The data comes from The Humane League's US Egg Production dataset by Samara Mendez. Dataset and code is available for this project on OSF at US Egg Production Data Set.

This dataset tracks the supply of cage-free eggs in the United States from December 2007 to February 2021. For TidyTuesday we've used data through February 2021, but the full dataset, with data through the present, is available in the OSF project.

Data Dictionary

egg-production.csv

cage-free-percentages.csv

Eggs US rose to 2.70 USD/Dozen on July 11, 2025, up 1.13% from the previous day. Over the past month, Eggs US's price has risen 1.47%, and is up 15.69% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Eggs US.

Egg Size Detection

## Overview

Egg Size Detection is a dataset for object detection tasks - it contains Objects annotations for 756 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

1) Data Introduction • The Egg Image Dataset is constructed by collecting images of eggs captured in real-world environments, classified based on whether the eggs are damaged or not damaged.

2) Data Utilization (1) Characteristics of the Egg Image Dataset: • It includes images collected from various real-world settings such as kitchens, farms, and markets, making it highly effective for model training and improving data generalization. • The dataset provides a clear distinction between damaged and undamaged eggs, making it suitable for solving problems related to object recognition and quality inspection.

(2) Applications of the Egg Image Dataset: • Development of Object Recognition and Quality Classification Models: It can be used to train AI models to automatically detect and classify eggs based on their damage status. • Utilization in Research and Development (R&D): The dataset can be applied to various R&D projects, including product quality management and the development of automated inspection systems.

Here are a few use cases for this project:

1. Poultry Farm Management: The model can be used by poultry farmers to automate the process of counting the number of eggs produced each day. This will help improve accuracy and reduce time consumption, improving overall productivity.

2. Supermarket Inventory Management: Retail businesses can use the model to monitor egg stocks, helping to ensure they always have enough products available for customers, and also help with efficient restocking plans.

3. Egg Production Quality Control: In egg production factories, this model could help detect eggs on the conveyor belt, assisting in the identification of any broken or defective eggs which need to be removed from the production line.

4. Ecological Studies: The model can be used by ecologists to count the number of eggs in bird nests or other wildlife species, which can provide valuable data for ecological research and conservation efforts.

5. Culinary Industry: Restaurants or large-scale catering services can use this model to maintain accurate counts of eggs used in their kitchen, aiding in precise portion control and cost management.

This dataset was created as part of Aldrumont Ferraz Júnior's master's thesis, titled "Development of an Automated Method to Estimate the Mass of Chicken Egg Components Using Computer Vision and Artificial Intelligence."

The dataset contains videos and mass measurements of eggs collected to train artificial intelligence models capable of estimating the mass of egg components (yolk, albumen, and shell) from ovoscopic images. The eggs were filmed under four different light sources (blue, green, red, and white LEDs) in two distinct orientations (tip-up and tip-down). Each egg has a unique identification index and detailed measurements of its assessed mass.

This work contributes to the automation of egg classification and quality assessment in the poultry industry, reducing dependence on manual methods and improving estimation accuracy. If you use this dataset in your research, please credit this work accordingly.

Missing Data: Some rows in the dataset contain missing values, indicating that data collection was unsuccessful for those specific cases. The main reasons for these missing values include:

Egg damage during handling, which made it impossible to measure the mass components. Errors in mass measurement, leading to data inconsistency and exclusion. Issues during video recording, such as incorrect lighting conditions or equipment malfunctions. Data filtering criteria, where some samples were removed due to deviations greater than 2% between measured and calculated total mass. Dataset Column Descriptions data → The date when image collection and mass assessment were performed. video A → The name of the video captured for the egg under different lighting conditions, considering a specific orientation. video B → The name of the second video for the same egg, but filmed in a different orientation. index → A unique identifier for the egg, ensuring traceability between images and mass measurements. Shell → Measured mass of the eggshell (in grams). Yolk + Albumen → Measured mass of the yolk and albumen combined (in grams). Albumen → Measured mass of the albumen (in grams). Total Measured Mass → The total mass of the egg before separating its components. Yolk → Measured mass of the yolk (in grams). Total Calculated Mass → The sum of the measured masses of the egg components (shell, albumen, and yolk). Mass Difference (Calculated vs. Measured) → The difference between the total measured mass and the total calculated mass, used for data consistency analysis. 100% - (Calculated/Measured Mass) → The percentage difference between the measured and calculated mass values. Shell / Total Measured Mass → The proportion of the shell relative to the total egg mass. Yolk / Total Measured Mass → The proportion of the yolk relative to the total egg mass. Albumen / Total Measured Mass → The proportion of the albumen relative to the total egg mass. This dataset is a valuable resource for studies in computer vision, machine learning, and poultry industry applications. If you use this dataset, please cite Aldrumont Ferraz Júnior and his thesis.

Eggs CH rose to 3,450 CNY/T on July 11, 2025, up 0.09% from the previous day. Over the past month, Eggs CH's price has risen 23.26%, but it is still 23.82% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Eggs CH.

The "Egg Model" is a synthetic reservoir model consisting of an ensemble of 101 relatively small three-dimensional realizations of a channelized reservoir produced under water flooding conditions with eight water injectors and four producers. This data set represents a "standard version" of the Egg Model which is meant to serve as a standard test case in future publications. We implemented and tested the model in four reservoir simulators: Dynamo/Mores (Shell), Eclipse (Schlumberger), AD-GPRS (Stanford University) and MRST (Sintef). This data set also contains the input files for the various simulators.

Egg Quality

## Overview

Egg Quality is a dataset for object detection tasks - it contains Good_quality annotations for 1,042 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Dataset Card for Parasitic Egg Image Classification Dataset

This dataset card aims to be a base template for the Parasitic Egg Image Classification Dataset. It has been generated using this raw template.

