Datasets

Cooking States

Cooking State Recognition Challenge Dataset
How were the data collected ?
Dataset images were collected from Google, using Vatic annotation tool and labelbox tool.
Class of states : whole, peeled, floured, sliced, diced, grated, julienne, juice, creamy, mixed, and other

How many dataset version we have so far ?
There are two versions of the datasets. Dataset and

Dataset version 2.0
Total number of images: 9309
Number of images with object labels: 7629
Number of images with no clear object label: 1680
Number of object types: 18
Number of states: 11
Download:

A collage of various raw and prepared food ingredients including chicken, eggs, vegetables, cheese, fruits, cooked dishes, and baking elements.
A bar chart displays the object counts in a dataset, with various food items listed on the x-axis, and their corresponding counts represented by vertical bars, highlighting items like bread and chicken as having the highest quantities. The chart features labeled axes, clearly illustrating the data distribution of different objects.
A bar chart displays the counts of different states in a dataset, with categories such as "floured," "sliced," and "juiced," showcasing varying frequencies represented by red bars against a gray scale. The y-axis indicates count values, while the x-axis lists the different state categories, with the title at the top labeling the chart's purpose.

Dataset version 1.0
Total number of images: 5978
Total number of classes: 7
Download:

A bar chart displaying the count of different food preparation methods, with "Whole" and "Sliced" categories having the highest counts, while "Grated," "Julienne," "Diced," "Juice," and "Paste" show varying lower counts. The y-axis represents the count, and the x-axis lists the preparation classes.

Md. Sadman Sakib
Department of CSE, 色色研究所, United States
mdsadman@usf.edu

Results for Dataset version 1.0

Cooking State Recognition Challenge Papers
Name Paper Accuracy
Tianze Chen 80%
Rahul Paul 77%
Astha Sharma 76%
Md Sirajus Salekin 73.3%