Colony Counter is an application within the CarbConnect platform. It automatically detects and counts bacterial colonies from agar plate images.
The application returns the total colony count and bounding boxes for detected colonies, with optional annotated output for visualization.
This repository contains the model card for the private Hugging Face model repository associated with the application. A companion Space for this app already exists under the CarbGeM organization.
Intended Use and Limitations
Research Use Only (RUO).
This tool is strictly intended for research use only and is not for use in clinical diagnostics or medical procedures. For further details, please refer to the Colony Counter Learn More page on CarbConnect.
Intended users
Microbiologists
Researchers
Laboratories performing bacterial colony analysis
Out-of-scope use
Clinical diagnostics
Medical procedures
Use as a standalone diagnostic device
Practical limitations
Output quality depends on the quality, angle, lighting, and resolution of the agar plate image.
Colony overlap, artifacts, reflections, and dense growth patterns may affect detection accuracy.
Results are intended to support research workflows and should not replace expert review.
How to Use
Typical workflow:
Capture or upload an image of an agar plate.
Run inference through the Colony Counter application.
Review the total colony count and the detected bounding boxes.
Optionally inspect the annotated output image for visual verification.
Use the result for research support only, not for clinical decision-making.
Training Data
The model was trained using the following dataset:
Dataset name: Annotated dataset for deep-learning-based bacterial colony detection
Description: A dataset containing 369 digital images of 24 bacteria species cultures of veterinary importance, with a total of 56,865 manually annotated bounding boxes for bacterial colonies
Modifications: The dataset was used in its original form without any modifications
Outputs
For each processed image, the application can provide:
Total detected colony count
Bounding boxes for detected colonies
Optional annotated output image
Citation
If you use or reference the training dataset, please cite:
Solymosi, Norbert and Nagy, Sára. Annotated dataset for deep-learning-based bacterial colony detection. figshare. Dataset. 10.6084/m9.figshare.22022540
