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+# Dataset Card for Bacterial Morphology Classification Dataset
+
+## Dataset Summary
+
+This dataset contains images of bacteria categorized into three morphological classes: cocci, bacilli, and spirilla. It is designed for training, validating, and testing machine learning models for bacterial morphology classification.
+
+## Dataset Details
+
+### Dataset Description
+
+This dataset was created to support research in microbiology and machine learning, focusing on bacterial morphology classification. Images in the dataset are labeled into three classes: cocci, bacilli, and spirilla. The dataset was processed to ensure compatibility and uniformity, including re-saving images in the RGB JPEG format to address encoding issues.  
+
+* Dataset Title: Bacterial Morphology Classification
+* Dataset Curator: Yola Charara, University of Michigan-Flint, M.S Data Science-Student
+* Dataset Version: The data was collected from September 28, 2024 till October 1, 2024.
+* Data Card Author: Yola Charara, University of Michigan-Flint, M.S Data Science-Student
+* Data Statement Version: December 6, 2024
+* License: CC BY 4.0
+
+## Uses
+
+### Direct Use
+
+The dataset is intended for training and evaluating machine learning models to classify bacteria by morphology, supporting tasks in microbiology and biomedical research.
+
+### Out-of-Scope Use
+
+The dataset is not suitable for applications outside bacterial morphology classification. Misuse could include attempts to infer specific bacterial species or other unrelated properties.
+
+## Dataset Structure
+
+The dataset is divided into training, validation, and test sets. Images in the training and validation sets are grouped by class, while the test set contains images without class-based folders.
+
+## Dataset Creation
+
+### Curation Rationale
+
+The dataset was created to facilitate automated bacterial classification, reducing reliance on manual microscopy analysis and accelerating research workflows.
+
+### Source Data
+
+#### Data Collection and Processing
+
+Images were curated from the python library bing-downloader which downloads a bulk of images from bing images. Preprocessing included resizing, normalizing, and re-saving all `.jpg` images in RGB mode to ensure compatibility and resolve encoding issues.
+
+#### Who are the source data producers?
+
+The images were sourced from microbiological research or publicly available datasets. Specific data producers are not disclosed.
+
+### Annotations 
+
+#### Annotation process
+
+Each image was labeled based on its morphological class by graduate students.
+
+#### Personal and Sensitive Information
+
+The dataset does not contain any personal or sensitive information.
+
+## Bias, Risks, and Limitations
+
+The dataset is limited to three morphological classes and may not generalize well to other bacterial shapes or conditions. There may be inherent biases in the dataset depending on the sources of the images.
+
+### Recommendations
+
+Users should test models on other datasets to ensure generalizability and reduce bias, as this dataset may not cover all variations. Additional data from diverse sources is recommended to improve model robustness.
+
+## Glossary 
+
+**Cocci:** Round-shaped bacteria.  
+**Bacilli:** Rod-shaped bacteria.  
+**Spirilla:** Spiral-shaped bacteria.
+
+## More Information 
+
+Codalab link for this dataset: https://codalab.lisn.upsaclay.fr/competitions/20680?secret_key=b04da988-294a-4491-831c-3f4b55529a0b 
+
+## Dataset Card Contact
+
+email: yolac@umich.edu