Weather Status Predictor From Images
About the Project
predicting weather status has been a rich field to apply the technology of machine learning (ML) and deep learning (DL) along with Convolutional Neural Network (CNN). There are so many examples of projects with various level of accuracy and advance that predict or classify the weather status from given satellite images in visible light, infrared ranges, or other light spectra. However, for this project I will do a similar approach but with images taken with smart phones or digital cameras of a landscape views, then try to predict the appearing weather status in that appearance. I used different algorithms for ML using only two classes, that is, sunny and cloudy. For CNN I used the entire dataset of more than 18K images with 5-class weather status. Each image is 200x200 pixels with 3-channel colors.
Online Predictor
The final models that I reached are deployed on Heroku TRY NOW you can predict on binary classification or with 5-class classification. Check the confusion matrix
Data Dictionary
You can find the dataset in Kaggle, where more details about the data is given.
Data Summary
| Class | Folder | Images Count |
|---|---|---|
| Sunny | sunny | 6702 |
| Cloudy | cloudy | 6274 |
| Foggy | foggy | 1261 |
| Rainy | rainy | 1927 |
| Snowy | snowy | 1875 |
| Total | - | 18039 |