kandi X-RAY | VAD_DNN Summary
kandi X-RAY | VAD_DNN Summary
VAD_DNN is a Python library. VAD_DNN has no bugs, it has no vulnerabilities and it has low support. However VAD_DNN build file is not available. You can download it from GitHub.
VAD_DNN
VAD_DNN
Support
Quality
Security
License
Reuse
Support
VAD_DNN has a low active ecosystem.
It has 6 star(s) with 2 fork(s). There are 2 watchers for this library.
It had no major release in the last 6 months.
There are 1 open issues and 0 have been closed. On average issues are closed in 363 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of VAD_DNN is current.
Quality
VAD_DNN has no bugs reported.
Security
VAD_DNN has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
VAD_DNN 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
VAD_DNN releases are not available. You will need to build from source code and install.
VAD_DNN has no build file. You will be need to create the build yourself to build the component from source.
Top functions reviewed by kandi - BETA
kandi has reviewed VAD_DNN and discovered the below as its top functions. This is intended to give you an instant insight into VAD_DNN implemented functionality, and help decide if they suit your requirements.
- Select next batch of files
- Read the input file
- Read the output file
- Normalize x
- Initialize inference
- Batch norm of x
- Apply affine transformation
- Convolutional LSTM layer
- Create a new bias variable
- 2d conv2d convolution
- Get VGG model data
- Download a file and extract it
- Saves an image
- Unprocess an image
- Bottleneck convolution bottleneck
- Creates a weight variable
- Evaluate the model
- Convert a dense tensor
- Compute the prediction for a given logits
- Converts a dense tensor to one - hot representation
Get all kandi verified functions for this library.
VAD_DNN Key Features
No Key Features are available at this moment for VAD_DNN.
VAD_DNN Examples and Code Snippets
No Code Snippets are available at this moment for VAD_DNN.
Community Discussions
No Community Discussions are available at this moment for VAD_DNN.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install VAD_DNN
You can download it from GitHub.
You can use VAD_DNN 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.
You can use VAD_DNN 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 .
Find more information at:
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
