implementing app

app.py

@@ -62,9 +62,9 @@ if image_file is not None:
    dataset.prepare_data()
    trainer = pl.Trainer(logger=False)
    atom_preds = trainer.predict(model_atom, dataset.test_dataloader())
-   st.write(atom_preds)
+#   st.write(atom_preds)
    plt.imshow(image, cmap="gray")
-   for bbox, label in zip(atom_preds[0]['boxes'], atom_preds[0]['pred']):
+   for bbox, label in zip(atom_preds[0]['boxes'], atom_preds[0]['preds']):
        plot_bbox(bbox, label)
   
    col2.image(plt.show(), use_column_width=True)