DVBPR | Personalized Fashion Recommendation and Generation | Recommender System library

by kang205 Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | DVBPR Summary

DVBPR is a Python library typically used in Artificial Intelligence, Recommender System, Deep Learning, Generative adversarial networks applications. DVBPR has no bugs, it has no vulnerabilities and it has low support. However DVBPR build file is not available. You can download it from GitHub.

Personalized Fashion Recommendation and Generation

Support

Quality

Security

License

Reuse

Support

DVBPR has a low active ecosystem.

It has 151 star(s) with 45 fork(s). There are 8 watchers for this library.

It had no major release in the last 6 months.

There are 3 open issues and 5 have been closed. On average issues are closed in 143 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of DVBPR is current.

Quality

DVBPR has 0 bugs and 83 code smells.

Security

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

DVBPR code analysis shows 0 unresolved vulnerabilities.

There are 3 security hotspots that need review.

License

DVBPR does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

DVBPR releases are not available. You will need to build from source code and install.

DVBPR has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

DVBPR saves you 698 person hours of effort in developing the same functionality from scratch.

It has 1614 lines of code, 88 functions and 9 files.

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

Top functions reviewed by kandi - BETA

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

Get an image
Read image file
Center of crop
Transform an image
Generate example images
Merge two images
Make a gif from a list of images
Save images
Build the model
Generate the generator
Calculate the sampler
Computes discriminator
Train the model
Loads checkpoint from checkpoint_dir
Saves the model to checkpoint_dir
Loads checkpoint from given directory
Concatenate x and y
Gets the discriminator
Get the generator function
Show all trainable variables
Merge images

Get all kandi verified functions for this library.

DVBPR Key Features

No Key Features are available at this moment for DVBPR.

DVBPR Examples and Code Snippets

No Code Snippets are available at this moment for DVBPR.

Community Discussions

Trending Discussions on DVBPR

undestanding feed_dict in sess.run

QUESTION

undestanding feed_dict in sess.run

Asked 2018-Jul-10 at 14:23

I'm new to tensorflow. I have some code I'm trying to understand. Is there a way to get a list of all possible inputs for the "feed_dict" in sess.run? Is the structure of feed_dict always the same or does it depend on the session?

code:

...

ANSWER

Answered 2018-Jul-09 at 21:43

feed_dict is just a dictionary where the key is the variable containing tensor information, and the value is the data to be fed to the network. Usually you can populate the session graph and find the placeholders, as they can only be inputs to a graph. You can populate the graph by:

for op in sess.graph.get_operations(): print(op.name, op.type)

As each session can depend on a different graph, feed_dict can have different inputs. If you are defining your own graph, it is good practice to keep the input placeholders as different variables.

Also your sess.run command is extracting inputs from the session.

Source https://stackoverflow.com/questions/51253483

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

Vulnerabilities

No vulnerabilities reported

Install DVBPR

You can download it from GitHub.
You can use DVBPR 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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