DISN | Deep Implicit Surface Network for High-quality Single | Image Editing library

by laughtervv Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | DISN Summary

DISN is a Python library typically used in Media, Image Editing applications. DISN has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However DISN build file is not available. You can download it from GitHub.

Please report bugs here and we will publish the bug fix and the latest updates.

Support

Quality

Security

License

Reuse

Support

DISN has a low active ecosystem.

It has 183 star(s) with 31 fork(s). There are 16 watchers for this library.

It had no major release in the last 6 months.

There are 9 open issues and 6 have been closed. On average issues are closed in 2 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of DISN is current.

Quality

DISN has 0 bugs and 0 code smells.

Security

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

DISN code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

DISN 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

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

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

Installation instructions, examples and code snippets are available.

DISN saves you 2601 person hours of effort in developing the same functionality from scratch.

It has 5649 lines of code, 258 functions and 31 files.

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

Top functions reviewed by kandi - BETA

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

Train the model
Get image coordinates
Get a trained model
Calculate loss from end points
Get the batch for a given index
Get a single image
Get an item from the list
Return the path to the image directory for the given cat
Builds a tf sdf feature
Convert images to hdf5 files
Get sdf_features
Wrapper for sdf_partial_fc
Get SDF partial binary
Verify the nn
Test the image for the given image
Create an SDF object
Get image mat matrix
Transpose input tensor
VGG embedding
VGG network
1D convolutional convolution layer
Create TensorFlow session
Create sdf file
Generate hdf5 file for an object
Create the network
Batch normalization template

Get all kandi verified functions for this library.

DISN Key Features

No Key Features are available at this moment for DISN.

DISN Examples and Code Snippets

No Code Snippets are available at this moment for DISN.

Community Discussions

Trending Discussions on DISN

Need help in task of panda dataframe (juypternotebook) HELP NEW problem "Only the most traded stock of the firm"

how can i filter a dataframe by some criteria and then save .csv?

QUESTION

Need help in task of panda dataframe (juypternotebook) HELP NEW problem "Only the most traded stock of the firm"

Asked 2020-May-27 at 09:56

Hi guys i started at jupyter notebook few days ago.

I need help, i have a dataframe by panda. something like this

...

ANSWER

Answered 2020-May-27 at 09:56

You can know the frequency of stocks which traded greater than 500000 for 80% of days by,

Source https://stackoverflow.com/questions/62014845

QUESTION

how can i filter a dataframe by some criteria and then save .csv?

Asked 2020-May-27 at 01:22

Hi guys i started at jupyter notebook few days ago.

I need help, i have a dataframe by panda. something like this

...

ANSWER

Answered 2020-May-27 at 01:22

We can use nunique

Source https://stackoverflow.com/questions/62033614

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

Vulnerabilities

No vulnerabilities reported

Install DISN

download the dataset following the instruction of https://www.shapenet.org/account/ (about 30GB).
download 2d image following 3DR2N2[https://github.com/chrischoy/3D-R2N2], please cite their paper if you use this image tar file:
run h5 file generation (about 26 GB) :

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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