add explanation

app.py

@@ -62,9 +62,11 @@ demo = gr.Interface(run_front_detection, gr.Image(type='pil'), "image", title='C
                                  by Isensee, F., Jaeger, P. F. (2020) https://github.com/MIC-DKFZ/nnUNet and  \
                                 and was trained and tested with the dataset of Gourmelon et al. \
                                 https://doi.pangaea.de/10.1594/PANGAEA.940950. <p> <p>\
-                                Drag & Drop a PNG image and click 'Submit' to apply the calving front detection. <p> \
-                                For images larger than 200KB we suggest to run on your own PC, this platform providese limited computational resources. ",
-
+                                Drag & Drop a PNG image and click 'Submit' to apply the calving front detection or clock on an example image below. <p> \
+                                For images larger than 200KB we suggest to run on your own PC, this platform providese limited computational resources. <p>\
+                                The output shows an overlay of the segmentation mask generated by the network over the input image. Area of ocean is colored in blue, glacier in white, rock in gray and radar shadow in black.\
+                                The claving front is a thin red line.",
+                    min_height=5000,
                     examples=[os.path.join(os.path.dirname(__file__), "test_sar_images/Mapple_2018-06-11_S1_20_2_009.png"),
                               os.path.join(os.path.dirname(__file__), "test_sar_images/COL_2011-06-18_TDX_7_1_024_small.png"),])