https://github.com/dnth/microalgae-cell-counter-blogpost

Accompanying repo for the blogpost Modelling a Microalgae Cell Counter with Deep Learning on dicksonneoh.com
https://github.com/dnth/microalgae-cell-counter-blogpost

Last synced: about 2 months ago
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Accompanying repo for the blogpost Modelling a Microalgae Cell Counter with Deep Learning on dicksonneoh.com

• Host: GitHub
• URL: https://github.com/dnth/microalgae-cell-counter-blogpost
• Owner: dnth
• Created: 2022-04-07T06:44:02.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2022-06-15T05:24:29.000Z (almost 3 years ago)
• Last Synced: 2025-03-25T18:12:22.424Z (about 2 months ago)
• Language: Jupyter Notebook
• Size: 116 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# Training a Deep Learning Model for Cell Counting in 17 Lines of Code with 17 Images

![image](https://dicksonneoh.com/images/portfolio/training_dl_model_for_cell_counting/post_image.png)

This is an accompanying repo for the blog post Training a Deep Learning Model for Cell Counting in 17 Lines of Code with 17 Images.

Link to the full blog post

https://dicksonneoh.com/portfolio/training_dl_model_for_cell_counting/

In this blog post, I will walk you through how to use the IceVision library and train a state-of-the-art deep learning model with Fastai to count microalgae cells.

Among the things you will learn:

* Installation of the libraries.

* Prepare and label any dataset for object detection.

* Train a high-performance VFNet model with IceVision & Fastai.

* Use the model for inference on new images.

By the end of the post, you will have an object detection model that will automatically detect microalgae cells from an image.

![image](https://dicksonneoh.com/portfolio/training_dl_model_for_cell_counting/inference_hu4e27c33022e9aff192e501fa00651150_1733072_720x0_resize_box_3.png)

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