DEV Community

Super Kai (Kazuya Ito)
Super Kai (Kazuya Ito)

Posted on • Edited on

Datasets for Computer Vision (3)

Buy Me a Coffee

*Memos:

(1) Oxford-IIIT Pet(2012):

  • has the 7,349 cat and dog images(3,680 for train and validation, 3,669 for test) each connected to the label from 37 classes: *Memos:
    • Each class has roughly 200 images.
    • 3,680 for train or train and validation and 3,669 for test.
  • is used for Image Classification and Fine-Grained Image Classification.
  • is OxfordIIITPet() in PyTorch. *My post explains OxfordIIITPet().

Image description

(2) Oxford 102 Flower(2008):

  • has 8,189 flower images(1,020 for train, 1,020 for validation and 6,149 for test) with the 102 categories(classes). *Each class has 40 to 258 images.
  • is used for Fine-Grained Flower Classification.
  • is Flowers102() in PyTorch. *My post explains Flowers102().

Image description

(3) Stanford Cars(2013):

  • has 16185 car images(8,144 for train and 8,041 for test) with 196 classes.
  • is used for Fine-Grained Flower Classification.
  • is StanfordCars() in PyTorch. *My post explains StanfordCars().

Image description

(4) Places365(2017):

  • has scene images with the 365 scene categories(classes) out of the 434 scene categories(classes) in the Places Database and there are Places365-Standard, Places365-Challenge and Places-Extra69 as you can see here: *Memos:
    • Places365-Standard has 2,168,460 images(1,803,460 for train, 36,500 for validation and 328,500 for test) with the 365 categories(classes) out of the 434 categories(classes) in the Places Database. *There are 50 images per category(class) in the validation set and 900 images per category(class) in the test set.
    • Places365-Challenge has 8,391,628 images(8,026,628 for train, 36,500 for validation and 328,500 for test), adding 6,223,168 extra images to the train set of Places365-Standard.
    • Places-Extra69 has 105,321 images(98,721 for train and 6,600 for test) with the extra 69 categories(classes) out of the 434 categories(classes) in the Places Database. *Currently, it cannot be downloaded.
  • is used for Scene Classification.
  • is Places365() in PyTorch. *My post explains Places365().

Image description

(5) Flickr8k(2013):

  • has the 8,091 images obtained from flickr with the five different captions for each image.
  • is used for Image Captioning.
  • is Flickr8k() in PyTorch but it doesn't explain how to set up the dataset to it so I don't know how to load the dataset with it.

Image description

(6) Flickr30k(2015):

  • has 31,784 images obtained from flickr with the five different captions for each image.
  • is used for Image Captioning.
  • is Flickr8k() in PyTorch but it doesn't explain how to set up the dataset to it so I don't know how to load the dataset with it.

Image description

Heroku

Simplify your DevOps and maximize your time.

Since 2007, Heroku has been the go-to platform for developers as it monitors uptime, performance, and infrastructure concerns, allowing you to focus on writing code.

Learn More

Top comments (0)

Heroku

This site is powered by Heroku

Heroku was created by developers, for developers. Get started today and find out why Heroku has been the platform of choice for brands like DEV for over a decade.

Sign Up

👋 Kindness is contagious

Discover a treasure trove of wisdom within this insightful piece, highly respected in the nurturing DEV Community enviroment. Developers, whether novice or expert, are encouraged to participate and add to our shared knowledge basin.

A simple "thank you" can illuminate someone's day. Express your appreciation in the comments section!

On DEV, sharing ideas smoothens our journey and strengthens our community ties. Learn something useful? Offering a quick thanks to the author is deeply appreciated.

Okay