metadata

license: apache-2.0
task_categories:
  - image-classification
language:
  - en
tags:
  - Weather
  - Classification
size_categories:
  - 10K<n<100K

WeatherNet-05-18039

Overview

WeatherNet-05 is a weather image classification dataset consisting of 18,039 images labeled into 5 distinct weather-related classes. The dataset is suitable for training and evaluating computer vision models on the task of classifying weather conditions based on image data.

Dataset Structure

Split: train
Number of rows: 18,039
Label Type: Categorical (5 classes)
Image Resolution: Varies (from 90px to 4.86k px width)
File Format: Auto-converted to Parquet for efficient processing

Label Classes

The dataset contains the following classes (not fully visible in the image but inferred from partial data):

cloudy or overcast
[4 other class names not displayed in the screenshot]

Usage

You can use the dataset directly with Hugging Face's datasets library:

from datasets import load_dataset

dataset = load_dataset("prithivMLmods/WeatherNet-05-18039")

Applications

This dataset is ideal for:

Weather image classification
Transfer learning with visual transformers
Fine-tuning pre-trained computer vision models

Related Models

This dataset has been used to train or fine-tune models such as:

prithivMLmods/Weather-Image-Classification (Image Classification)

Collections

This dataset is part of the collection:

Content Filters SigLIP2/ViT (Moderation, Balance, Contextual Understanding)