czeslov / weather-classification

This model classifies weather conditions based on images. It uses a Convolutional Neural Network (CNN) trained on various weather phenomena to predict the weather condition of a given image.

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Weather Classification Model

This model classifies weather conditions from images using a deep learning approach. The model was trained on a dataset of various weather phenomena and can predict one of the following weather classes:

Dew
Fog/Smog
Frost
Glaze
Hail
Lightning
Rain
Rainbow
Rime
Sandstorm
Snow

Features:

Real-time predictions: Classifies weather images quickly, ideal for applications requiring fast response times.
Multiple classes: Can detect and classify 11 different weather conditions.
Efficient architecture: Optimized to be lightweight and fast, suitable for various platforms.

Usage:

Inputs:

Image: A single image of weather conditions. The image should be a .jpg, .png, or similar format and will be resized to 200x200 pixels before processing.

Output:

Predicted Class: The model will return the predicted weather class based on the image input