DeeplabV3_Apolloscape_and_CityScape | This repo is a copy of the network DeepLabv3 from google

by JinyongJeong Python Version: Current License: No License

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

kandi X-RAY | DeeplabV3_Apolloscape_and_CityScape Summary

DeeplabV3_Apolloscape_and_CityScape is a Python library typically used in Telecommunications, Media, Media, Entertainment applications. DeeplabV3_Apolloscape_and_CityScape has no bugs, it has no vulnerabilities and it has low support. However DeeplabV3_Apolloscape_and_CityScape build file is not available. You can download it from GitHub.

This repo is a copy of the network DeepLabv3+ from google. I simply extracted the necessary code in order to run without having to download lots of unnecessary code.

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Security

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Support

DeeplabV3_Apolloscape_and_CityScape has a low active ecosystem.

It has 8 star(s) with 1 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

DeeplabV3_Apolloscape_and_CityScape has no issues reported. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of DeeplabV3_Apolloscape_and_CityScape is current.

Quality

DeeplabV3_Apolloscape_and_CityScape has no bugs reported.

Security

DeeplabV3_Apolloscape_and_CityScape has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

DeeplabV3_Apolloscape_and_CityScape 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

DeeplabV3_Apolloscape_and_CityScape releases are not available. You will need to build from source code and install.

DeeplabV3_Apolloscape_and_CityScape 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.

Top functions reviewed by kandi - BETA

kandi has reviewed DeeplabV3_Apolloscape_and_CityScape and discovered the below as its top functions. This is intended to give you an instant insight into DeeplabV3_Apolloscape_and_CityScape implemented functionality, and help decide if they suit your requirements.

Expand convolution layer
Splits input_tensor into chunks
Pad inputs with fixed padding
Returns a list of num_ways divided by num_ways
Parse command line arguments
Sum the evaluation results
Get image data
Preprocess the image
Deploy a model
Slimoser for variables
Path to the optimizer device
Xception module
Resize image to given range
Load data from filelist
Summarize the evaluation
Extract features from images
Random crop
Evaluate the prediction
Predict labels for multiple images
Xception block
Compute stereo rectify parameters
Creates a separable convolutional convolutional convolution
Convert dataset to TFRecord
Process a single image
Build a deeplab
Compute the similarity of a pose

Get all kandi verified functions for this library.

DeeplabV3_Apolloscape_and_CityScape Key Features

No Key Features are available at this moment for DeeplabV3_Apolloscape_and_CityScape.

DeeplabV3_Apolloscape_and_CityScape Examples and Code Snippets

No Code Snippets are available at this moment for DeeplabV3_Apolloscape_and_CityScape.

Community Discussions

No Community Discussions are available at this moment for DeeplabV3_Apolloscape_and_CityScape.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install DeeplabV3_Apolloscape_and_CityScape

You can download it from GitHub.
You can use DeeplabV3_Apolloscape_and_CityScape 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.