What is ImageNet used for?
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What is ImageNet used for?
ImageNet is a large dataset of annotated photographs intended for computer vision research. The goal of developing the dataset was to provide a resource to promote the research and development of improved methods for computer vision.
How many categories are there in ImageNet?
ImageNet contains more than 20,000 categories with a typical category, such as “balloon” or “strawberry”, consisting of several hundred images.
Why was ImageNet so important?
It proved that training on ImageNet gave models a big boost, requiring only fine-tuning for other recognition tasks. Convolutional neural networks trained in this manner find patterns at the pixel level, making thousands of computations through ascending fields of abstraction – a concept called transfer learning.
What are the classes of ImageNet?
IMAGENET 1000 Class List
| Class ID | Class Name |
|---|---|
| 0 | tench, Tinca tinca |
| 1 | goldfish, Carassius auratus |
| 2 | great white shark, white shark, man-eater, man-eating shark, Carcharodon caharias’, |
| 3 | tiger shark, Galeocerdo cuvieri |
What does ImageNet dataset contain?
The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy. Since 2010 the dataset is used in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a benchmark in image classification and object detection.
Is ImageNet solved?
Today, many consider ImageNet solved—the error rate is incredibly low at around 2\%. But that’s for classification, or identifying which object is in an image.
What is the resolution of ImageNet?
The average resolution of an ImageNet image is 469×387. They are usually cropped to 256×256 or 224×224 in your image preprocessing step.
Does ImageNet have human?
In ImageNet, we aim to provide on average 1000 images to illustrate each synset. Images of each concept are quality-controlled and human-annotated. In its completion, we hope ImageNet will offer tens of millions of cleanly labeled and sorted images for most of the concepts in the WordNet hierarchy.
What is ImageNet-1K dataset?
Download PDF ImageNet-1K serves as the primary dataset for pretraining deep learning models for computer vision tasks. ImageNet-21K dataset, which is bigger and more diverse, is used less frequently for pretraining, mainly due to its complexity, low accessibility, and underestimation of its added value.
Who created ImageNet dataset?
ImageNet is organised through 21,000 categories that are still being used today to train computational models. In September 2019, ImageNet creator Fei-Fei Li gave a talk at The Photographers’ Gallery talking through the events and key people that led to the datasets creation.