implementing app

app.py

@@ -83,13 +83,15 @@ if image_file is not None:
        os.makedirs("uploads/images")
    with open(os.path.join("uploads/images/","0.png"),"wb") as f: 
         f.write(image_file.getbuffer()) 
-   st.success("Saved File")
+   #st.success("Saved File")
    dataset.prepare_data()
    trainer = pl.Trainer(logger=False)
+   st.write('Predicting atoms,bonds,charges,..., please wait')
    atom_preds = trainer.predict(model_atom, dataset.test_dataloader())
    bond_preds = trainer.predict(model_bond, dataset.test_dataloader())
    stereo_preds = trainer.predict(model_stereo, dataset.test_dataloader())
    charge_preds = trainer.predict(model_charge, dataset.test_dataloader())
+   st.write('Done')
    #st.write(atom_preds)
    plt.imshow(image, cmap="gray")
    for bbox, label in zip(atom_preds[0]['boxes'][0], atom_preds[0]['preds'][0]):