are 1 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 3 have been closed. On average issues are closed in 16 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of selective_search is v1.1.0

Quality

selective_search has no bugs reported.

Security

selective_search has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

selective_search 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

selective_search releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Performs selective search
Calculate the similarity between two colors
Calculate the pairwise similarity pair
Calculate the simulation
Performs selective search using selective search
Load a strategy

Get all kandi verified functions for this library.

selective_search Key Features

No Key Features are available at this moment for selective_search.

selective_search Examples and Code Snippets

No Code Snippets are available at this moment for selective_search.

Community Discussions

Trending Discussions on selective_search

Special function on feature maps of convolutional layer

Extracting image from bounding box - selective search

What is the correct way to call this OpenCV function from Python?

QUESTION

Special function on feature maps of convolutional layer

Asked 2019-Jan-25 at 17:02

In Short:

How do I pass feature maps from convolutional layer defined in Keras to a special function (region proposer) which is then passed to other Keras layers (e.g Softmax classifier)?

Long:

I'm trying to implement something like Fast R-CNN (not Faster R-CNN) in Keras. The reason for this is because I'm trying to implement a custom architecture as seen in the figure below:

Here's the code for the figure above (excluding candidates input):

...

ANSWER

Answered 2019-Jan-25 at 17:02

To my best understanding, selective-search take an input and return n no of patches of different (H,W). So in your case, feature-map is of dims (164,164,96), you can assume (164,164) as the input for selective-search and it will give you n number of patch, for exp as (H1,W1), (H2,W2),.... So you can now append all the channel as it is, to that patch, so it becomes as of dims (H1,W1,96),(H2,W2,96),.....

Note: But there is downside of doing this too. Selective-Search algorithm use the strategy in which it breaks the image in grids and then re-join those patch as per the heatmap of the object. You would not be able to do that on feature-map. But you can use random search method on that and it can be useful.

Source https://stackoverflow.com/questions/54366838

QUESTION

Extracting image from bounding box - selective search

Asked 2018-Feb-14 at 20:12

I am learning how to properly use a selective search algorithm to create bounding boxes around an image, extract the smaller images within the bounding box and then run further analysis on the smaller images.

I am able to obtain the bounding boxes through the following, but how do I save/extract/export the images within each bounding box?

...

ANSWER

Answered 2017-Aug-15 at 10:35

You know how to get each rectangle using the lines

Source https://stackoverflow.com/questions/45666888

QUESTION

What is the correct way to call this OpenCV function from Python?

Asked 2017-Aug-06 at 18:56

I would like to use the selective search algorithm to segment images into possible object locations. I found that the library I already use for computer vision, OpenCV, implements this functionality as shown in the documentation here. However, I'm using Python and not C++, so I looked through OpenCV's github repositories until I found the example that I reproduced below.

...

ANSWER

Answered 2017-Aug-06 at 18:56

Apparently, the version of OpenCV 3.2.0 that I compiled for Python was missing this fix locally. I went ahead and recompiled my python bindings using the latest stable release of OpenCV 3.3.0 and the latest changes to the OpenCV contrib repository and the sample script worked as expected after that.

Source https://stackoverflow.com/questions/45526539

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

Vulnerabilities

No vulnerabilities reported

Install selective_search

Installing from PyPI is recommended :.
For detailed examples, refer this part of the repository.

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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