Skip to content

This repository implements a Convolutional Neural Network (CNN) for classifying and predicting biomaterial attachment levels. It supports both regression and classification tasks, enabling precise analysis of biomaterial interactions.

Notifications You must be signed in to change notification settings

Karthi-DStech/CNN-for-Predicting-Attachment-Level-of-Bacteria

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

CNN-for-Predicting-Attachment-Level-of-Bacteria

This repository implements a Convolutional Neural Network (CNN) for classifying and predicting biomaterial attachment levels. It supports both regression and classification tasks, enabling precise analysis of biomaterial interactions. The CNN model is designed to handle complex data, providing accurate predictions and classifications to advance research in biomaterial science.

This Highly scalable framework allows for easy addition of more combinations in the future and can be seamlessly transferred to other projects.

Project Structure

  • models/:

    • CNN.py: Implementation of CNN Architecture for Supervised-Learning.
    • Networks.py: Implementation of Base Network (parent) definitions and configurations for the CNN architecture.
  • options/:

    • base_options.py: Basic Command-line arguments for the training script.
    • train_options.py: Hyperparameter Command-line arguments for the training script.
  • utils/:

    • images_utils.py: Utilities for image handling.
    • visualizer.py: This file provides scripts for a TensorBoard visualizer for tracking training progress.
    • weights_init.py: This file contains scripts for weight initialization functions for the CNN architecture.
  • train.py: Script for training the model.

  • call_methods.py: This file contains scripts for dynamically creating models, networks, datasets, and data loaders based on provided names and options.

Requirements

To run the code, you need the following:

Python 3.8 or above PyTorch 1.7 or above torchvision tqdm matplotlib TensorboardX 2.7.0 Install the necessary packages using pip:

About

This repository implements a Convolutional Neural Network (CNN) for classifying and predicting biomaterial attachment levels. It supports both regression and classification tasks, enabling precise analysis of biomaterial interactions.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages