
# Dataset Card for Pizza or Not Pizza?

## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** https://kaggle.com/datasets/carlosrunner/pizza-not-pizza
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary

Who doesn't like pizza? This dataset contains about 1000 images of pizza and 1000 images of dishes other than pizza. It can be used for a simple binary image classification task.

All images were rescaled to have a maximum side length of 512 pixels. 

This is a subset of the Food-101 dataset. Information about the original dataset can be found in the following paper: 
Bossard, Lukas, Matthieu Guillaumin, and Luc Van Gool. "Food-101 – Mining Discriminative Components with Random Forests." In *European conference on computer vision*, pp. 446-461. Springer, Cham, 2014.

The original dataset can be found in the following locations:
https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/
https://www.kaggle.com/datasets/dansbecker/food-101
https://paperswithcode.com/dataset/food-101
https://www.tensorflow.org/datasets/catalog/food101

Number of instances in each class:
Pizza: 983
Not Pizza: 983

##Acknowledgements

The Food-101 data set consists of images from Foodspotting [1] which are not property of the Federal Institute of Technology Zurich (ETHZ). Any use beyond scientific fair use must be negociated with the respective picture owners according to the Foodspotting terms of use [2].

[1] http://www.foodspotting.com/
[2] http://www.foodspotting.com/terms/

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

[More Information Needed]

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

[More Information Needed]

### Data Splits

[More Information Needed]

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

This dataset was shared by [@carlosrunner](https://kaggle.com/carlosrunner)

### Licensing Information

The license for this dataset is other

### Citation Information

```bibtex
[More Information Needed]
```

### Contributions

[More Information Needed]
license:other region:us
{"license": ["other"], "kaggle_id": "carlosrunner/pizza-not-pizza"}
TAGS
#license-other #region-us 


# Dataset Card for Pizza or Not Pizza?

## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions

## Dataset Description

- Homepage: URL
- Repository:
- Paper:
- Leaderboard:
- Point of Contact:

### Dataset Summary

Who doesn't like pizza? This dataset contains about 1000 images of pizza and 1000 images of dishes other than pizza. It can be used for a simple binary image classification task.

All images were rescaled to have a maximum side length of 512 pixels. 

This is a subset of the Food-101 dataset. Information about the original dataset can be found in the following paper: 
Bossard, Lukas, Matthieu Guillaumin, and Luc Van Gool. "Food-101 – Mining Discriminative Components with Random Forests." In *European conference on computer vision*, pp. 446-461. Springer, Cham, 2014.

The original dataset can be found in the following locations:
URL
URL
URL
URL

Number of instances in each class:
Pizza: 983
Not Pizza: 983

##Acknowledgements

The Food-101 data set consists of images from Foodspotting [1] which are not property of the Federal Institute of Technology Zurich (ETHZ). Any use beyond scientific fair use must be negociated with the respective picture owners according to the Foodspotting terms of use [2].

[1] URL
[2] URL

### Supported Tasks and Leaderboards



### Languages



## Dataset Structure

### Data Instances



### Data Fields



### Data Splits



## Dataset Creation

### Curation Rationale



### Source Data

#### Initial Data Collection and Normalization



#### Who are the source language producers?



### Annotations

#### Annotation process



#### Who are the annotators?



### Personal and Sensitive Information



## Considerations for Using the Data

### Social Impact of Dataset



### Discussion of Biases



### Other Known Limitations



## Additional Information

### Dataset Curators

This dataset was shared by @carlosrunner

### Licensing Information

The license for this dataset is other





### Contributions


# Dataset Card for Pizza or Not Pizza? ## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## Dataset Description

- Homepage: URL
- Repository:
- Paper:
- Leaderboard:
- Point of Contact: ### Dataset Summary

Who doesn't like pizza? This dataset contains about 1000 images of pizza and 1000 images of dishes other than pizza. It can be used for a simple binary image classification task.

All images were rescaled to have a maximum side length of 512 pixels. 

This is a subset of the Food-101 dataset. Information about the original dataset can be found in the following paper: 
Bossard, Lukas, Matthieu Guillaumin, and Luc Van Gool. "Food-101 – Mining Discriminative Components with Random Forests." In *European conference on computer vision*, pp. 446-461. Springer, Cham, 2014.

The original dataset can be found in the following locations:
URL
URL
URL
URL

Number of instances in each class:
Pizza: 983
Not Pizza: 983 ### Supported Tasks and Leaderboards ### Languages ## Dataset Structure ### Data Instances ### Data Fields ### Data Splits ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators

This dataset was shared by @carlosrunner ### Licensing Information

The license for this dataset is other ### Contributions
TAGS
#license-other #region-us 
 # Dataset Card for Pizza or Not Pizza? ## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## Dataset Description

- Homepage: URL
- Repository:
- Paper:
- Leaderboard:
- Point of Contact: ### Dataset Summary

Who doesn't like pizza? This dataset contains about 1000 images of pizza and 1000 images of dishes other than pizza. It can be used for a simple binary image classification task.

All images were rescaled to have a maximum side length of 512 pixels. 

This is a subset of the Food-101 dataset. Information about the original dataset can be found in the following paper: 
Bossard, Lukas, Matthieu Guillaumin, and Luc Van Gool. "Food-101 – Mining Discriminative Components with Random Forests." In *European conference on computer vision*, pp. 446-461. Springer, Cham, 2014.

The original dataset can be found in the following locations:
URL
URL
URL
URL

Number of instances in each class:
Pizza: 983
Not Pizza: 983 ### Supported Tasks and Leaderboards ### Languages ## Dataset Structure ### Data Instances ### Data Fields ### Data Splits ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators

This dataset was shared by @carlosrunner ### Licensing Information

The license for this dataset is other ### Contributions
passage: TAGS
#license-other #region-us 
# Dataset Card for Pizza or Not Pizza?## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions## Dataset Description

- Homepage: URL
- Repository:
- Paper:
- Leaderboard:
- Point of Contact:### Dataset Summary

Who doesn't like pizza? This dataset contains about 1000 images of pizza and 1000 images of dishes other than pizza. It can be used for a simple binary image classification task.

All images were rescaled to have a maximum side length of 512 pixels. 

This is a subset of the Food-101 dataset. Information about the original dataset can be found in the following paper: 
Bossard, Lukas, Matthieu Guillaumin, and Luc Van Gool. "Food-101 – Mining Discriminative Components with Random Forests." In *European conference on computer vision*, pp. 446-461. Springer, Cham, 2014.

The original dataset can be found in the following locations:
URL
URL
URL
URL

Number of instances in each class:
Pizza: 983
Not Pizza: 983### Supported Tasks and Leaderboards### Languages## Dataset Structure### Data Instances### Data Fields### Data Splits## Dataset Creation### Curation Rationale### Source Data#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### Annotation process#### Who are the annotators?### Personal and Sensitive Information## Considerations for Using the Data### Social Impact of Dataset### Discussion of Biases### Other Known Limitations## Additional Information### Dataset Curators

This dataset was shared by @carlosrunner