https://github.com/universvm/bacxeption

Deep Learning Template for bacterial image classification in Keras.
https://github.com/universvm/bacxeption

bioinformatics biotechnology deep-learning neural-network

Last synced: 20 days ago
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Deep Learning Template for bacterial image classification in Keras.

• Host: GitHub
• URL: https://github.com/universvm/bacxeption
• Owner: universvm
• License: gpl-3.0
• Created: 2018-12-19T15:17:10.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2023-02-02T06:15:19.000Z (almost 2 years ago)
• Last Synced: 2024-05-21T12:09:39.306Z (6 months ago)
• Topics: bioinformatics, biotechnology, deep-learning, neural-network
• Language: Python
• Homepage:
• Size: 9.34 MB
• Stars: 8
• Watchers: 4
• Forks: 2
• Open Issues: 8
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        




Deep Learning for bacterial classification


# BacXeption

BacXeption is a Deep Learning template of image segmentation functions and a 

Convolutional Neural Network (CNN) built on Keras for bacterial image 

classification. It uses the Xception architecture with pre-trained weights (https://arxiv.org/abs/1610.02357). 

## Examples

## 1. Getting Started

This project requires Python 3.6+

### 1.1 Pre-requisites

Install the prerequisites with PIP

```

pip install -r requirements.txt

```

### 1.2 Running the trained model

1. Place the raw images in `data/test_data/`

2. Run `python main.py`

This should output labelled images with a .txt file of the coordinates of 

each box in the `output/$DATE_TIME` folder. Example: 



## 2. Training your own model

### 2.1 Two categories

1. Replace the images in the `data/0/` and `data/1/` with your 

images. 

2. Run `python train.py`

3. Move the `output/$DATE_TIME/model.json` and `output/$DATE_TIME/model.h5` 

in the `model/` folder.

4. Follow the instructions in section 1.2 

### 2.1 >Two categories

1. Change `NUM_CLASSES` in config.py to the number of classes wanted. 

2. Add your data in the `data/` folder. Each category should have a separate

 folder name, these must be integers starting from 0 (eg. `0/`,`1/`,`2/` for

  3 categories) 

3. Follow the instructions in section 2.1

## 3. Contributing

Pull requests and suggestions are always welcome. 

## 4. Additional information

### Authors

Leonardo Castorina - [universVM](https://github.com/universvm)

## Acknowledgments

[Dr. Teuta Pilizota](http://pilizotalab.bio.ed.ac.uk) - Proposing the 

problem and useful discussions. 

[Dario Miroli](https://github.com/DarioMiroli) – For introducing me to Keras

 and debugging early versions of BacXeption

 

[François Chollet](https://github.com/fchollet) – Developing Keras and 

Xception