@tejaswi0910 and @Nitya-Pasrija
Please reach out to the maintainers if you get stuck or wish to report someone.
Image classification refers to the task of extracting information classes from a multiband raster image. The resulting raster from image classification can be used to create thematic maps. Image Classification is a fundamental task that attempts to comprehend an entire image as a whole. The goal is to classify the image by assigning it to a specific label. Typically, Image Classification refers to images in which only one object appears and is analyzed. In contrast, object detection involves both classification and localization tasks, and is used to analyze more realistic cases in which multiple objects may exist in an image. Depending on the interaction between the analyst and the computer during classification, there are two types of classification: supervised and unsupervised.
There are 2 types of classifications-
Supervised classification Supervised classification uses the spectral signatures obtained from training samples to classify an image. With the assistance of the Image Classification toolbar, you can easily create training samples to represent the classes you want to extract. You can also easily create a signature file from the training samples, which is then used by the multivariate classification tools to classify the image.
Unsupervised classification Unsupervised classification finds spectral classes (or clusters) in a multiband image without the analyst’s intervention. The Image Classification toolbar aids in unsupervised classification by providing access to the tools to create the clusters, the capability to analyze the quality of the clusters and access to classification tools.
This repository consists of various machine learning projects, and all of the projects must follow a certain template. I hope the contributors will take care of this while contributing to this repository.
Dataset - This folder stores the dataset used in this project. If the Dataset is not able to upload in this folder due to the large size, then put a README.md file inside the Dataset folder and put the link of the collected dataset in it. That'll work!
Images - This folder is used to store the images generated during the data analysis, data visualization, and data segmentation of the project.
Model - This folder would have your project file (that is .ipynb file) be it analysis or prediction.
https://youtube.com/playlist?list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi&utm_source=EKLEiJECCKjOmKnC5IiRIQ https://youtube.com/playlist?list=PLZoTAELRMXVPBTrWtJkn3wWQxZkmTXGwe&utm_source=EKLEiJECCKjOmKnC5IiRIQ
You can take up any of the existing issues or create a new one to contribute!
Contribution period ends: 28 January 2024
You can refer to the following resources on Git and Github to get started and contact our Project Mentors via Discord if you have any doubts.