10 Must-know Computer Vision Dataset1. The Modified National Institute of Standards and Technology database of handwritten digits (MNIST database, in short).
Nov 4, 2022In this tutorial, we talked about three popular datasets in computer vision, namely ImageNet, MS COCO, and Google Open Images. Then, we also
Datasets: Importance and Problems
Computer vision is considered one of the main fields where deep learning achieved excellent results and revolutionalized the way scientists develop algorithms.
However, deep learning models need more and more data in order to work properly and achieve these results.
As a result, the development of large-scale open-source datasets has become a neces.
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Google Open Images
The third dataset that we will discuss in this article is Google Open Images which was created by Google.
It consists of around 9 million images that are annotated with more than 6000 classes.
Google Open Images gained a lot of popularity due to its large variety of classes, contrary to ImageNet, which contains 1000 classes.
Another characteristic .
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How many images are there in a dataset?
There are 20.580 images and 120 categories.
This dataset contains 16,185 images and 196 classes of cars.
The data is split into 8,144 training images and 8,041 testing images, where each class has been split roughly in a 50-50 split.
You have to download the images and their class labels and bounding boxes separately.
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Imagenet
ImageNet is one of the most important datasets in computer vision since it is the first open-source large-scale dataset that was widely used for deep learning algorithms.It was developed by a group of researchers at Stanford, Princeton, and UNC Chapel Hill.
The initial idea of ImageNet was to create a WordNet (that is a large lexical database of En.
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Kaggle Datasets
The three above datasets are very popular and cover a variety of tasks.
However, the number of different visual tasks that exist is much greater.
So, where can someone search for a dataset that fits his specific needs.
Kaggle dataset is a place where we can search and explore over 100 thousand datasets.
Also, there is a specific computer vision sec.
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MS Coco
Another very popular dataset for computer vision is MS COCO which stands for Common Objects in Context and was developed by Microsoft.It is a large-scale dataset that can be used for object detection, segmentation, and captioning.
It is considered the main benchmark for evaluating object detection algorithms.
Also, its large popularity lies in the .
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Overview
In this article, we’ll present some popular datasets in the field of computer vision.
First, we’ll discuss the importance of having large-scale open-source datasets in computer vision.
Then, we’ll talk about three popular datasets that are ImageNet, MS COCO, and Google Open images.
Finally, we’ll briefly mention the Kaggle datasets.
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What datasets are used in deep learning?
Then, we’ll talk about three popular datasets that are ImageNet, MS COCO, and Google Open images.
Finally, we’ll briefly mention the Kaggle datasets. 2.
Datasets:
Importance and Problems Computer vision is considered one of the main fields where deep learning achieved excellent results and revolutionalized the way scientists develop algorithms. ,
What is a good dataset for computer vision?
MS COCO Another very popular dataset for computer vision is MS COCO which stands for Common Objects in Context and was developed by Microsoft.
It is a large-scale dataset that can be used for object detection, segmentation, and captioning.
It is considered the main benchmark for evaluating object detection algorithms.
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Why do we need large-scale open-source datasets in computer vision?
As a result, the development of large-scale open-source datasets has become a necessity in computer vision in recent years.
Hopefully, more and more computer vision datasets are created every day for a variety of visual tasks like object detection, segmentation, classification, captioning, pose estimation, etc.
