fdscs | Copyright 2018 , Kyle Yee and Ayan Chakrabarti

by ayanc Python Version: Current License: No License

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

kandi X-RAY | fdscs Summary

fdscs is a Python library. fdscs has no bugs, it has no vulnerabilities and it has low support. However fdscs build file is not available. You can download it from GitHub.

Copyright (C) 2018, Kyle Yee and Ayan Chakrabarti.

Support

Quality

Security

License

Reuse

Support

fdscs has a low active ecosystem.

It has 23 star(s) with 6 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 8 have been closed. On average issues are closed in 1 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of fdscs is current.

Quality

fdscs has 0 bugs and 0 code smells.

Security

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

fdscs code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

fdscs 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

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

fdscs 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.

fdscs saves you 273 person hours of effort in developing the same functionality from scratch.

It has 662 lines of code, 29 functions and 12 files.

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

Top functions reviewed by kandi - BETA

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

Build the graph
Convolution layer
Predict using cv
Unet
Construct the graph
Low resolution function
Pretty print the data
Pretty print a string
Removes files from the list
Load the wcard file
Load Adam
Load weights from file fn
Save the weights to fn
Saves Adam to fn
Compute the loss loss function
Switch to test
Pretty print a string
Loads the model

Get all kandi verified functions for this library.

fdscs Key Features

No Key Features are available at this moment for fdscs.

fdscs Examples and Code Snippets

No Code Snippets are available at this moment for fdscs.

Community Discussions

No Community Discussions are available at this moment for fdscs.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install fdscs

You will need a machine with a GPU and a modern version of Tensorflow with GPU support installed. You will need to compile our custom Tensorflow ops in the slib/ directory. You can try running the make.sh file provided, which might work for you out of the box. If it doesn't, please look at the instructions at https://www.tensorflow.org/guide/extend/op. Also note that the python code assumes that your library will be compiled as slib.so, which is the case on Linux systems. On other systems, the loadable library may have a different extension. If that is the case, please modify the sopath definition at the top of slib/__init__.py accordingly.

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 .

Find more information at: