Image-Classification-Streamlit-TensorFlow

A basic web-app for image classification using Streamlit and TensorFlow.

It classifies the given image of a flower into one of the following five categories :-

1. Daisy
2. Dandelion
3. Rose
4. Sunflower
5. Tulip

Commands

To run the app locally, use the following command :-
streamlit run app.py

The webpage should open in the browser automatically.
If it doesn't, the local URL would be output in the terminal, just copy it and open it in the browser manually.
By default, it would be http://localhost:8501/

Click on Browse files and choose an image from your computer to upload.
Once uploaded, the model will perform inference and the output will be displayed.

Output

Notes

• A simple flower classification model was trained using TensorFlow.
• The weights are stored as flower_model_trained.hdf5.
• The code to train the modify and train the model can be found in model.py.
• The web-app created using Streamlit can be found in app.py

References

• https://www.tensorflow.org/tutorials/images/classification
• https://docs.streamlit.io/en/stable/