CMATERdb | Easy to use CMATERdb datasets converted in NumPy format | Machine Learning library

by prabhuomkar Python Version: Current License: Apache-2.0

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kandi X-RAY | CMATERdb Summary

CMATERdb is a Python library typically used in Telecommunications, Media, Advertising, Marketing, Artificial Intelligence, Machine Learning, Deep Learning applications. CMATERdb has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However CMATERdb build file is not available. You can download it from GitHub.

CMATERdb is the pattern recognition database repository created at the ‘Center for Microprocessor Applications for Training Education and Research’ (CMATER) research laboratory, Jadavpur University, Kolkata 700032, INDIA. This database is free for all non-commercial uses. Please acknowledge CMATER explicitly, whenever you use this database for academic and research purposes. For using some databases, one must also cite relevant research publications, mentioned in this website. Official Dataset Repository: Link Shifted Repository as per Google Code Archive (Not Live): Link.

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CMATERdb has a low active ecosystem.

It has 16 star(s) with 1 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

CMATERdb has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of CMATERdb is current.

Quality

CMATERdb has no bugs reported.

Security

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

License

CMATERdb is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

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

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

Save the given numeral_type .
Load numeral images .

Get all kandi verified functions for this library.

CMATERdb Key Features

No Key Features are available at this moment for CMATERdb.

CMATERdb Examples and Code Snippets

No Code Snippets are available at this moment for CMATERdb.

Community Discussions

Trending Discussions on CMATERdb

Error in prediction in digit recognition using cnn

How do I format a dataset for training in Python?

QUESTION

Error in prediction in digit recognition using cnn

Asked 2020-May-29 at 20:09

I want to predict the digit is 5 or not from 0 to 9.I have used cmaterdb dataset.

For this task I have changed all the digit label 0 except 5 in the training and test dataset

...

ANSWER

Answered 2020-May-29 at 20:09

I can guess, you have an accuracy of about 90%, but your model almost always predicts 0 ( not 5), right?

If it is the case, the reason can be the imbalanced classes. Your original dataset, I guess is balanced, like we have almost N 0s, almost N 1s, ... and almost N 9s. What you did, you kept the almost N 5s, and labeled it to 1, and turn the rest of almost 9*N examples to label 0. It means now you have 10% of data labeled 1( which are 5s) and 90% of data labeled 0. This is an imbalance case, and it is very normal you get a good accuracy of around 90%, but a poor prediction for the minority class. For imbalanced cases, accuracy is not a good metric or maybe it is not enough. Try to trace Precision,recall, and F1 as well.

my suggestion, sample from the non 5 classes ( 1/10 from each ) and keep all the 5s. You should get better predictions.

Source https://stackoverflow.com/questions/62090571

QUESTION

How do I format a dataset for training in Python?

Asked 2017-Jul-07 at 01:47

How do I format a dataset for training in Python?

I have 3000 grayscale BMP images of some handwritten digits (just like MNIST). Now I want to train my model with this dataset (I am using the Keras library) and I am using a convolution neural network for training.

I am using this code to convert one of the images into array

...

ANSWER

Answered 2017-Jul-06 at 18:03

You can use any library that loads image files into arrays, such as Pillow.

Read Pillow's documentation to learn how to load an image file into an array.

Then, you should usually scale the array into values between 0 and 1. Usually, you just divide the image array by 255 (because they are RGB values between 0 and 255).

Be sure to end up with an array shaped like this: (3000, width, heigth, channels), where channels is usually 3 (Red, green, blue).

Source https://stackoverflow.com/questions/44953187

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

Vulnerabilities

No vulnerabilities reported

Install CMATERdb

You can download it from GitHub.
You can use CMATERdb 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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