implementing app

app.py

@@ -53,5 +53,12 @@ if image_file is not None:
    dataset.prepare_data()
    trainer = pl.Trainer(logger=False)
    atom_preds = trainer.predict(model_atom, dataset.test_dataloader())
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+   st.write(atom_preds)
+   #plt.imshow(im, cmap="gray")
+   #     for bbox, label in zip(bboxes_XYXY, labels):
+   #         plot_bbox(bbox, label)
+   #     plt.axis('off')
+   #     plt.savefig("example_image.png",bbox_inches='tight', pad_inches=0)
+   #     plt.show()
+#x = st.slider('Select a value')
+#st.write(x, 'squared is', x * x)