corrected app.py file

[sai-charan1]

Pull Request Description:

Title: Add Streamlit App for Solar Panel Dust Detection with Model Integration

Description:
This update introduces a Streamlit web application for predicting solar panel dust accumulation based on uploaded images. The app leverages a pre-trained deep learning model for image classification, and users can easily interact with it by uploading images of solar panels to receive predictions.

Changes Made:

• Implemented the Streamlit interface for image upload.
• Integrated model loading functionality, which now loads both the model architecture from best_model.json and the weights from best_model.h5.
• Added image preprocessing steps to ensure compatibility with the trained model.
• Enabled model predictions on uploaded images and displayed the output in a user-friendly format.

How to Test:

1. Run the Streamlit app using the command: streamlit run app.py.
2. Navigate to http://localhost:8501 in your browser.
3. Upload an image of a solar panel to receive a prediction of dust accumulation.

Images after upadting code