TensorflowFreezeModel

by vcvycy Python Version: Current License: No License

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

kandi X-RAY | TensorflowFreezeModel Summary

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

TensorflowFreezeModel

Support

Quality

Security

License

Reuse

Support

TensorflowFreezeModel has a low active ecosystem.

It has 7 star(s) with 3 fork(s). There are 1 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 486 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of TensorflowFreezeModel is current.

Quality

TensorflowFreezeModel has no bugs reported.

Security

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

License

TensorflowFreezeModel 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

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

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

Bulk detect face detection
Generate bounding boxes for a heatmap
Get bounding box
Returns nms from boxes
Setup the network
Max pooling op
Convolution layer
Define a forward layer
Decorator to define a layer
Feed layers
Return a unique name for a given prefix
Load network layers and layers
Create TMNN layer
Create TMNN
Loads data from file
Setup the module
Parse command line arguments
Freeze the model
Draw a rectangle
Show an image
Detect the face of a given image

Get all kandi verified functions for this library.

TensorflowFreezeModel Key Features

No Key Features are available at this moment for TensorflowFreezeModel.

TensorflowFreezeModel Examples and Code Snippets

No Code Snippets are available at this moment for TensorflowFreezeModel.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install TensorflowFreezeModel

You can download it from GitHub.
You can use TensorflowFreezeModel 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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