benchmark visual recognition datasets for deep learning Caltech101, Caltech256, CaltechBirds, CIFAR-10, CIFAR-100 and stl10. Guide to Visual Recognition Datasets for Deep Learning with Python Code
Some visual recognition datasets have set benchmarks for supervised learning (Caltech101, Caltech256, CaltechBirds, CIFAR-10 andCIFAR-100) and unsupervised or self-taught learning algorithms(STL10) using deep learning across different object categories for various researches and developments. Under visual recognition mainly comes image classification, image segmentation and localization, object detection and various other use case problems. Many of these datasets have APIs present across some deep learning frameworks. I’ll be mentioning some of them in this article which can be directly imported and used to train models.
Cifar(Canadian Institute of Advanced Research) is a subset of 80 million tiny images dataset which has been collected by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton.
Dataset can be found on the official website of the Computer Science department of the University of Toronto.
California Institute of Technology( Caltech) – a private research institute. Caltech vision databases are present under the Computational Vision section.
STL10 dataset was inspired byCIFAR-10, the dataset is present in the official website of the computer science department, Stanford University.
Taking our visual recognition datasets discussions further, today we will be talking about these datasets features along with some python code snippets on how to use them.
In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.
Today you're going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates. We gonna use Python OS remove( ) method to remove the duplicates on our drive. Well, that's simple you just call remove ( ) with a parameter of the name of the file you wanna remove done.
In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.
Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc.. You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like __init__, __call__, __str__ etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).
The OS module is a python module that provides the interface for interacting with the underlying operating system that Python is running.