image-augment | Image augmentation library for machine learning | Machine Learning library

by piercus JavaScript Version: 1.1.1 License: No License

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | image-augment Summary

image-augment is a JavaScript library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. image-augment has no bugs, it has no vulnerabilities and it has low support. You can install using 'npm i image-augment' or download it from GitHub, npm.

Image augmentation library for machine learning in javascript

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image-augment has a low active ecosystem.

It has 14 star(s) with 1 fork(s). There are 1 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of image-augment is 1.1.1

Quality

image-augment has 0 bugs and 0 code smells.

Security

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

image-augment code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

image-augment 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

image-augment releases are available to install and integrate.

Deployable package is available in npm.

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

image-augment saves you 2165 person hours of effort in developing the same functionality from scratch.

It has 4743 lines of code, 0 functions and 105 files.

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

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image-augment Key Features

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

image-augment Examples and Code Snippets

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

Community Discussions

Trending Discussions on image-augment

Where to get models for TransferLearning based on topics

Keras ImageDataGenerator: problem with data and label shape

How to use ImageDataGenerator with my own set of images for image augmentation

QUESTION

Where to get models for TransferLearning based on topics

Asked 2020-Jun-02 at 10:46

Suppose you're searching for a pretrained model for e.g. human gender recognition, or age estimation (Transfer Learning). So, you'd want a net that is trained on, ideally, human faces and not on stuff like the ImageNet dataset.

I know that there are two big starting points for the search:

Keras applications
TensorHub

Now, the best I've found is to use the search tool of the TensorHub website, like here.

That gives me some models trained on the CelebA-HQ dataset, which is something I was searching for.

But, it didn't give any results for e.g. the keywords "sport", "food" or "gun".

So, what is a good way to find pretrained models for a desired "topic"?

...

ANSWER

Answered 2020-Jun-02 at 10:46

It's hard to find a model for each topic at a single place.

The general strategy could be searching in GitHub with the relevant tags ["tensorflow", "sport"].

You can generally find many models on model-zoo websites: https://modelzoo.co/

This is also useful: https://github.com/tensorflow/models

If you need code (probably with pre-trained weights): paperswithcode.com is a good place to search.

Source https://stackoverflow.com/questions/62149846

QUESTION

Keras ImageDataGenerator: problem with data and label shape

Asked 2019-Jan-02 at 11:45

I wanted to generate more images using Keras as you can see in here, using this code (almost the same as source>Random Rotations):

...

ANSWER

Answered 2019-Jan-02 at 11:40

You need to change the shape of your labels

Source https://stackoverflow.com/questions/54005424

QUESTION

How to use ImageDataGenerator with my own set of images for image augmentation

Asked 2017-Jul-25 at 10:07

From here it shows how to do image augmentation with an existing image set, cifar10.

How can I create an ImageDataGenerator with my own set of images?

...

ANSWER

Answered 2017-Jul-25 at 07:48

You could change your train_generator to flow_from_directory() and simply point to an image directory of your choosing:

Source https://stackoverflow.com/questions/45296431

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

Vulnerabilities

No vulnerabilities reported

Install image-augment

You can install using 'npm i image-augment' or download it from GitHub, npm.

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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