https://github.com/adamw78/blobcounter

GUI-based application utilizing computer vision to count numbers of yeast cell colonies
https://github.com/adamw78/blobcounter

bmp computer-vision cv excel gif gui jpg machine-learning ml multithreading opencv openpyxl png pyinstaller pyside6 python qt6 tiff xlsx xml

Last synced: 3 months ago
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GUI-based application utilizing computer vision to count numbers of yeast cell colonies

• Host: GitHub
• URL: https://github.com/adamw78/blobcounter
• Owner: AdamW78
• Created: 2025-04-08T20:37:54.000Z (6 months ago)
• Default Branch: master
• Last Pushed: 2025-07-12T17:56:36.000Z (3 months ago)
• Last Synced: 2025-07-12T19:41:51.530Z (3 months ago)
• Topics: bmp, computer-vision, cv, excel, gif, gui, jpg, machine-learning, ml, multithreading, opencv, openpyxl, png, pyinstaller, pyside6, python, qt6, tiff, xlsx, xml
• Language: Python
• Homepage:
• Size: 93.9 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Blob Counter

![](img/Exampleusage.png)

## About

BlobCounter is a GUI-based application that allows for parametrized automatic detection of blobs. 

It was originally developed to count colonies of yeast cells.

It is performance-optimized to allow for the handling of large images (up to 10000x10000 pixels)

and can be used for batch processing of images. 

It also provides a simple way to visualize the results of the blob detection process. 

Detected blobs are circled in red, and all images are pannable, zoomable, and savable.

Most significantly, BlobCounter allows for human intervention in the blob detection process.

The user can manually add or remove blobs from the detection results, and the application will update the results accordingly.

This allows for a more accurate detection process, especially in cases where the automatic detection process is not perfect.

As a result, this software works an excellent tool for generating training data for machine learning applications 

in addition to its primary purpose of blob detection for research pruposes.

## Features

- GUI-based application

- Parametrized automatic blob detection

- Batch processing of images

- Human intervention in the detection process

- Visualization of results

- Performance-optimized for large images

- Undo/Redo functionality

- Counted-image saving to PNG

- Counted blobs saved to XML

- Automatic, formatted output to XLSX

## Usage