  Dataset Details





  Dataset Description

This dataset is designed for the classification of parasitic eggs from microscopic images. Parasitic infections are a major health concern, particularly in developing countries, where parasites are a significant cause of… See the full description on the dataset page: https://huggingface.co/datasets/Abdelkareem/parasitic-egg.

This dataset includes data on China's egg market transaction prices from 2014-2021 and consists of 2 parts: (1) text data including the national egg market retail price statistics table (weekly), the national egg market wholesale price statistics table (daily), the national egg market wholesale price change information, the national and 12 provinces (autonomous regions and municipalities directly under the central government) monthly average wholesale prices and information on the rate of change; (2) picture data sets include monthly average wholesale prices and weekly retail prices and their rate of change line graphs for the national egg market from 2014-2021.

Large white, Grade A chicken eggs, sold in a carton of a dozen. Includes organic, non-organic, cage free, free range, and traditional."

This dataset is about books. It has 1 row and is filtered where the book is Egg : the definitive guide to choosing, cooking and enjoying eggs. It features 7 columns including author, publication date, language, and book publisher.

market123/egg dataset hosted on Hugging Face and contributed by the HF Datasets community

Hatching Eggs

## Overview

Hatching Eggs is a dataset for object detection tasks - it contains Reptile Eggs annotations for 273 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

🍳This dataset is just a cumulation of eggs produced in India, statewise with the number of eggs produced in each Indian State from the years 2004-2020.

🍳The data can be used for EDAs, visualizations, ML models, Analytics or even demand forecasting or recommendation plans.

Image by Couleur from Pixabay

Egg DatasetA tab delimited dataset of insect egg shape and size from the published literature, including additional variables (e.g. volume, aspect ratio) calculated from data in egg_dataset_raw_values.tsv. See publication methods for details on how final values were calculated.egg_dataset.tsvEgg Dataset (Raw Values)A tab delimited dataset of insect egg shape and size from the published literature, reporting the values as recorded (e.g. original published taxonomic name, text description of maximum and minimum egg length). See publication for details and on how data was collected.egg_dataset_raw_values.tsvBibliography Egg Dataset (BibTeX format)A bibtex file of sources cited in the egg dataset. References listed here can be matched to entries in the egg dataset by their unique bibliographic identifier (e.g. Iwata1958).bibliography_egg_dataset.bibBibliography Egg Dataset (PDF format)A formatted bibliography of sources cited in the egg dataset.bibliography_egg_dataset.pdf

A dataset of eggs with annotations for egg and crack classes. A total of 840 images with 740 train and 100 test images.

This dataset collection contains monthly egg production data sourced from the website of Luke, the Natural Resources Institute Finland. It includes one or more dataset tables related to egg production in Finland. The tables provide information on the quantity of eggs produced each month, measured in kilograms. The dataset collection is a valuable resource for analyzing egg production trends in Finland and understanding the dynamics of the industry. The data is obtained from Luke's website, which is maintained by the Natural Resources Institute Finland, an organization dedicated to promoting sustainable development and the responsible use of natural resources in Finland.

This repository contains Electrogastrography signals termed Electrogastrograms (EGG) recorded with surface Ag/AgCl electrodes placed over stomach and pre-processed in 20 healthy individuals (8 Females and 12 Males). The method for EGG recording and pre-processing together with subjects' data can be found in Popović et al. 2019.

For each subject, EGG was recorded from three locations before (fasting state) and after (postprandial state) a commercial oat meal (274 kcal). Two 20 minutes recordings (files) are obtained for each subject - fasting and postprandial.

Naming convention for files: subjects ID _ type of recording (fasting / postprandial).

Sample rate was set at 2 Hz and A/D card had 16 bits resolution. Gain of the amplifier was set at 1000. Overall, file size is 7200 samples (2400 samples for each channel). All signals were filtered with 3rd order band-pass Butterworth filter with cut-off frequencies of 0.03 Hz and 0.25 Hz. In order to avoid phase distortion, zero-phase digital filtering was performed in Matlab R2013a by filtfilt() function. GNU Octave code for analysis of EGG signals with statistical calculations presented in Popović et al. 2019 is also provided (eggAnalysis.m).

For convenient test download and appropriate preview, we provided all signals in .zip and sample signal for ID1 in .txt form.

Dataset contents

EGG-database.zip, data files, text format

eggAnalysis.m, GNU Octave code

README.txt, metadata for data files, text format

ID1_fasting.txt and ID1_postprandial.txt, sample data files for subject ID1, text format

Data files contain numerical values with decimal point according to the following structure

column - CH1* (recorded samples from channel 1)

column - CH2* (recorded samples from channel 2)

column - CH3* (recorded samples from channel 3)

• For exact anatomical locations for EGG channels CH1, CH2, and CH3, please refer to Popović et al. 2019.

If you find these signals useful for your own research or teaching class, please cite both relevant paper and dataset as:

Popović, N.B., Miljković, N. and Popović, M.B., 2019. Simple gastric motility assessment method with a single-channel electrogastrogram. Biomedical Engineering/Biomedizinische Technik, 64(2), pp.177-185, doi: 10.1515/bmt-2017-0218.

Popović, N.B., Miljković, N. and Popović, M.B., 2020. Three-channel surface electrogastrogram (EGG) dataset recorded during fasting and post-prandial states in 20 healthy individuals [Data set]. Zenodo, doi: 10.5281/zenodo.3730617.

DISCLAIMER: The GNU Octave code is provided without any guarantee and it is not intended for medical purposes.