tensorflow-image-classifier | image classifier , retrained for specific classes | Computer Vision library

by burliEnterprises Python Version: Current License: No License

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kandi X-RAY | tensorflow-image-classifier Summary

tensorflow-image-classifier is a Python library typically used in Artificial Intelligence, Computer Vision, Tensorflow applications. tensorflow-image-classifier has no bugs, it has no vulnerabilities and it has low support. However tensorflow-image-classifier build file is not available. You can download it from GitHub.

image classifier, retrained for specific classes

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tensorflow-image-classifier has a low active ecosystem.

It has 61 star(s) with 47 fork(s). There are 9 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 1 have been closed. On average issues are closed in 380 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of tensorflow-image-classifier is current.

Quality

tensorflow-image-classifier has no bugs reported.

Security

tensorflow-image-classifier has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

tensorflow-image-classifier 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.

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tensorflow-image-classifier releases are not available. You will need to build from source code and install.

tensorflow-image-classifier has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are available. Examples and code snippets are not available.

Top functions reviewed by kandi - BETA

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

Retrieves a set of bottleneck_truths
Ensure directory exists
Get or create a bottleneck
Get the full path to the image
Create bottleneck file
Run bottleneck on image
Returns the path to the bottleneck
Adds the final training tensor
Create summaries for variables
Download and extract the model
Create the bottleneck graph
Compute the evaluation step
Adds input_distortions
Cache bottleneck files
Generate bottleneck_truths for images
Create a list of images in image_dir
Determines if the image should distort

Get all kandi verified functions for this library.

tensorflow-image-classifier Key Features

No Key Features are available at this moment for tensorflow-image-classifier.

tensorflow-image-classifier Examples and Code Snippets

No Code Snippets are available at this moment for tensorflow-image-classifier.

Community Discussions

Trending Discussions on tensorflow-image-classifier

How to feed an image ROI into session.run() of Tensorflow?

QUESTION

How to feed an image ROI into session.run() of Tensorflow?

Asked 2019-Mar-12 at 12:19

I am trying to feed my image roi into the Tensorflow classifier I took from here. The idea is to first run a simple filter, get rectangle candidates, and then check (using the network) whether each rectangle(roi) is actually what I am looking for.

...

ANSWER

Answered 2019-Mar-08 at 15:12

feed_dict expect a dictionary with tensors as keys, to populate the placeholders with the specified valued. It's not in your code snippet how does the screw_id is initiated, but I bet it's not a tensor of any kind, hence, your error.

Source https://stackoverflow.com/questions/55065471

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

Vulnerabilities

No vulnerabilities reported

Install tensorflow-image-classifier

Make sure you have Python (https://www.python.org/) installed, then install Tensorflow (https://www.tensorflow.org/install/) on your system, and clone this repo.

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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