Manual Image Classifier

Description

This script is a tool for manually classifying images into predefined categories. It connects to a remote server to fetch images, displays them to the user, and allows the user to classify these images into various categories based on visual inspection.

Features

• Connects to a remote server using SSH
• Downloads and displays images for classification
• Supports categorizing images into user-defined categories
• Moves classified images on the server to corresponding directories within the server
• Copies classified images from server to a local directory structure

Installation

1. Clone the repository: git clone https://github.com/martinezeth/manual-image-classifier.git

2. Navigate to the project directory

Conda Environment

You will need to run the following command to generate a Conda enviroment: conda create -n manual-classifier python=3 Then, activate your environment using the next command: conda activate manual-classifier Install dependencies with the command: pip install -r requirements.txt

Configuration

Prior to first using this script, there are a few things that need to be configured:

1. Create a .ini file named config.ini within the project directory.
2. Copy and paste the contents of the sample.config.ini into your created config.ini file.
3. Make sure to put the server hostname, your SSH username and password in the respective fields. The classifications_path should be the path to the 'Classifications' folder on your local machine. (Or the main directory that holds subfolders with each representing classification categories.)
4. The remote_classifications_path should be the path to the 'Classifications' folder on your server.

IMPORTANT: When adding your information to your config.ini file, make sure to not include anything extra (surrounding quotation marks, brackets, etc.) around the text.

Usage

Assuming that you are in the project directory, run the script from the command line: python manualClassifier.py

Follow the on-screen prompts to begin classifying images.

Contributions

Please feel free to fork the project and submit pull requests. You are more than welcome to use my script, but please give appropriate credit!

License

MIT License